Moving Average Rainbow (Stormer)This strategy is based and shown by trader and investor Alexandre Wolwacz "Stormer".
Overview
The strategy uses 12 moving averages (default EMA) to identify trends and generate trading signals opening positions.
Allowing to select the type of moving average and length to be used.
The conditions includes relationship between moving averages, the position of the current price relative to the moving averages, and the occurrence of certain price patterns.
Calculation
The mean moving averages is calculated by adding all the 12 moving averages and dividing by 12, the value is used to help to identify trend and possible condition to open position.
The 12 moving averages is spliced by 3 ranges, initial range (moving average lines 1 to 4), middle range (moving average lines 5 to 8) and end range (moving average lines 9 to 12). These ranges helps to identify potential trend and market turn over.
The moving average touch price is a relationship between the low price (uptrend) or high price (downtrend) with the moving average lines, it identifies where the price (low/high) has reached the the moving average line. Fetching the value to help for opening position, set stop loss and take profit.
Since the stop loss is based and set from the previous moving average touch price value, when position is about to be open and setting the stop loss value, there is a verification to check both current and previous moving average touch price to recalculate the stop loss value.
The turnover trend checks for a possible market turnover event, setting up a new profit target, this setting when enabled is to be helpful when a turnover occurs against the position to exit position with some profit based on highest high price if long or lowest low price if short.
The turnover signal is similar to turnover trend. The difference is that when this setting is enabled and it triggers, it simply exit the current position and opens up a reverse position, long goes short and short goes long. And there is an complement optional that checks current price exit profitable.
Entry Position
Long Position:
Price is higher than the mean moving averages. Meaning possible uptrend.
The lines of the middle range from the moving averages are in increasing order. Meaning possible uptrend.
The current high pierced up previous high.
Fetch the previous value of the moving average touch price. Meaning the low price has touched one of the moving average lines, which that value is conditioning to open position.
Short Position:
Price is lower than the mean moving averages. Meaning possible downtrend.
The lines of the middle range from the moving averages are in decreasing order. Meaning possible downtrend.
The current low pierced down previous low.
Fetch the previous value of the moving average touch price. Meaning the high price has touched one of the moving average lines, which that value is conditioning to open position.
Risk Management
Stop Loss:
The stop loss is based from the previous moving average touch price value, high price for short and low price for long or occurs an verification to check for both current and previous moving average touch price value and a recalculation is done to set the stop loss.
Take Profit:
According to the author, the profit target should be at least 1:1.6 the risk, so to have the strategy mathematically positive.
The profit target is configured input, can be increased or decreased.
It calculates the take profit based on the price of the stop loss with the profit target input.
Turnover Trend
Long Position:
The moving averages initial range lines signals a possible market turnover. Meaning long might be going short.
Fetches the highest high hit since the opening of the position, setting that value to the new profit target.
Short Position:
The moving averages initial range lines signals a possible market turnover. Meaning short might be going long.
Fetches the lowest low hit since the opening of the position, setting that value to the new profit target.
Wyszukaj w skryptach "stop loss"
GKD-M Baseline Optimizer [Loxx]Giga Kaleidoscope GKD-M Baseline Optimizer is a Metamorphosis module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
The Baseline Optimizer enables traders to backtest over 60 moving averages using variable period inputs. It then exports the baseline with the highest cumulative win rate per candle to any baseline-enabled GKD backtest. To perform the backtesting, the trader selects an initial period input (default is 60) and a skip value that increments the initial period input up to seven times. For instance, if a skip value of 5 is chosen, the Baseline Optimizer will run the backtest for the selected moving average on periods such as 60, 65, 70, 75, and so on, up to 90. If the user selects an initial period input of 45 and a skip value of 2, the Baseline Optimizer will conduct backtests for the chosen moving average on periods like 45, 47, 49, 51, and so forth, up to 57.
The Baseline Optimizer provides a table displaying the output of the backtests for a specified date range. The table output represents the cumulative win rate for the given date range.
On the Metamorphosis side of the Baseline Optimizer, a cumulative backtest is calculated for each candle within the date range. This means that each candle may exhibit a different distribution of period inputs with the highest win rate for a particular moving average. The Baseline Optimizer identifies the period input combination with the highest win rates for long and short positions and creates a win-rate adaptive long and short moving average chart. The moving average used for shorts differs from the moving average used for longs, and the moving average for each candle may vary from any other candle. This customized baseline can then be exported to all baseline-enabled GKD backtests.
The backtest employed in the Baseline Optimizer is a Solo Confirmation Simple, allowing only one take profit and one stop loss to be set.
Lastly, the Baseline Optimizer incorporates Goldie Locks Zone filtering, which can be utilized for signal generation in advanced GKD backtests.
█ Moving Averages included in the Baseline Optimizer
Adaptive Moving Average - AMA
ADXvma - Average Directional Volatility Moving Average
Ahrens Moving Average
Alexander Moving Average - ALXMA
Deviation Scaled Moving Average - DSMA
Donchian
Double Exponential Moving Average - DEMA
Double Smoothed Exponential Moving Average - DSEMA
Double Smoothed FEMA - DSFEMA
Double Smoothed Range Weighted EMA - DSRWEMA
Double Smoothed Wilders EMA - DSWEMA
Double Weighted Moving Average - DWMA
Exponential Moving Average - EMA
Fast Exponential Moving Average - FEMA
Fractal Adaptive Moving Average - FRAMA
Generalized DEMA - GDEMA
Generalized Double DEMA - GDDEMA
Hull Moving Average (Type 1) - HMA1
Hull Moving Average (Type 2) - HMA2
Hull Moving Average (Type 3) - HMA3
Hull Moving Average (Type 4) - HMA4
IE /2 - Early T3 by Tim Tilson
Integral of Linear Regression Slope - ILRS
Kaufman Adaptive Moving Average - KAMA
Leader Exponential Moving Average
Linear Regression Value - LSMA ( Least Squares Moving Average )
Linear Weighted Moving Average - LWMA
McGinley Dynamic
McNicholl EMA
Non-Lag Moving Average
Ocean NMA Moving Average - ONMAMA
One More Moving Average - OMA
Parabolic Weighted Moving Average
Probability Density Function Moving Average - PDFMA
Quadratic Regression Moving Average - QRMA
Regularized EMA - REMA
Range Weighted EMA - RWEMA
Recursive Moving Trendline
Simple Decycler - SDEC
Simple Jurik Moving Average - SJMA
Simple Moving Average - SMA
Sine Weighted Moving Average
Smoothed LWMA - SLWMA
Smoothed Moving Average - SMMA
Smoother
Super Smoother
T3
Three-pole Ehlers Butterworth
Three-pole Ehlers Smoother
Triangular Moving Average - TMA
Triple Exponential Moving Average - TEMA
Two-pole Ehlers Butterworth
Two-pole Ehlers smoother
Variable Index Dynamic Average - VIDYA
Variable Moving Average - VMA
Volume Weighted EMA - VEMA
Volume Weighted Moving Average - VWMA
Zero-Lag DEMA - Zero Lag Exponential Moving Average
Zero-Lag Moving Average
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
Adaptive Moving Average - AMA
The Adaptive Moving Average (AMA) is a moving average that changes its sensitivity to price moves depending on the calculated volatility. It becomes more sensitive during periods when the price is moving smoothly in a certain direction and becomes less sensitive when the price is volatile.
ADXvma - Average Directional Volatility Moving Average
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.
The ADXvma has the SMA in Chande's CMO replaced with an EMA , it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
A side effect is, those additional layers slow down the ADXvma when you compare it to Chande's Variable Index Dynamic Average VIDYA .
The ADXVMA provides support during uptrends and resistance during downtrends and will stay flat for longer, but will create some of the most accurate market signals when it decides to move.
Ahrens Moving Average
Richard D. Ahrens's Moving Average promises "Smoother Data" that isn't influenced by the occasional price spike. It works by using the Open and the Close in his formula so that the only time the Ahrens Moving Average will change is when the candlestick is either making new highs or new lows.
Alexander Moving Average - ALXMA
This Moving Average uses an elaborate smoothing formula and utilizes a 7 period Moving Average. It corresponds to fitting a second-order polynomial to seven consecutive observations. This moving average is rarely used in trading but is interesting as this Moving Average has been applied to diffusion indexes that tend to be very volatile.
Deviation Scaled Moving Average - DSMA
The Deviation-Scaled Moving Average is a data smoothing technique that acts like an exponential moving average with a dynamic smoothing coefficient. The smoothing coefficient is automatically updated based on the magnitude of price changes. In the Deviation-Scaled Moving Average, the standard deviation from the mean is chosen to be the measure of this magnitude. The resulting indicator provides substantial smoothing of the data even when price changes are small while quickly adapting to these changes.
Donchian
Donchian Channels are three lines generated by moving average calculations that comprise an indicator formed by upper and lower bands around a midrange or median band. The upper band marks the highest price of a security over N periods while the lower band marks the lowest price of a security over N periods.
Double Exponential Moving Average - DEMA
The Double Exponential Moving Average ( DEMA ) combines a smoothed EMA and a single EMA to provide a low-lag indicator. It's primary purpose is to reduce the amount of "lagging entry" opportunities, and like all Moving Averages, the DEMA confirms uptrends whenever price crosses on top of it and closes above it, and confirms downtrends when the price crosses under it and closes below it - but with significantly less lag.
Double Smoothed Exponential Moving Average - DSEMA
The Double Smoothed Exponential Moving Average is a lot less laggy compared to a traditional EMA . It's also considered a leading indicator compared to the EMA , and is best utilized whenever smoothness and speed of reaction to market changes are required.
Double Smoothed FEMA - DSFEMA
Same as the Double Exponential Moving Average (DEMA), but uses a faster version of EMA for its calculation.
Double Smoothed Range Weighted EMA - DSRWEMA
Range weighted exponential moving average (EMA) is, unlike the "regular" range weighted average calculated in a different way. Even though the basis - the range weighting - is the same, the way how it is calculated is completely different. By definition this type of EMA is calculated as a ratio of EMA of price*weight / EMA of weight. And the results are very different and the two should be considered as completely different types of averages. The higher than EMA to price changes responsiveness when the ranges increase remains in this EMA too and in those cases this EMA is clearly leading the "regular" EMA. This version includes double smoothing.
Double Smoothed Wilders EMA - DSWEMA
Welles Wilder was frequently using one "special" case of EMA (Exponential Moving Average) that is due to that fact (that he used it) sometimes called Wilder's EMA. This version is adding double smoothing to Wilder's EMA in order to make it "faster" (it is more responsive to market prices than the original) and is still keeping very smooth values.
Double Weighted Moving Average - DWMA
Double weighted moving average is an LWMA (Linear Weighted Moving Average). Instead of doing one cycle for calculating the LWMA, the indicator is made to cycle the loop 2 times. That produces a smoother values than the original LWMA
Exponential Moving Average - EMA
The EMA places more significance on recent data points and moves closer to price than the SMA ( Simple Moving Average ). It reacts faster to volatility due to its emphasis on recent data and is known for its ability to give greater weight to recent and more relevant data. The EMA is therefore seen as an enhancement over the SMA .
Fast Exponential Moving Average - FEMA
An Exponential Moving Average with a short look-back period.
Fractal Adaptive Moving Average - FRAMA
The Fractal Adaptive Moving Average by John Ehlers is an intelligent adaptive Moving Average which takes the importance of price changes into account and follows price closely enough to display significant moves whilst remaining flat if price ranges. The FRAMA does this by dynamically adjusting the look-back period based on the market's fractal geometry.
Generalized DEMA - GDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages.". Instead of using fixed multiplication factor in the final DEMA formula, the generalized version allows you to change it. By varying the "volume factor" form 0 to 1 you apply different multiplications and thus producing DEMA with different "speed" - the higher the volume factor is the "faster" the DEMA will be (but also the slope of it will be less smooth). The volume factor is limited in the calculation to 1 since any volume factor that is larger than 1 is increasing the overshooting to the extent that some volume factors usage makes the indicator unusable.
Generalized Double DEMA - GDDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages''. This is an extension of the Generalized DEMA using Tim Tillsons (the inventor of T3) idea, and is using GDEMA of GDEMA for calculation (which is the "middle step" of T3 calculation). Since there are no versions showing that middle step, this version covers that too. The result is smoother than Generalized DEMA, but is less smooth than T3 - one has to do some experimenting in order to find the optimal way to use it, but in any case, since it is "faster" than the T3 (Tim Tillson T3) and still smooth, it looks like a good compromise between speed and smoothness.
Hull Moving Average (Type 1) - HMA1
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMA for smoothing.
Hull Moving Average (Type 2) - HMA2
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses EMA for smoothing.
Hull Moving Average (Type 3) - HMA3
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses LWMA for smoothing.
Hull Moving Average (Type 4) - HMA4
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMMA for smoothing.
IE /2 - Early T3 by Tim Tilson and T3 new
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
Integral of Linear Regression Slope - ILRS
A Moving Average where the slope of a linear regression line is simply integrated as it is fitted in a moving window of length N (natural numbers in maths) across the data. The derivative of ILRS is the linear regression slope. ILRS is not the same as a SMA ( Simple Moving Average ) of length N, which is actually the midpoint of the linear regression line as it moves across the data.
Kaufman Adaptive Moving Average - KAMA
Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low.
Leader Exponential Moving Average
The Leader EMA was created by Giorgos E. Siligardos who created a Moving Average which was able to eliminate lag altogether whilst maintaining some smoothness. It was first described during his research paper "MACD Leader" where he applied this to the MACD to improve its signals and remove its lagging issue. This filter uses his leading MACD's "modified EMA" and can be used as a zero lag filter.
Linear Regression Value - LSMA ( Least Squares Moving Average )
LSMA as a Moving Average is based on plotting the end point of the linear regression line. It compares the current value to the prior value and a determination is made of a possible trend, eg. the linear regression line is pointing up or down.
Linear Weighted Moving Average - LWMA
LWMA reacts to price quicker than the SMA and EMA . Although it's similar to the Simple Moving Average , the difference is that a weight coefficient is multiplied to the price which means the most recent price has the highest weighting, and each prior price has progressively less weight. The weights drop in a linear fashion.
McGinley Dynamic
John McGinley created this Moving Average to track prices better than traditional Moving Averages. It does this by incorporating an automatic adjustment factor into its formula, which speeds (or slows) the indicator in trending, or ranging, markets.
McNicholl EMA
Dennis McNicholl developed this Moving Average to use as his center line for his "Better Bollinger Bands" indicator and was successful because it responded better to volatility changes over the standard SMA and managed to avoid common whipsaws.
Non-lag moving average
The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals.
Ocean NMA Moving Average - ONMAMA
Created by Jim Sloman, the NMA is a moving average that automatically adjusts to volatility without being programmed to do so. For more info, read his guide "Ocean Theory, an Introduction"
One More Moving Average (OMA)
The One More Moving Average (OMA) is a technical indicator that calculates a series of Jurik-style moving averages in order to reduce noise and provide smoother price data. It uses six exponential moving averages to generate the final value, with the length of the moving averages determined by an adaptive algorithm that adjusts to the current market conditions. The algorithm calculates the average period by comparing the signal to noise ratio and using this value to determine the length of the moving averages. The resulting values are used to generate the final value of the OMA, which can be used to identify trends and potential changes in trend direction.
Parabolic Weighted Moving Average
The Parabolic Weighted Moving Average is a variation of the Linear Weighted Moving Average . The Linear Weighted Moving Average calculates the average by assigning different weights to each element in its calculation. The Parabolic Weighted Moving Average is a variation that allows weights to be changed to form a parabolic curve. It is done simply by using the Power parameter of this indicator.
Probability Density Function Moving Average - PDFMA
Probability density function based MA is a sort of weighted moving average that uses probability density function to calculate the weights. By its nature it is similar to a lot of digital filters.
Quadratic Regression Moving Average - QRMA
A quadratic regression is the process of finding the equation of the parabola that best fits a set of data. This moving average is an obscure concept that was posted to Forex forums in around 2008.
Regularized EMA - REMA
The regularized exponential moving average (REMA) by Chris Satchwell is a variation on the EMA (see Exponential Moving Average) designed to be smoother but not introduce too much extra lag.
Range Weighted EMA - RWEMA
This indicator is a variation of the range weighted EMA. The variation comes from a possible need to make that indicator a bit less "noisy" when it comes to slope changes. The method used for calculating this variation is the method described by Lee Leibfarth in his article "Trading With An Adaptive Price Zone".
Recursive Moving Trendline
Dennis Meyers's Recursive Moving Trendline uses a recursive (repeated application of a rule) polynomial fit, a technique that uses a small number of past values estimations of price and today's price to predict tomorrow's price.
Simple Decycler - SDEC
The Ehlers Simple Decycler study is a virtually zero-lag technical indicator proposed by John F. Ehlers. The original idea behind this study (and several others created by John F. Ehlers) is that market data can be considered a continuum of cycle periods with different cycle amplitudes. Thus, trending periods can be considered segments of longer cycles, or, in other words, low-frequency segments. Applying the right filter might help identify these segments.
Simple Loxx Moving Average - SLMA
A three stage moving average combining an adaptive EMA, a Kalman Filter, and a Kauffman adaptive filter.
Simple Moving Average - SMA
The SMA calculates the average of a range of prices by adding recent prices and then dividing that figure by the number of time periods in the calculation average. It is the most basic Moving Average which is seen as a reliable tool for starting off with Moving Average studies. As reliable as it may be, the basic moving average will work better when it's enhanced into an EMA .
Sine Weighted Moving Average
The Sine Weighted Moving Average assigns the most weight at the middle of the data set. It does this by weighting from the first half of a Sine Wave Cycle and the most weighting is given to the data in the middle of that data set. The Sine WMA closely resembles the TMA (Triangular Moving Average).
Smoothed LWMA - SLWMA
A smoothed version of the LWMA
Smoothed Moving Average - SMMA
The Smoothed Moving Average is similar to the Simple Moving Average ( SMA ), but aims to reduce noise rather than reduce lag. SMMA takes all prices into account and uses a long lookback period. Due to this, it's seen as an accurate yet laggy Moving Average.
Smoother
The Smoother filter is a faster-reacting smoothing technique which generates considerably less lag than the SMMA ( Smoothed Moving Average ). It gives earlier signals but can also create false signals due to its earlier reactions. This filter is sometimes wrongly mistaken for the superior Jurik Smoothing algorithm.
Super Smoother
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a Two pole Butterworth filter combined with a 2-bar SMA ( Simple Moving Average ) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Three-pole Ehlers Butterworth
The 3 pole Ehlers Butterworth (as well as the Two pole Butterworth) are both superior alternatives to the EMA and SMA . They aim at producing less lag whilst maintaining accuracy. The 2 pole filter will give you a better approximation for price, whereas the 3 pole filter has superior smoothing.
Three-pole Ehlers smoother
The 3 pole Ehlers smoother works almost as close to price as the above mentioned 3 Pole Ehlers Butterworth. It acts as a strong baseline for signals but removes some noise. Side by side, it hardly differs from the Three Pole Ehlers Butterworth but when examined closely, it has better overshoot reduction compared to the 3 pole Ehlers Butterworth.
Triangular Moving Average - TMA
The TMA is similar to the EMA but uses a different weighting scheme. Exponential and weighted Moving Averages will assign weight to the most recent price data. Simple moving averages will assign the weight equally across all the price data. With a TMA (Triangular Moving Average), it is double smoother (averaged twice) so the majority of the weight is assigned to the middle portion of the data.
Triple Exponential Moving Average - TEMA
The TEMA uses multiple EMA calculations as well as subtracting lag to create a tool which can be used for scalping pullbacks. As it follows price closely, its signals are considered very noisy and should only be used in extremely fast-paced trading conditions.
Two-pole Ehlers Butterworth
The 2 pole Ehlers Butterworth (as well as the three pole Butterworth mentioned above) is another filter that cuts out the noise and follows the price closely. The 2 pole is seen as a faster, leading filter over the 3 pole and follows price a bit more closely. Analysts will utilize both a 2 pole and a 3 pole Butterworth on the same chart using the same period, but having both on chart allows its crosses to be traded.
Two-pole Ehlers smoother
A smoother version of the Two pole Ehlers Butterworth. This filter is the faster version out of the 3 pole Ehlers Butterworth. It does a decent job at cutting out market noise whilst emphasizing a closer following to price over the 3 pole Ehlers .
Variable Index Dynamic Average - VIDYA
Variable Index Dynamic Average Technical Indicator ( VIDYA ) was developed by Tushar Chande. It is an original method of calculating the Exponential Moving Average ( EMA ) with the dynamically changing period of averaging.
Variable Moving Average - VMA
The Variable Moving Average (VMA) is a study that uses an Exponential Moving Average being able to automatically adjust its smoothing factor according to the market volatility.
Volume Weighted EMA - VEMA
An EMA that uses a volume and price weighted calculation instead of the standard price input.
Volume Weighted Moving Average - VWMA
A Volume Weighted Moving Average is a moving average where more weight is given to bars with heavy volume than with light volume. Thus the value of the moving average will be closer to where most trading actually happened than it otherwise would be without being volume weighted.
Zero-Lag DEMA - Zero Lag Double Exponential Moving Average
John Ehlers's Zero Lag DEMA's aim is to eliminate the inherent lag associated with all trend following indicators which average a price over time. Because this is a Double Exponential Moving Average with Zero Lag, it has a tendency to overshoot and create a lot of false signals for swing trading. It can however be used for quick scalping or as a secondary indicator for confluence.
Zero-Lag Moving Average
The Zero Lag Moving Average is described by its creator, John Ehlers , as a Moving Average with absolutely no delay. And it's for this reason that this filter will cause a lot of abrupt signals which will not be ideal for medium to long-term traders. This filter is designed to follow price as close as possible whilst de-lagging data instead of basing it on regular data. The way this is done is by attempting to remove the cumulative effect of the Moving Average.
Zero-Lag TEMA - Zero Lag Triple Exponential Moving Average
Just like the Zero Lag DEMA , this filter will give you the fastest signals out of all the Zero Lag Moving Averages. This is useful for scalping but dangerous for medium to long-term traders, especially during market Volatility and news events. Having no lag, this filter also has no smoothing in its signals and can cause some very bizarre behavior when applied to certain indicators.
█ Volatility Goldie Locks Zone
The Goldie Locks Zone volatility filter is the standard first-pass filter used in all advanced GKD backtests (Complex, Super Complex, and Full GKd). This filter requires the price to fall within a range determined by multiples of volatility. The Goldie Locks Zone is separate from the core Baseline and utilizes its own moving average with Loxx's Exotic Source Types you can read about below.
On the chart, you will find green and red dots positioned at the top, indicating whether a candle qualifies for a long or short trade respectively. Additionally, green and red triangles are located at the bottom of the chart, signifying whether the trigger has crossed up or down and qualifies within the Goldie Locks zone. The Goldie Locks zone is represented by a white color on the mean line, indicating low volatility levels that are not suitable for trading.
█ Volatility Types Included in the Baseline Optimizer
The GKD system utilizes volatility-based take profits and stop losses. Each take profit and stop loss is calculated as a multiple of volatility. Users can also adjust the multiplier values in the settings.
This module includes 17 types of volatility:
Close-to-Close
Parkinson
Garman-Klass
Rogers-Satchell
Yang-Zhang
Garman-Klass-Yang-Zhang
Exponential Weighted Moving Average
Standard Deviation of Log Returns
Pseudo GARCH(2,2)
Average True Range
True Range Double
Standard Deviation
Adaptive Deviation
Median Absolute Deviation
Efficiency-Ratio Adaptive ATR
Mean Absolute Deviation
Static Percent
Various volatility estimators and indicators that investors and traders can use to measure the dispersion or volatility of a financial instrument's price. Each estimator has its strengths and weaknesses, and the choice of estimator should depend on the specific needs and circumstances of the user.
Close-to-Close
Close-to-Close volatility is a classic and widely used volatility measure, sometimes referred to as historical volatility.
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a larger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility is calculated using only a stock's closing prices. It is the simplest volatility estimator. However, in many cases, it is not precise enough. Stock prices could jump significantly during a trading session and return to the opening value at the end. That means that a considerable amount of price information is not taken into account by close-to-close volatility.
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. This is useful as close-to-close prices could show little difference while large price movements could have occurred during the day. Thus, Parkinson's volatility is considered more precise and requires less data for calculation than close-to-close volatility.
One drawback of this estimator is that it doesn't take into account price movements after the market closes. Hence, it systematically undervalues volatility. This drawback is addressed in the Garman-Klass volatility estimator.
Garman-Klass
Garman-Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing prices. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change follows a continuous diffusion process (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremes.
Researchers Rogers and Satchell have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term (mean return not equal to zero). As a result, it provides better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. This leads to an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
Yang-Zhang volatility can be thought of as a combination of the overnight (close-to-open volatility) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility. It is considered to be 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman-Klass-Yang-Zhang (GKYZ) volatility estimator incorporates the returns of open, high, low, and closing prices in its calculation.
GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e., it assumes that the underlying asset follows a Geometric Brownian Motion (GBM) process with zero drift. Therefore, the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, with the main applications being technical analysis and volatility modeling.
The moving average is designed such that older observations are given lower weights. The weights decrease exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility. It's the standard deviation of ln(close/close(1)).
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by ?.
?avg(var;M) + (1 ? ?) avg(var;N) = 2?var/(M+1-(M-1)L) + 2(1-?)var/(M+1-(M-1)L)
Solving for ? can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg(var; N) against avg(var; M) - avg(var; N) and using the resulting beta estimate as ?.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Standard Deviation
Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation.
Adaptive Deviation
By definition, the Standard Deviation (STD, also represented by the Greek letter sigma ? or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis, we usually use it to measure the level of current volatility.
Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA, we can call it EMA deviation. Additionally, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting).
The difference when compared to the standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions.
Median Absolute Deviation
The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant.
Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution.
For this indicator, a manual recreation of the quantile function in Pine Script is used. This is so users have a full inside view into how this is calculated.
Efficiency-Ratio Adaptive ATR
Average True Range (ATR) is a widely used indicator for many occasions in technical analysis. It is calculated as the RMA of the true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range.
Mean Absolute Deviation
The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation.
This definition of the mean absolute deviation sounds similar to the standard deviation (SD). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life.
█ Loxx's Expanded Source Types Included in Baseline Optimizer
This indicator allows you to select from 33 source types. They are as follows:
Close
Open
High
Low
Median
Typical
Weighted
Average
Average Median Body
Trend Biased
Trend Biased (Extreme)
HA Close
HA Open
HA High
HA Low
HA Median
HA Typical
HA Weighted
HA Average
HA Average Median Body
HA Trend Biased
HA Trend Biased (Extreme)
HAB Close
HAB Open
HAB High
HAB Low
HAB Median
HAB Typical
HAB Weighted
HAB Average
HAB Average Median Body
HAB Trend Biased
HAB Trend Biased (Extreme)
What are Heiken Ashi "better" candles?
Heiken Ashi "better" candles are a modified version of the standard Heiken Ashi candles, which are a popular charting technique used in technical analysis. Heiken Ashi candles help traders identify trends and potential reversal points by smoothing out price data and reducing market noise. The "better formula" was proposed by Sebastian Schmidt in an article published by BNP Paribas in Warrants & Zertifikate, a German magazine, in August 2004. The aim of this formula is to further improve the smoothing of the Heiken Ashi chart and enhance its effectiveness in identifying trends and reversals.
Standard Heiken Ashi candles are calculated using the following formulas:
Heiken Ashi Close = (Open + High + Low + Close) / 4
Heiken Ashi Open = (Previous Heiken Ashi Open + Previous Heiken Ashi Close) / 2
Heiken Ashi High = Max (High, Heiken Ashi Open, Heiken Ashi Close)
Heiken Ashi Low = Min (Low, Heiken Ashi Open, Heiken Ashi Close)
The "better formula" modifies the standard Heiken Ashi calculation by incorporating additional smoothing, which can help reduce noise and make it easier to identify trends and reversals. The modified formulas for Heiken Ashi "better" candles are as follows:
Better Heiken Ashi Close = (Open + High + Low + Close) / 4
Better Heiken Ashi Open = (Previous Better Heiken Ashi Open + Previous Better Heiken Ashi Close) / 2
Better Heiken Ashi High = Max (High, Better Heiken Ashi Open, Better Heiken Ashi Close)
Better Heiken Ashi Low = Min (Low, Better Heiken Ashi Open, Better Heiken Ashi Close)
Smoothing Factor = 2 / (N + 1), where N is the chosen period for smoothing
Smoothed Better Heiken Ashi Open = (Better Heiken Ashi Open * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Open * (1 - Smoothing Factor))
Smoothed Better Heiken Ashi Close = (Better Heiken Ashi Close * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Close * (1 - Smoothing Factor))
The smoothed Better Heiken Ashi Open and Close values are then used to calculate the smoothed Better Heiken Ashi High and Low values, resulting in "better" candles that provide a clearer representation of the market trend and potential reversal points.
Heiken Ashi "better" candles, as mentioned previously, provide a clearer representation of market trends and potential reversal points by reducing noise and smoothing out price data. When using these candles in conjunction with other technical analysis tools and indicators, traders can gain valuable insights into market behavior and make more informed decisions.
To effectively use Heiken Ashi "better" candles in your trading strategy, consider the following tips:
-Trend Identification: Heiken Ashi "better" candles can help you identify the prevailing trend in the market. When the majority of the candles are green (or another color, depending on your chart settings) and there are no or few lower wicks, it may indicate a strong uptrend. Conversely, when the majority of the candles are red (or another color) and there are no or few upper wicks, it may signal a strong downtrend.
-Trend Reversals: Look for potential trend reversals when a change in the color of the candles occurs, especially when accompanied by longer wicks. For example, if a green candle with a long lower wick is followed by a red candle, it could indicate a bearish reversal. Similarly, a red candle with a long upper wick followed by a green candle may suggest a bullish reversal.
-Support and Resistance: You can use Heiken Ashi "better" candles to identify potential support and resistance levels. When the candles are consistently moving in one direction and then suddenly change color with longer wicks, it could indicate the presence of a support or resistance level.
-Stop-Loss and Take-Profit: Using Heiken Ashi "better" candles can help you manage risk by determining optimal stop-loss and take-profit levels. For instance, you can place your stop-loss below the low of the most recent green candle in an uptrend or above the high of the most recent red candle in a downtrend.
-Confirming Signals: Heiken Ashi "better" candles should be used in conjunction with other technical indicators, such as moving averages, oscillators, or chart patterns, to confirm signals and improve the accuracy of your analysis.
In this implementation, you have the choice of AMA, KAMA, or T3 smoothing. These are as follows:
Kaufman Adaptive Moving Average (KAMA)
The Kaufman Adaptive Moving Average (KAMA) is a type of adaptive moving average used in technical analysis to smooth out price fluctuations and identify trends. The KAMA adjusts its smoothing factor based on the market's volatility, making it more responsive in volatile markets and smoother in calm markets. The KAMA is calculated using three different efficiency ratios that determine the appropriate smoothing factor for the current market conditions. These ratios are based on the noise level of the market, the speed at which the market is moving, and the length of the moving average. The KAMA is a popular choice among traders who prefer to use adaptive indicators to identify trends and potential reversals.
Adaptive Moving Average
The Adaptive Moving Average (AMA) is a type of moving average that adjusts its sensitivity to price movements based on market conditions. It uses a ratio between the current price and the highest and lowest prices over a certain lookback period to determine its level of smoothing. The AMA can help reduce lag and increase responsiveness to changes in trend direction, making it useful for traders who want to follow trends while avoiding false signals. The AMA is calculated by multiplying a smoothing constant with the difference between the current price and the previous AMA value, then adding the result to the previous AMA value.
T3
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators*
*(not part of the NNFX algorithm)
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
What is an Metamorphosis indicator?
The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy.
The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Full GKD Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Kase Peak Oscillator
Confirmation 2: uf2018
Continuation: Vortex
Exit: Rex Oscillator
Metamorphosis: Baseline Optimizer as shown on the chart above
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
█ Giga Kaleidoscope Modularized Trading System Signals
Standard Entry
1. GKD-C Confirmation gives signal
2. Baseline agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
1-Candle Standard Entry
1a. GKD-C Confirmation gives signal
2a. Baseline agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Baseline Entry
1. GKD-B Basline gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
1-Candle Baseline Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Volatility/Volume Entry
1. GKD-V Volatility/Volume gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Volatility/Volume Entry
1a. GKD-V Volatility/Volume gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior
Next Candle
1b. Price retraced
2b. Volatility/Volume agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Baseline agrees
Confirmation 2 Entry
1. GKD-C Confirmation 2 gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Volatility/Volume agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Confirmation 2 Entry
1a. GKD-C Confirmation 2 gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior
Next Candle
1b. Price retraced
2b. Confirmation 2 agrees
3b. Confirmation 1 agrees
4b. Volatility/Volume agrees
5b. Baseline agrees
PullBack Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price is beyond 1.0x Volatility of Baseline
Next Candle
1b. Price inside Goldie Locks Zone Minimum
2b. Price inside Goldie Locks Zone Maximum
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Continuation Entry
1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously
2. Baseline hasn't crossed since entry signal trigger
4. Confirmation 1 agrees
5. Baseline agrees
6. Confirmation 2 agrees
█ Connecting to Backtests
All GKD indicators are chained indicators meaning you export the value of the indicators to specialized backtest to creat your GKD trading system. Each indicator contains a proprietary signal generation algo that will only work with GKD backtests. You can find these backtests using the links below.
GKD-BT Giga Confirmation Stack Backtest:
GKD-BT Giga Stacks Backtest:
GKD-BT Full Giga Kaleidoscope Backtest:
GKD-BT Solo Confirmation Super Complex Backtest:
GKD-BT Solo Confirmation Complex Backtest:
GKD-BT Solo Confirmation Simple Backtest:
NoanFam IndicatorNoan Indicator: A Simple Manual for Beginners
Welcome to the Noan Indicator manual!
This guide will help you understand how to use the Noan Indicator for your trading needs, even if you have little to no knowledge of trading.
The Noan Indicator is a versatile tool that can be applied to different trading strategies, such as 123 patterns, trend breaks, or sudden large price movements.
How to Start the Indicator:
1. Determine 2% risk:
The first step is to determine the risk you're willing to take for a particular trade.
We recommend a 2% risk, meaning you should not risk more than 2% of your account balance on any single trade.
a. Enter Portfolio Size: Enter the total value of your trading portfolio. This value will be used to calculate the trade size based on the percentage risk you're willing to take.
b. Enter Leverage Multiplier: Enter the leverage multiplier you are using for your trades. This value will be used to adjust the trade size accordingly.
c. Split amount to trade (Entry-DCA): Select the desired percentage split for your initial trade entry and dollar-cost averaging (DCA) trade. You can choose between 60/40, 50/50, or 100% (no DCA).
2. Identify a trade opportunity:
Analyze the market, using technical and/or fundamental analysis, to identify potential trade opportunities. Look for patterns, trends, support and resistance levels, and other indicators that signal the right time to enter a trade. Remember that the Noan Indicator is designed to assist you in managing risk, and it is not a standalone trading strategy. Always use your own research and judgement when making trading decisions.
After conducting your research and finding a good point to enter, input the trade type (long or short) into the indicator.
3. Set entry price:
The entry price should be based on your analysis and represents the price at which you would like to enter the market.
It is essential to set a realistic entry price, taking into consideration the current market conditions and price action.
After conducting your own research and identifying a good entry point for a long or short trade, input the Entry Price into the Noan Indicator.
4. Preferences:
The Noan indicator is set default with a Dollar Cost Averaging (DCA) area.
You can choose to disable this feature if desired.
Also an option to choose whether you want to see the values ($) or percentages (%) for the different levels in the indicator.
5. Select a predefined Trail Stop Loss:
If a trailing stop loss option is selected in the settings, a line will be displayed on the chart, showing the level where the stop loss will be moved based on the chosen option.
Protect your investment and help manage risk during the trade.
It allows you to limit your losses while allowing your profits to run.
Move Stop Loss to Average Entry: The stop loss moves to your average entry price (considering DCA) once the market reaches a specific level.
Move Stop Loss to Entry: The stop loss moves to your initial entry price.
Move Stop Loss to TP1 after DCA: The stop loss moves to the first Take Profit level after executing the DCA.
Move Stop Loss to TP1, TP2, TP3, or LTPR: The stop loss moves to the specified Take Profit level or Last Trailing Profit Range.
6. Set alerts:
Set up alerts for when the indicator reaches specific levels or when other conditions are met.
This will help you stay informed about potential trading opportunities.
To set up alerts using the Noan Indicator v2.7.0:
a. Right-click on the chart and select "Add Alert" or click the "Alerts" tab in the left sidebar and click the "+" button.
b. In the "Condition" dropdown menu, select the "Noan Indicator v2.7.0" script.
c. Choose the alert type by selecting a condition from the available options (e.g., crossing, greater than, less than, etc.).
d. Specify the alert settings, such as the alert name, message, and frequency.
e. Click "Create" to create the alert.
What Makes This Indicator Unique?
The Noan Indicator is designed to suit various trading strategies and can help confirm a setup after thorough research or upon reaching a Point of Interest (POI). By inputting a pre-examined entry price, the indicator will display different potential levels for Take Profits (TPs), Dollar-Cost Averaging (DCA), and Stop Loss (SL) areas. These levels are based on fixed percentages derived from data collected from thousands of trades.
If the different levels correspond well with past price levels, this can provide an extra point of confirmation for your trading decision. The TPs, DCA, and SL areas at these levels are structured according to the Noan Theory, further enhancing the effectiveness of the indicator.
In summary, the Noan Indicator is a versatile and powerful tool that can help traders of all levels make more informed decisions, regardless of their trading strategy. By following this simple manual, you can start using the Noan Indicator to improve your trading performance.
*Backtesting System ⚉ ＯＶＥＲＶＩＥＷ ⚉
One of the best Systems for Backtesting your Strategies.
Incredibly flexible, simple, fast and feature-rich system — will solve most of your queries without much effort.
Many systems for setting StopLoss, TakeProfit, Risk Management and advanced Filters.
All you need to do is plug in your indicator and start Backtesting .
I intentionally left the option to use my System on Full Power before you load your indicator into it.
The system uses the built-in simple and popular moving average crossover signal for this purpose. (EMA 50 & 200).
Also Highly Recommend that you Fully use ALL of the features of this system so that you understand how they work before you ask questions.
Also tried to leave TIPS for each feature everywhere, read Tips, activate them and see how they work.
But before you use this system, I Recommend you to read the following description in Full.
—————— How to connect your indicator in 2 steps:
Adapt your indicator by adding only 2 lines of code and then connect it to this Backtesting System.
Step 1 — Create your connector, For doing so:
• 1 — Find or create in your indicator where are the conditions printing the Long-Buy and Short-Sell signals.
• 2 — Create an additional plot as below
I'm giving an example with a Two moving averages cross.
Please replicate the same methodology for your indicator wether it's a MACD, RSI , Pivots, or whatever indicator with Clear Buy and Sell conditions.
//@version=5
indicator('Moving Average Cross', overlay = true)
MA200 = ta.𝚎𝚖𝚊(close, 200)
MA50 = ta.𝚎𝚖𝚊(close, 50)
// Generate Buy and Sell conditions
buy = ta.crossover (MA200, MA50)
sell = ta.crossunder (MA200, MA50)
plot(MA200, color=color.green)
plot(MA50 , color=color.red )
bgcolor(color = buy ? color.green : sell ? color.red : na, title='SIGNALS')
// ———————————————— SIGNAL FOR SYSTEM ————————————————
Signal = buy ? +1 : sell ? -1 : 0
plot(Signal, title='🔌Connector🔌', display = display.none)
// —————— 🔥 The Backtesting System expects the value to be exactly +1 for the 𝚋𝚞𝚕𝚕𝚒𝚜𝚑 signal, and -1 for the 𝚋𝚎𝚊𝚛𝚒𝚜𝚑 signal
Basically, I identified my Buy & Sell conditions in the code and added this at the bottom of my indicator code
Now you can connect your indicator to the Backtesting System using the Step 2
Step 2 — Connect the connector
• 1 — Add your updated indicator to a TradingView chart and Add the Backtesting System as well to the SAME chart
• 2 — Open the Backtesting System settings and in the External Source field select your 🔌Connector🔌 (which comes from your indicator)
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𝐄𝐱𝐭𝐞𝐫𝐧𝐚𝐥 𝐒𝐨𝐮𝐫𝐜𝐞 — Select your indicator. Add your indicator by following the 2 steps described above and select it in the menu. To familiarize yourself with the system until you select your indicator, you will have an in-built strategy of crossing the two moving EMA's of 50 and 200.
Long Deals — Enable/Disable Long Deals.
Short Deals — Enable/Disable Short Deals.
Wait End Deal — Enable/Disable waiting for a trade to close at Stop Loss/Take Profit. Until the trade closes on the Stop Loss or Take Profit, no new trade will open.
Reverse Deals — To force the opening of a trade in the opposite direction.
ReEntry Deal — Automatically open the same new deal after the deal is closed.
ReOpen Deal — Reopen the trade if the same signal is received. For example, if you are already in the long and a new signal is received in the long, the trade will reopen. * Does not work if Wait End Deal is enabled.
𝐓𝐚𝐤𝐞 𝐏𝐫𝐨𝐟𝐢𝐭:
None — Disables take profit. Useful if you only want to use dynamic stoplosses such as MA, Fast-Trailing, ATR Trail.
FIXED ％ — Fixed take profit in percent.
FIXED ＄ — Fixed Take in Money.
ATR — Fixed Take based on ATR.
R:R — Fixed Take based on the size of your stop loss. For example, if your stop is 10% and R:R=1, then the Take would be 10%. R:R=3 Take would be 30%, etc.
HH / LL — Fixed Take based on the previous maximum/minimum (extremum).
𝐒𝐭𝐨𝐩 𝐋𝐨𝐬𝐬:
None — Disables Stop Loss. Useful if you want to work without a stop loss. *Be careful if Wait End Deal is enabled, the trade may not close for a long time until it reaches the Take.
FIXED ％ — Fixed Stop in percent.
FIXED ＄ — Fixed Stop in Money.
TRAILING — Dynamic Trailing Stop like on the stock exchanges.
FAST TRAIL — Dynamic Fast Trailing Stop moves immediately in profit and stays in place if the price stands still or the price moves in loss.
ATR — Fixed Stop based on the ATR.
ATR TRAIL — Dynamic Trailing Stop based on the ATR.
LO / HI — A Fixed Stop based on the last Maximum/Minimum extemum. Allows you to place a stop just behind or above the low/high candle.
MA — Dynamic Stop based on selected Moving Average. * You will have 8 types of MA (EMA, SMA, HMA, etc.) to choose from, but you can easily add dozens of other MAs, which makes this type of stop incredibly flexible.
Add ％ — If true, then with the "𝗦𝘁𝗼𝗽 ％" parameter you can add percentages to any of the current SL. Can be especially useful when using Stop - 𝗔𝗧𝗥 or 𝗠𝗔 or 𝗟𝗢/𝗛𝗜. For example with 𝗟𝗢/𝗛𝗜 to put a stop for the last High/Low and add 0.5% additional Stoploss.
Fixed R:R — If the stop loss is Dynamic (Trailing or MA) then if R:R true can also be made Dynamic * Use it carefully, the function is experimental.
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A unique method of constructing intermediate Take Profit Levels will allow you to select up to 5 intermediate Take Profit Levels and one intermediate Stop Loss.
Intermediate Take Profit Levels are perfectly calculated into 5 equal parts in the form of levels from the entry point to the final Take Profit target.
All you need to do is to choose the necessary levels for fixing and how much you want to fix at each level as a percentage. For example, TP 3 will always be exactly between the entry point and the Take Profit target. And the value of TP 3 = 50 will close 50% of the amount of the remaining size of the position.
Note: all intermediate SL/TP are closed from the remaining position amount and not from the initial position size, as TV does by default.
SL 0 Position — works in the same way as TP 1-5 but it's Stop. With this parameter you can set the position where the intermediate stop will be set.
Breakeven on TP — When activated, it allows you to put the stop loss at Breakeven after the selected TP is reached. For this function to work as it should - you need to activate an intermediate Take. For example, if TP 3 is activated and Breakeven on TP = 3, then after the price reaches this level, the Stop loss will go to Breakeven.
* This function will not work with Dynamic Stoplosses, because it simply does not make sense.
CoolDown # Bars — When activated, allows you to add a delay before a new trade is opened. A new trade after CoolDown will not be opened until # bars pass and a new signal appears.
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Powerful time filter code that allows you to filter data based on specific time zones, dates, and session days. This code is ideal for those who need to analyze data from different time zones and weed out irrelevant data.
With Time Filter, you can easily set the starting and ending time zones by which you want to filter the data.
You can also set a start and end date for your data and choose which days of the week to include in the analysis. In addition, you can specify start and end times for a specific session, allowing you to focus your analysis on specific time periods.
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Signal Filters — allows you to easily customize and optimize your trading strategies based on 10 filters.
Each filter is designed to help you weed out inaccurate signals to minimize your risks.
Let's take a look at their features:
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Risk management tools that allow you to set the maximum number of losing trades in a row, a limit on the number of trades per day or week and other filters.
Loss Streak — Set Max number of consecutive loss trades.
Win Streak — Max Winning Streak Length.
Row Loss InDay — Max of consecutive days with a loss in a row.
DrawDown ％ — Max DrawDown (in % of strategy equity).
InDay Loss ％ — Set Max Intraday Loss.
Daily Trades — Limit the number of MAX trades per day.
Weekly Trades — Limit the number of MAX trades per week.
* 🡅 I would Not Recommend using these functions without understanding how they work.
Order Size — Position Size
• NONE — Use the default position size settings in Tab "Properties".
• EQUITY — The amount of the allowed position as a percentage of the initial capital.
• Use Net Profit — On/Off the use of profit in the following trades. *Only works if the type is EQUITY.
• SIZE — The size of the allowed position in monetary terms.
• Contracts — The size of the allowed position in the contracts. 1 Сontract = Сurrent price.
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It is important to note that I have never worked with Backtesting and the functions associated with them before.
It took me about a month of slow work to build this system.
I want to say Big Thanks:
• The PineScripters🌲 group, the guys suggested how to implement some features. Especially @allanster
• Thanks to all those people who share their developments for free on TV and not only.
• I also thank myself for not giving up and finishing the project, and not trying to monetize the system by selling it. * Although I really want the money :)
I tried hard to make it as fast and convenient as possible for everyone who will use my code.
That's why I didn't use any libraries and dozens of heavy functions, and I managed to fit in 8+-functions for the whole code.
Absolutely every block of code I tried to make full-fledged modular, that it was easy to import/edit for myself (you).
I have abused the Ternary Pine operator a little (a lot) so that the code was as compact as possible.
Nevertheless, I tried very hard to keep my code very understandable even for beginners.
At last I managed to write 500 lines of code, making it one of the fastest and most feature-rich systems out there.
I hope everyone enjoys my work.
Put comments and write likes.
Ichi-Price WaveWelcome to the Ichi-Price Wave. This indicator is designed for day trading options contracts for any ticker, using a number of indicators — Ichimoku Cloud, Volume-Weighted Average Price, Stochastic Relative Strength Index, Exponential Moving Average (13/48) — and calculating how they interact with each other to provide entry and exit signals for both Calls and Puts on normal days. ****Read the Important Information section before opening any positions based on this indicator. (Also *NFA)
The general concept is that you, the trader, are a Surfer 🏄🏾 who rides the best waves in deep water until it gets dangerous.
Emoji storyline: The 🏄🏾 emoji (Call or Put, depending on the color of its Green or Red label, respectively) indicates an upcoming *potential* entry that, for a number of reasons, may be disregarded. (See: Important Information section below). And just as there are no certainties in the stock market itself, the tiered exit signals are ranked by low 🐬, medium 🦈 and high risk 🦑 tolerance. (In other words, it's relatively safe to surf with dolphins around, but there's the off chance they even strike trainers and become aggressive. It's more dangerous to swim with sharks. And on the unlikely, rare occasion you see a literal, giant, mythical, ship destroying Kraken 😬 ... you definitely need to get out of the water.
Surfing for as long as possible reaps the greatest rewards — but risk/reward are to be considered for entries and exits. Exiting every time you see a 🐬 (E1) should secure profits nearly 100% of the time, but they'll be very minimal. Whereas surfing til you reach a Kraken 🦑 (which will not even appear on most Price Wave cycles) would reap the most rewards. (NFA: I recommend considering sharks 🦈 as an exit point for the majority of positions, and perhaps only keeping a few runners open with the hopes of finding that shiny Kraken. (On the non-Emoji chart, the low, medium and high risk exits are named E1, E2 and E3, respectively. Got to the indicator's Settings > Inputs > then toggle EMOJIs ON/OFF)
Boring stuff: The entry 🏄🏾 signals are triggered by multiple conditions that must be all true. For Call entries, one of the necessary conditions is that the RSI's K must be maximum 10 (this can be changed in default). This, along with another condition where current price must be below the VWAP Lower Bound 1, serves as a great reference point showing the stock price is currently uncomfortable where it is and may likely soon snap back closer to the VWAP, perhaps even to the other side due to a pendulum effect.
Important information
Relying on those two factors for setting entry and exit points are great for normal days. (Normal, as in the ticker price bounces within a channel (e.g., ≤3% + or -) that's trending slightly bullish or bearish depending on greater market trend). But there are abnormal days where news catalysts (e.g., CPI data, CEO scandals, unexpected company data release, etc.) trigger FOMO and FUD, ultimately rendering the logic behind most indicators non applicable (e.g., RSI's "buy when oversold"). On the chart, this indicator accounts for this with two measures:
One, you should only "Surf" in the water. That is, there are two bands — Shallow and Deep Water. Any "Surf" emojis where price action is outside of the water should be ignored**. Two, there are additional EMOJIs that show you "Bearish trend" ⛈ and "Bullish trend ☀️. (Story time again: You obviously shouldn't surf in thunder and lightning. But also, surfing in the blistering sun with no clouds in the sky during a heatwave is also dangerous to your health.)
You can use these two measures to disregard the "surfers" suggesting you join them in opening a position in the suggested direction. And surfers followed by Cloud EMOJIs — 🌤️ (Put) or 🌧️ (Call) — can be used as "perfect entry" points. (The clouds represent weather being less extreme and better for surfing).
(**While these should mostly be ignored, these have not been muted because there is the possibility of a very strong turn around if you happen to catch the last one (which is not ideal for risk-averse traders). Use other indicators, such as the MACD and trend lines, to find potential bottoms (or tops) as price action plunges (or soars) due to abnormal news circumstances.)
Entry and exit buffers
At the beginning of each day, most indicators usually are not immediately calibrated correctly due to premarket trading and open market (at least to the degree that the day's sentiment can be best read from them due to the amount of volatility). What I recommend when using this indicator is disregarding signals during the first 15 minutes (or possibly 30 minutes) of market open to get the best results. And also, considering this indicator is meant for day trading (i.e., not holding positions overnight), disregarding ENTRY signals for the last 45 minutes of the trading day could give yourself enough buffer on the back end for exiting comfortably.
RSI entry
Preparing for an entry when you see a surfer is recommended, but actually opening the position when you see a 🌤️ (Put) or 🌧️ (Call) would yield best results and avoid misfires — particularly when those two cloud EMOJIs are signaled when the RSI is overbought and K is at least 95 (Puts), or oversold and K at maximum 5 (Calls). (Story time logic: The cloud eclipsing the Sun means it's cooling off and better for surfing. And the rain cloud no longer having lightning means the "bearish" storm is possibly soon over).
Delta and the Greeks
You should experiment yourself, but keep in mind that this is for capitalizing off of a day's minor price swings (≤3% + or -). Entering a same day expiry contract that's deep OTM is not going to work with this indicator (even if you enter at a surfer 🏄🏾 and exit at a Kraken 🦑) because the price wave from one end to the other won't be enough to compensate for the other Greeks working against you. Use another indicator (or insider knowledge ... Just kidding, that's illegal, don't do that) if you want to buy those kind of contracts.
I personally purchase contracts w/ minimum 80% Implied Volatility and somewhere between 20-40 Delta. Having a nice range for yourself with these factors, depending also on the size of your own portfolio and the risk tolerance you have, will determine how much you're able to capitalize off successful entry and exits.
Tips
• I set stop losses 5-10% depending on the ticker. (e.g., $TSLA's volatility may require SL closer to 10% whereas using it on $SPY, a 5% could suffice). This is in addition to ignoring entry signals that don't meet the aforementioned two requirements (i.e., it's risky to Surf in shallow water, and you shouldn't try to Surf at all outside of the water, ref. Band 2 and outside of Band 2). Remember, this is the stock market — not the casino. We rely on strategy and risk management — not hope.
• It's recommended you use time intervals ≤ 5 min. (I use 1 minute and 5 min)
• Liquidity . Using these signals on a ticker with low liquidity (particularly if you enter on the Ask side), can reduce your profits to 0% or even to a loss even if you have a perfect entry and exit. I always point to SPY as the optimal bid-ask spread, but keep that in mind.
What's with the name "Ichi-Price Wave"?
The "Ichi" gives credit to Japanese journalist Goichi Hosoda, whose indicator I used in conjunction with the 13/48 Exponential Moving Averages to create some of the exit signal conditions (e.g., E2🦈). That E2 condition is: Signal the first time the price intersects the Ichimoku conversion line *after* it has entered the VWAP UB/LB channel on one end and has exited on the opposite end). And it's named "Price Wave" because it's a literal price wave, which is where the fun surf narrative comes in. Also, "Price" doubles as me naming it after myself (in a less pretentious way). It's actually convenient that my last name is literally Price. Almost as if I was born for this. Nonetheless, this indicator is far more accurate in spotting directional changes than the free 13/48 cross, which oddly enough, influencers are charging for access. It's free, but the code is protected, for now at least.
Try it out on any ticker and look at how accurately it catches the tops and bottoms (keeping in mind to ignore misfires according to the two measures and also setting ~5-10% stop losses). And of course, use this in conjunction with other indicators. Ignoring all of my other emojis and simply setting surfer 🏄🏾 alerts could serve as additional confirmations for your personal strategy. Or you could simply enter at a surfer 🏄🏾 and exit when it reaches VWAP (or at least increase your Stop Loss to sell at break even if it doesn't reach). That strategy is the most conservative and would secure consistent gains). AND AGAIN, use your stop losses. Either it makes a move or it doesn't. Simply re-enter at a better point if necessary.
PecuniaThe Pecunia indicator
It is a momentum indicator developed by tradewithpecunia. Our indicator is made with more than 4+ robust indicators. The indicator makes use of double top/ double bottom, price action movement, rectangle breakouts & divergence concepts with the crossover of 3+ moving averages.
Different parameters (mathematical calculations for each) have been set by us for each mentioned concept above. The indicator detects different trends in the price using 2 different algorithms. The use of 4 slopes has been done which catches momentum at different positions, according to the parameter set. We call this a knockout system because only when all the parameters are satisfied the buy and sell signal is generated. Even if one parameter fails the signals are not generated, this ensures that there is a momentum check and enough buy and sell signals are produced.
Using 4 parameters for upper bound/lower bounds the catch for median points has been done. 10+ & 10- lengths are looked at from the median points where we have put the stop loss.
Value points
1) The Trade Entry – The indicator continuously looks for suitable data values which when match with the parameters set by us, results in the generation of buy and sell signals. Once the condition is met, the buy and sell signals are displayed on the charts in real-time. Further one can set up an alert that is displayed on the screen and can be modified as an automated alert utilizing the trading view platform’s alert function.
2) The Order Execution – It is recommended to execute the order just before the candle is ended to avoid any hassle or the user can execute the order at the following candle to avoid any false signals set off due to volatility. The choice of instrument to use is the trader’s discretion keeping in mind their own risk/reward involved.
3) Exit Triggers – For an ongoing buy signal, you have to exit or book your profits from the trade at the sell signal. And for an ongoing sell signal, you have to exit or book your profits from the trade at the buy signal. If there is an ongoing buy or sell signal and it’s not moving in our desired trend then you have to take the stop loss at the trade exit signal or its opposite trade signal.
Color Notations:
By default, the color of the buy signal is green and the color of the sell signal is red. The color of the Trade Exit signal is black. Although the user can change the color of the signals at their convenience.
The Features:
1) Easy to understand signal bars
2) Easily distinguishable Buy and Sell signals
3) One must take into consideration that there is no holy grail method
Note:
If you are using this script, you acknowledge that the past performance is not necessarily the indication of future results and there are many more factors that go into being a profitable trader.
Before you proceed:
We are not SEBI Registered Analysts and shall not be culpable for any loss incurred directly or indirectly. Our indicator is no holy grail system. Investment in the stock market is subject to market risk. Trading in stocks, futures, or options is not suitable for every trader and involves a considerable risk of loss.
The market may fluctuate, and the user always has a risk of loss, thus, we won’t be liable for any losses incurred while using our indicator, our trading ideas, or our approach.
OnePunch Algo KITEIntroducing One of OnePunch ALGO Flagship plugin. In this plugin it comes with a in-built risk management system plus it allows users stop loss input per trade. This can be used with Cryptocurrency and Stocks equally.
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OnePunch ALGO KITE should be used with 30min or upper time limits, this is built for long term trading strategies. Make sure once you pick a crypto or stock to trade, check its backtest data: which can be found at Strategy Tester. A good strategy should always out perform the Buy & Hold for a given timeframe.
Best Bar Time: 45m
Other Options
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Short Term/Day Trading Setup
For Short Term or Day Trade: 5min, 15min & 30min candlesticks
Mid Term Trading Setup
For Mid-term traders: 45m, 1hr, 2hr, and 3hr setup works really well.
For Long Term Trading Setup
For long term traders: 4hr, 1D, 1Week and 1Month Setup works well.
* Best timeframe should beat buy and hold for a given timeline.
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####### How Strategy Work ########
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Strategy use multiple signals and technical data. Including and not limited to Simple Moving Averages, Volume , & Trends. In this chart, we picked Polkadot (DOTUSD) crypto coin as an example with an initial capital of $1k. We have also added a slippage of 1 just to be on the safe side and a commission rate of 0.01% (Commission rates depends of your broker).
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######## Built with Inputs #########
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Date Pick: User can backtest the plugin with exact date you want from to till. For an example, you can check date from 01 / 01 /2020 (Default setting date) till day, and compare apple to apple results with other stocks. This is mostly used to check if another stock/crypto do better than the other compared to a given timeframe.
Risk Management per Trade: This also allows users to put their own risk management loss percentage. In default it is set to 100%. This allows user to see in the long run, if this provide better results with or without a stop loss.
Commission Rates: User can update commission rates according to their broker's fees
Slippage: To be more conservative about the entry and exit of a trade, user can input any slippage amount
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#### How to Detect BUY Signals #####
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When a teal color BUY signal is given, it is a BUY. This signal basically happen when a stock land in a high volatility zone. We use in-build systems such as MA , Support and Resistance and Trends to come up with the Buy Signal. Algorithm make a market order when the criteria's are met and algorithm exit if this turns out to be a bluff bullish signal.
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#### How to Detect SELL Signals #####
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When a maroon color SELL signal is given, it is a SELL happen when a momentum changed in a bearish downtrend. Sell happen when a momentum changed in a bearish downtrend. We use moving averages and trend analysis to identify downtrends. Algorithm make a market order when the criteria's are met. There is a in-built risk management that make an exit order when a bullish alert turns out to be a bluff.
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#### Bullish and Bearish Signals #####
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When a silver color Bearish signal is given, it is a BEARISH trend alert. It's up to the user to decide what to do when this alert is given. (Note: Backtest data only shows Buy and Sell Signal market orders results, it does not account bearish alerts), a Bearish signal given when the stock/crypto is overbought in multiple technical indicators.
When a sea blue Bullish trend signaled. (Mind this sea blue color signal will not be calculated in the backtest, it is up to the users to decide what to do with this bullish signal) - This signal happen when a stock is oversold in multiple technical indicators.
DISCLAIMER: Stocks and options trading involves substantial RISK of LOSS and is NOT suitable for every investor. The valuation of stocks and options may fluctuate, and, as a result, clients may lose more than their original investment. If the market moves against you, you may sustain a total loss greater than the amount you deposited into your account. You are responsible for all the risks and financial resources you use and for the chosen trading system. You should not engage in trading unless you fully understand the nature of the transactions you are entering into and the extent of your exposure to loss. If you do not fully understand these risks, you must seek independent advice from your financial advisor.
All trading strategies are used at your own risk. And OnePunch ALGO Developer does NOT take any responsibility for your losses using any of the advice or suggestions or strategies are shown/said in any of OnePunch ALGO publications.
[Joy] Aladdin (1.0.0 Alpha)Explanation of the markers in the indicator
* Bearish / Sell sign: On the candle's close, I open a short position
* Bullish sign: On the candle's close, I open a long position
* Red circle: On the candle's close, I take at least 50% unrealized profit into a realized profit of any running long leverage position. I might even convert some portion of the position into stable coins.
* Green circle: On the candle's close, I take at least 50% unrealized profit into a realized profit of any running short leverage position. I might even convert some portion of the position into stable coins.
* Down Arrows: When the down arrow finishes and the candle close, I put a tighter stop loss of any running long leverage position. It sometimes indicates the local top.
* Up Arrows: When the up arrow finishes and the candle close, I put a tighter stop loss of any running short leverage position. It sometimes indicates the local bottom.
* Purple candle: Weakly bullish.
* Green candle: Strongly bullish
* Red candle: Strongly bearish
* Yellow candle: Weakly bearish
FAQ
Q: Does it use some EMA /MA/etc.? Does it use any indicator with tweaked settings?
Answer: No.
Q: What does it mostly depend on?
Answer: Volume and gradual flow of non-interrupted data. The logic depends purely on volume, price bars and the wicks.
Q: Does it work with all coins, stocks, futures, instruments?
Answer: I prefer to use the exchange with the best possible data. Then backtest out to find the best possible timeframe, stop loss and target all derived from this script data.
Q: Can you make it free or make it open source?
Answer: There is no free lunch in this world. I will never reveal or share the source code!
Q: Do you provide ongoing support for the indicator?
Answer: Yes, as long as I can, I will continue updating the indicator
Q: Are the bullish /buy & the bearish /sell markers automatic?
Answer: I have no control over the markers. It is driven purely by logic from the script.
Q: Is this financial advice?
Answer: This is not financial advice. I do not guarantee any profit or loss. I am not responsible for any of your losses or profits. My indicators do not assure profit or loss. It also does not auto-open or auto-close a trade.
Note:
The Aladdin has been derived from the Super Algorithm Indicator. I have depreciated the Super Algorithm Indicator I have automatically migrated every user to Aladdin, who had Super Algorithm Indicator. One should not use the SA indicator. One should start using this indicator instead.
Version 1
A derived version of Super Algorithm Indicator with optimized code (uses arrays, removes few warnings in the code, makes code more reusable) so that I can add further features in the future. A few new coding features in the pine script encouraged me to go for this version. Since the codebase has been revamped, it made sense for me to make it a new indicator. have also changed a small parameter that is configurable at the moment. Previously it was valued at 26. Now I am putting value at 21.
Dankland Playground Moneymaker - V2“version 2” of my playground bot script. Its essentially a powerhouse suite of strategies. Although it is similar to the previous script, it nets different results as sections have been changed. Such as the somewhat reluctant removal of the Chande Momentum... The RSIs have also been updated, this was one of the main changes. RSIS now include a Moving Average cross of RSI to generate signals above and below the given thresholds instead of simply on crossing a threshold. This should give greater functionality overall. Most functions including Moving Averages have been updated to include a wider range of kinds of moving averages. This includes not just the moving average cross, but MACD and RSIs as well. I tried to perform the same upgrade on the %B, Stochastics and SMI, but hit the unpacked code limit of 60,000 lines... So, more “versions” will have to come for future “upgrades”, with the recognition that there will be cases where the old, “downgraded” versions may perform better and that some people (like myself) may continue to use them on some markets until I/we devise superior settings on the new ones for said markets. For instance, instead of replacing my 1 hr BTCUSD bot (where I used the now deleted Chande to pretty pleasing affect...) I made a new one for LINKUSD 10 min so I can have both running for now and work on replacing the BTCUSD later.
How it works basically is this... you have 16 oscillators which can all be used as independently as you wish. They can be split up into different groups or ran all together.
When in separate groups they should not be able to sell eachothers positions without triggering a full stop loss by turning the Independence/Stop All switches on. Every single oscillator has its own entry and exit position sizing which can be stated as either a percent of balance or a flat amount of contracts (or both combined). Each oscillator has a minimum amount of profit you can tell it to sell it, which is calculated from the average cost of your current position, which does include all groups. This works out to help you average out better entry and exit prices, essentially a method of DCAing.
You can set the minimum sale amount, which is to keep it from placing orders below your exchanges minimum dollar trade cost.
All this functionality combined also ensures more accurate back tests by ensuring that the script simply cannot spend money it doesn't see as in the balance, whereas other scripts will use a percentage of equity, and once 100% of your equity is in BTC for instance, it will keep buying more BTC for free and thus spoof up backtest numbers. If you look through the strategies here, many people claim to have amazing scripts and then you look into it and this is happening and skewing their numbers. These people are either very ignorant or what they made or scam artists and trolls in my opinion.
This version also includes On Bar Close switches for each oscillator. When switched on, signals are only allowed to generate on Bar Close. This helps to prevent retriggering from live signals, which when you are running this many oscillators, will become a problem! However, in most cases, you do not need to generate signals intrabar, as backtests will show, ignoring intrabar buys and sells (intrabar stop losses can still be very important though!) won't exactly keep you from high profitability strategies, but rather, allowing elements of chaos from live indicators moving up and down intrabar will, in fact, drift your actual results further and further from the backtest. You want an accurate backtest though. So choose wisely when you turn these off and you will do better.
The included oscillators are as follows:
NO MORE Chande Momentum cross – REMOVED – I was hitting PINE code limits here so I had to make choices and this one simply had to go. Begone!
Moving Average Cross
MACD cross
%B Bollinger cross
Stochastic cross + region filter
Stochastic RSI cross + region filter
SMII cross and region filter
Three RMIs
Know-Sure-Thing line-cross
Coppock Curve line-cross
TRIX line-cross
RSI of MA w/ MA cross
RSI of MA of KST w/ MA cross
RSI of MA of Coppock Curve w/ MA cross
RSI of MA of Trix w/ MA cross
So the idea is that this is essentially multiple strategies combined into one backtestable house. Balance is calculated for all position sizes in order to try to prevent false entries that plague so many scripts (IE, you set pyramiding to 2, each buy $1000, initial balance $1000, and yet it buys two orders off the bat for $2000 total and nets 400% profit because the second was considered free, happens on 90+% of scripts on Tradingview if you aren't very very careful!)
You tune each indicator and position size them so that they work together as well as you can and in doing so you are able to create a single backtest that is capable of running a bot, essentially, between multiple strategies - you can run a slower Moving Average cross, a faster SMI cross or MACD , or Bollinger that grabs big moves only, all the while having MACD trade small bonuses along the way. This way you can weight the Risk to Reward of each against eachother.
I will not try to claim this is something you can open and with no work have the best bot on the planet. This scripts intention is to take a lot of relatively common trading strategies and combine them under on roof with some risk management and the ability to weigh each against eachother.
If you are looking for a super advanced singular algorithm that tries to capture every peak and valley exactly on the dot, this is not for you. If you are looking for a tool with a high level of customizability, with a publisher who intends to update it to the best of his ability in accordance to seeking to make the best product that I personally can make for both myself and the community (because I will be using this myself of course!) that was specifically designed with the intention of performing well in spot markets by averaging low entry costs and high exit costs, this is for you! That is the exact intention here. It can certainly work with margin, but you will have to take extra care in setting your stop losses. I intend to make a version capable of going short which will be included as part of the package. It may take some work to keep all of the risk management working as well for shorts though. There will be more scripts added to the “package” as I hit the limit on this one a few times and have had to keep some ideas out already.
The current backtest shown is hand-optimized by myself for Link /USD 10min market (Binance US – shouldn't need much work to fit to other exchange markets) with multiple stop losses.
(IK) Base Break BuyThis strategy first calculates areas of support (bases), and then enters trades if that support is broken. The idea is to profit off of retracement. Dollar-cost-averaging safety orders are key here. This strategy takes into account a .1% commission, and tests are done with an initial capital of 100.00 USD. This only goes long.
The strategy is highly customizable. I've set the default values to suit ETH/USD 15m. If you're trading this on another ticker or timeframe, make sure to play around with the settings. There is an explanation of each input in the script comments. I found this to be profitable across most 'common sense' values for settings, but tweaking led to some pretty promising results. I leaned more towards high risk/high trade volume.
Always remember though: historical performance is no guarantee of future behavior . Keep settings within your personal risk tolerance, even if it promises better profit. Anyone can write a 100% profitable script if they assume price always eventually goes up.
Check the script comments for more details, but, briefly, you can customize:
-How many bases to keep track of at once
-How those bases are calculated
-What defines a 'base break'
-Order amounts
-Safety order count
-Stop loss
Here's the basic algorithm:
-Identify support.
--Have previous candles found bottoms in the same area of the current candle bottom?
--Is this support unique enough from other areas of support?
-Determine if support is broken.
--Has the price crossed under support quickly and with certainty?
-Enter trade with a percentage of initial capital.
-Execute safety orders if price continues to drop.
-Exit trade at profit target or stop loss.
Take profit is dynamic and calculated on order entry. The bigger the 'break', the higher your take profit percentage. This target percentage is based on average position size, so as safety orders are filled, and average position size comes down, the target profit becomes easier to reach.
Stop loss can be calculated one of two ways, either a static level based on initial entry, or a dynamic level based on average position size. If you use the latter (default), be aware, your real losses will be greater than your stated stop loss percentage . For example:
-stop loss = 15%, capital = 100.00, safety order threshold = 10%
-you buy $50 worth of shares at $1 - price average is $1
-you safety $25 worth of shares at $0.9 - price average is $0.966
-you safety $25 worth of shares at $0.8. - price average is $0.925
-you get stopped out at 0.925 * (1-.15) = $0.78625, and you're left with $78.62.
This is a realized loss of ~21.4% with a stop loss set to 15%. The larger your safety order threshold, the larger your real loss in comparison to your stop loss percentage, and vice versa.
Indicator plots show the calculated bases in white. The closest base below price is yellow. If that base is broken, it turns purple. Once a trade is entered, profit target is shown in silver and stop loss in red.
BBofVWAP with entry at Pivot PointThis strategy uses BB of VWAP and Pivot point to enter and exit the Long position.
settings
BB length 50
BB Source VWAP
Entry
When VWAP crossing up BB midline and price/close is above weekly PivotPoint ( you can also use Daily pivot point )
Exit
When VWAP is crossing down BB lower band
Stop Loss
Stop loss defaulted to 5%
Note : Long will position will be exited on either VWAP crossing down BB lower band or stop loss is hit - whichever comes first . Being said that some time your stop loss exit is less than 5% which saves from more losses.
Entry is based on weekly Pivot point , so any time frame below weekly will work perfect. I have tested t on 30 min , 1 HR , 4 Hr , Daily charts. Even weekly setting shows good results , that will work for long term investing style.
if you change Pivot period to Daily , chose time frames below Daily.
I also noticed this strategy mostly do not enter Long position in a down trend. Even it finds one , it will be exited with minimal loss.
Warning
For the use of educational purposes only
Strategy Builder Crypto V6Hello everyone
This indicator is the result of 7 years of trading (including 3 years of analyzing day and night how crypto assets behave).
I made it fully customizable but I wouldn't recommend changing the default values as they're the most optimal ones for now. Might change in the future but I'm very happy with the signals so far and I hope you'll be as well :)
Without further due, let's dig into it...
0 - Algo trading and Why
In the crypto trading, there is a lot of useless noise (we can probably thank Crypto Twitter for that :p) and a lot of useless data with the sole purpose is to lure you (who said Bitfinex Long/Short ratio or CME gaps ??)
I wanted to remove all the useless and only focus on Technical Analysis (TA) because I was deeply convinced that TA includes by design Fundamental Analysis (FA) and Pumponomics Analysis (PA) - PA being for instance when your favorite twitter guru will pump and dump on you
I heard that so many people got REKT from the previous bear market and I wanted to give back to the community - who helped me so much a few years back.
I worked hard to design the method and make it simple for the public and for FREE (so far as I want to collect feedbacks from the community and improving the indicator)
THIS IS MY GIFT TO YOU
1 - Input values
I'll explain later on through a medium article what each parameter means and how to set them up. For now, please used the optimized and recommended values already set in the indicator
2 - The method
This method works for intraday trading for timeframes between m5 and H1. Any timeframe above could work but would give signals too late - in this case, I would recommend changing the inputs with smaller values to adjust
I see a trend being composed of a main trend, and mini sub trends. In other words, for instance, a weekly bullish trend is made of smaller H4 bullish trends. Hope it makes sense so far
Let's call the weekly trend the MAIN trend and the H4 smaller trends the SECONDARY trends
That's exactly what this indicator is about
It will catch the best MAIN trend and all the SECONDARY trends in the same direction of the MAIN trend.
It's up to you if you want to take all the SECONDARY trends or only the first one in the sequence.
3 - Invalidation signal
A signal invalidation is used to make you exiting your position with a small loss before your stop loss will get hit. Very powerful way to save your capital and limit your losses.
You'll find the indicator here on tradingview for free under the name Trend signal with Alert (made by myself)
Trend signal with Alert
to invalidate entries. You'll need to request an invite
Briefly, let's assume we get a BUY signal. I would exit the position either if I'm getting a DOWN trend signal. It means, if the oblique/logarithmic trendline is broken, then it's better to exit the position and wait for the indicator to give another BUY signal later hopefully
Best case, it will limit your loss in case the asset will dump.
Worst case, this strict management strategy will make you exiting your position for no reason and you'll re-enter later (with a signal) at almost the same price or a bit higher
In the long run, this method will prevent you from having big losses
4 - Stop Loss and Take profits levels
It's really up to you. It depends of your capital and psychology
This indicator is made to give big moves but that's not 100% guaranteed. You can draw some trendlines or use moving averages in big timeframes to set your take profit and stop loss levels.
I personally use this also, along with fibonacci on the weekly/monthly timeframes for my take profit levels
As I'm a nice person, I'm linking the Fibonacci indicator that I use here
Automatic Multi-timeframes fibonacci zones
. You'll also need to request an invite for that one
4-bis - Trailing stop
Not financial advice but I use a supertrend and I have a software that will trail my stop according to that supertrend level
For LONG positions, we could set the trailing below the supertrend.
For SHORT positions, we could set the trailing above the supertrend.
You'll find the indicator here on tradingview for free under the name Supertrend V1.0 - Buy or Sell Signal
5 - Which assets
It's working with the default values on major/mid/small caps and for ALTS/BTC, ALTS/USD and ALTS/ETH pairing
YES, THIS IS MOST AWESOME THING OF THE ENTIRE UNIVERSE !!!
6 - Best setup
m15 timeframe is my preferred one for this method. Best Risk/Reward/Invalidations ratio among all other timeframes
I strongly recommend to use the Trend Signal with the input value 14 for the invalidations
If you enter on a BUY signal, and get a RED trend signal, exit immediately the position without waiting for any other confirmation/pullback or anything else
If you enter on a SELL signal, and get a BLUE trend signal, exit immediately the position without waiting for any other confirmation/pullback or anything else
For the trailing stop/Supertrend value, it depends of your capital and how big your stop loss should be. I personally use the settings in the Supertrend indicator
7 - Alerts
You can setup alerts for the primary and secondary signals in Tradingview so that you won't have to stare at the charts all day long. You mental healthy is my priority above everything else :)
8 - More to come
I personally use the alerts from this indicator coupled with a system to take the trades given by the tradingview alerts. I'll publish it later on if I feel the indicator collects enough interest from you guys
Opening Range Breakout with Multi-Timeframe Liquidity]═══════════════════════════════════════
OPENING RANGE BREAKOUT WITH MULTI-TIMEFRAME LIQUIDITY
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A professional Opening Range Breakout (ORB) indicator enhanced with multi-timeframe liquidity detection, trading session visualization, volume analysis, and trend confirmation tools. Designed for intraday trading with comprehensive alert system.
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WHAT THIS INDICATOR DOES
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This indicator combines multiple trading concepts:
- Opening Range Breakout (ORB) - Customizable time period detection with automatic high/low identification
- Multi-Timeframe Liquidity - HTF (Higher Timeframe) and LTF (Lower Timeframe) key level detection
- Trading Sessions - Tokyo, London, New York, and Sydney session visualization
- Volume Analysis - Volume spike detection and strength measurement
- Multi-Timeframe Confirmation - Trend bias from higher timeframes
- EMA Integration - Trend filter and dynamic support/resistance
- Smart Alerts - Quality-filtered breakout notifications
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HOW IT WORKS
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OPENING RANGE BREAKOUT (ORB):
Concept:
The Opening Range is a period at the start of a trading session where price establishes an initial high and low. Breakouts beyond this range often indicate the direction of the day's trend.
Detection Method:
- Default: 15-minute opening range (configurable)
- Custom Range: Set specific session times with timezone support
- Automatically identifies ORH (Opening Range High) and ORL (Opening Range Low)
- Tracks ORB mid-point for reference
Range Establishment:
1. Session starts (or custom time begins)
2. Tracks highest high and lowest low during the period
3. Range confirmed at end of opening period
4. Levels extend throughout the session
Breakout Detection:
- Bullish Breakout: Close above ORH
- Bearish Breakout: Close below ORL
- Mid-point acts as bias indicator
Visual Display:
- Shaded box during range formation
- Horizontal lines for ORH, ORL, and mid-point
- Labels showing level values
- Color-coded fills based on selected method
Fill Color Methods:
1. Session Comparison:
- Green: Current OR mid > Previous OR mid
- Red: Current OR mid < Previous OR mid
- Gray: Equal or first session
- Shows day-over-day momentum
2. Breakout Direction (Recommended):
- Green: Price currently above ORH (bullish breakout)
- Red: Price currently below ORL (bearish breakout)
- Gray: Price inside range (no breakout)
- Real-time breakout status
MULTI-TIMEFRAME LIQUIDITY:
Two-Tier System for comprehensive level identification:
HTF (Higher Timeframe) Key Liquidity:
- Default: 4H timeframe (configurable to Daily, Weekly)
- Identifies major institutional levels
- Uses pivot detection with adjustable parameters
- Suitable for swing highs/lows where large orders rest
LTF (Lower Timeframe) Key Liquidity:
- Default: 1H timeframe (configurable)
- Provides precision entry/exit levels
- Finer granularity for intraday trading
- Captures minor swing points
Calculation Method:
- Pivot high/low detection algorithm
- Configurable left bars (lookback) and right bars (confirmation)
- Timeframe multiplier for accurate multi-timeframe detection
- Automatic level extension
Mitigation System:
- Tracks when levels are swept (broken)
- Configurable mitigation type: Wick or Close-based
- Option to remove or show mitigated levels
- Display limit prevents chart clutter
Asset-Specific Optimization:
The indicator includes quick reference settings for different assets:
- Major Forex (EUR/USD, GBP/USD): Default settings optimal
- Crypto (BTC/ETH): Left=12, Right=4, Display=7
- Gold: HTF=1D, Left=20
TRADING SESSIONS:
Four Major Sessions with Full Customization:
Tokyo Session:
- Default: 04:00-13:00 UTC+4
- Asian trading hours
- Often sets daily range
London Session:
- Default: 11:00-20:00 UTC+4
- Highest liquidity period
- Major institutional activity
New York Session:
- Default: 16:00-01:00 UTC+4
- US market hours
- High-impact news events
Sydney Session:
- Default: 01:00-10:00 UTC+4
- Earliest Asian activity
- Lower volatility
Session Features:
- Shaded background boxes
- Session name labels
- Optional open/close lines
- Session high/low tracking with colored lines
- Each session has independent color settings
- Fully customizable times and timezones
VOLUME ANALYSIS:
Volume-Based Trade Confirmation:
Volume MA:
- Configurable period (default: 20)
- Establishes average volume baseline
- Used for spike detection
Volume Spike Detection:
- Identifies when volume exceeds MA * multiplier
- Default: 1.5x average volume
- Confirms breakout strength
Volume Strength Measurement:
- Calculates current volume as percentage of average
- Shows relative volume intensity
- Used in alert quality filtering
High Volume Bars:
- Identifies bars above 50th percentile
- Additional confirmation layer
- Indicates institutional participation
MULTI-TIMEFRAME CONFIRMATION:
Trend Bias from Higher Timeframes:
HTF 1 (Trend):
- Default: 1H timeframe
- Uses EMA to determine intermediate trend
- Compares current timeframe EMA to HTF EMA
HTF 2 (Bias):
- Default: 4H timeframe
- Uses 50 EMA for longer-term bias
- Confirms overall market direction
Bias Classifications:
- Bullish Bias: HTF close > HTF 50 EMA AND Current EMA > HTF1 EMA
- Bearish Bias: HTF close < HTF 50 EMA AND Current EMA < HTF1 EMA
- Neutral Bias: Mixed signals between timeframes
EMA Stack Analysis:
- Compares EMA alignment across timeframes
- +1: Bullish stack (lower TF EMA > higher TF EMA)
- -1: Bearish stack (lower TF EMA < higher TF EMA)
- 0: Neutral/crossed
Usage:
- Filters false breakouts
- Confirms trend direction
- Improves trade quality
EMA INTEGRATION:
Dynamic EMA for Trend Reference:
Features:
- Configurable period (default: 20)
- Customizable color and width
- Acts as dynamic support/resistance
- Trend filter for ORB trades
Application:
- Above EMA: Favor long breakouts
- Below EMA: Favor short breakouts
- EMA cross: Potential trend change
- Distance from EMA: Momentum gauge
SMART ALERT SYSTEM:
Quality-Filtered Breakout Notifications:
Alert Types:
1. Standard ORB Breakout
2. High Quality ORB Breakout
Quality Criteria:
- Volume Confirmation: Volume > 1.2x average
- MTF Confirmation: Bias aligned with breakout direction
Standard Alert:
- Basic breakout detection
- Price crosses ORH or ORL
- Icon: 🚀 (bullish) or 🔻 (bearish)
High Quality Alert:
- Both volume AND MTF confirmed
- Stronger probability setup
- Icon: 🚀⭐ (bullish) or 🔻⭐ (bearish)
Alert Information Includes:
- Alert quality rating
- Breakout level and current price
- Volume strength percentage (if enabled)
- MTF bias status (if enabled)
- Recommended action
One Alert Per Bar:
- Prevents alert spam
- Uses flag system to track sent alerts
- Resets on new ORB session
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HOW TO USE
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OPENING RANGE SETUP:
Basic Configuration:
1. Select time period for opening range (default: 15 minutes)
2. Choose fill color method (Breakout Direction recommended)
3. Enable historical data display if needed
Custom Range (Advanced):
1. Enable Custom Range toggle
2. Set specific session time (e.g., 0930-0945)
3. Select appropriate timezone
4. Useful for specific market opens (NYSE, LSE, etc.)
LIQUIDITY LEVELS SETUP:
Quick Configuration by Asset:
- Forex: Use default settings (Left=15, Right=5)
- Crypto: Set Left=12, Right=4, Display=7
- Gold: Set HTF=1D, Left=20
HTF Liquidity:
- Purpose: Major support/resistance levels
- Recommended: 4H for day trading, 1D for swing trading
- Use as profit targets or reversal zones
LTF Liquidity:
- Purpose: Entry/exit refinement
- Recommended: 1H for day trading, 4H for swing trading
- Use for position management
Mitigation Settings:
- Wick-based: More sensitive (default)
- Close-based: More conservative
- Remove or Show mitigated levels based on preference
TRADING SESSIONS SETUP:
Enable/Disable Sessions:
- Master toggle for all sessions
- Individual session controls
- Show/hide session names
Session High/Low Lines:
- Enable to see session extremes
- Each session has custom colors
- Useful for range trading
Customization:
- Adjust session times for your broker
- Set timezone to match your location
- Customize colors for visibility
VOLUME ANALYSIS SETUP:
Enable Volume Analysis:
1. Toggle on Volume Analysis
2. Set MA length (20 recommended)
3. Adjust spike multiplier (1.5 typical)
Usage:
- Confirm breakouts with volume
- Identify climactic moves
- Filter false signals
MULTI-TIMEFRAME SETUP:
HTF Selection:
- HTF 1 (Trend): 1H for day trading, 4H for swing
- HTF 2 (Bias): 4H for day trading, 1D for swing
Interpretation:
- Trade only with bias alignment
- Neutral bias: Be cautious
- Bias changes: Potential reversals
EMA SETUP:
Configuration:
- Period: 20 for responsive, 50 for smoother
- Color: Choose contrasting color
- Width: 1-2 for visibility
Usage:
- Filter trades: Long above, Short below
- Dynamic support/resistance reference
- Trend confirmation
ALERT SETUP:
TradingView Alert Creation:
1. Enable alerts in indicator settings
2. Enable ORB Breakout Alerts
3. Right-click chart → Add Alert
4. Select this indicator
5. Choose "Any alert() function call"
6. Configure delivery method (mobile, email, webhook)
Alert Filtering:
- All alerts include quality rating
- High Quality alerts = Volume + MTF confirmed
- Standard alerts = Basic breakout only
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TRADING STRATEGIES
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CLASSIC ORB STRATEGY:
Setup:
1. Wait for opening range to complete
2. Price breaks and closes above ORH or below ORL
3. Volume > average (if enabled)
4. MTF bias aligned (if enabled)
Entry:
- Bullish: Buy on break above ORH
- Bearish: Sell on break below ORL
- Consider retest entries for better risk/reward
Stop Loss:
- Bullish: Below ORL or range mid-point
- Bearish: Above ORH or range mid-point
- Adjust based on volatility
Targets:
- Initial: Range width extension (ORH + range width)
- Secondary: HTF liquidity levels
- Final: Session high/low or major support/resistance
ORB + LIQUIDITY CONFLUENCE:
Enhanced Setup:
1. Opening range established
2. HTF liquidity level near or beyond ORH/ORL
3. Breakout occurs with volume
4. Price targets the liquidity level
Entry:
- Enter on ORB breakout
- Target the HTF liquidity level
- Use LTF liquidity for position management
Management:
- Partial profits at ORB + range width
- Move stop to breakeven at LTF liquidity
- Final exit at HTF liquidity sweep
ORB REJECTION STRATEGY (Counter-Trend):
Setup:
1. Price breaks above ORH or below ORL
2. Weak volume (below average)
3. MTF bias opposite to breakout
4. Price closes back inside range
Entry:
- Failed bullish break: Short below ORH
- Failed bearish break: Long above ORL
Stop Loss:
- Beyond the failed breakout level
- Or beyond session extreme
Target:
- Opposite end of opening range
- Range mid-point for partial profit
SESSION-BASED ORB TRADING:
Tokyo Session:
- Typically narrower ranges
- Good for range trading
- Wait for London open breakout
London Session:
- Highest volume and volatility
- Strong ORB setups
- Major liquidity sweeps common
New York Session:
- Strong trending moves
- News-driven volatility
- Good for momentum trades
Sydney Session:
- Quieter conditions
- Suitable for range strategies
- Sets up Tokyo session
EMA-FILTERED ORB:
Rules:
- Only take bullish breaks if price > EMA
- Only take bearish breaks if price < EMA
- Ignore counter-trend breaks
Benefits:
- Reduces false signals
- Aligns with larger trend
- Improves win rate
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CONFIGURATION GUIDE
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OPENING RANGE SETTINGS:
Time Period:
- 15 min: Standard for most markets
- 30 min: Wider range, fewer breakouts
- 60 min: For slower markets or swing trades
Custom Range:
- Use for specific market opens
- NYSE: 0930-1000 EST
- LSE: 0800-0830 GMT
- Set timezone to match exchange
Historical Display:
- Enable: See all previous session data
- Disable: Cleaner chart, current session only
LIQUIDITY SETTINGS:
Left Bars (5-30):
- Lower: More frequent, sensitive levels
- Higher: Fewer, more significant levels
- Recommended: 15 for most markets
Right Bars (1-25):
- Confirmation period
- Higher: More reliable, less frequent
- Recommended: 5 for balance
Display Limit (1-20):
- Number of active levels shown
- Higher: More context, busier chart
- Recommended: 7 for clarity
Extension Options:
- Short: Levels visible near formation
- Current: Extended to current bar (recommended)
- Max: Extended indefinitely
VOLUME SETTINGS:
MA Length (5-50):
- Shorter: More responsive to spikes
- Longer: Smoother baseline
- Recommended: 20 for balance
Spike Multiplier (1.0-3.0):
- Lower: More sensitive spike detection
- Higher: Only extreme spikes
- Recommended: 1.5 for day trading
MULTI-TIMEFRAME SETTINGS:
HTF 1 (Trend):
- 5m chart: Use 15m or 1H
- 15m chart: Use 1H or 4H
- 1H chart: Use 4H or 1D
HTF 2 (Bias):
- One level higher than HTF 1
- Provides longer-term context
- Don't use same as HTF 1
EMA SETTINGS:
Length:
- 20: Responsive, more signals
- 50: Smoother, stronger filter
- 200: Long-term trend only
Style:
- Choose contrasting color
- Width 1-2 for visibility
- Match your trading style
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BEST PRACTICES
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Chart Timeframe Selection:
- ORB Trading: Use 5m or 15m charts
- Session Review: Use 1H or 4H charts
- Swing Trading: Use 1H or 4H charts
Quality Over Quantity:
- Wait for high-quality alerts (volume + MTF)
- Avoid trading every breakout
- Focus on confluence setups
Risk Management:
- Position size based on range width
- Wider ranges = smaller positions
- Use stop losses always
- Take partial profits at targets
Market Conditions:
- Best results in trending markets
- Reduce position size in choppy conditions
- Consider session overlaps for volatility
- Avoid trading near major news if inexperienced
Continuous Improvement:
- Track win rate by session
- Note which confluence factors work best
- Adjust settings based on market volatility
- Review performance weekly
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PERFORMANCE OPTIMIZATION
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This indicator is optimized with:
- max_bars_back declarations for efficient processing
- Conditional calculations based on enabled features
- Proper memory management for drawing objects
- Minimal recalculation on each bar
Best Practices:
- Disable unused features (sessions, MTF, volume)
- Limit historical display to reduce rendering
- Use appropriate timeframe for your strategy
- Clear old drawing objects periodically
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EDUCATIONAL DISCLAIMER
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This indicator combines established trading concepts:
- Opening Range Breakout theory (price action)
- Liquidity level detection (pivot analysis)
- Session-based trading (time-of-day patterns)
- Volume analysis (confirmation technique)
- Multi-timeframe analysis (trend alignment)
All calculations use standard technical analysis methods:
- Pivot high/low detection algorithms
- Moving averages for trend and volume
- Session time filtering
- Timeframe security functions
The indicator identifies potential trading setups but does not predict future price movements. Success requires proper application within a complete trading strategy including risk management, position sizing, and market context.
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USAGE DISCLAIMER
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This tool is for educational and analytical purposes. Opening Range Breakout trading involves substantial risk. The alert system and quality filters are designed to identify potential setups but do not guarantee profitability. Always conduct independent analysis, use proper risk management, and never risk capital you cannot afford to lose. Past performance does not indicate future results. Trading intraday breakouts requires experience and discipline.
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CREDITS & ATTRIBUTION
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ORIGINAL SOURCE:
This indicator builds upon concepts from LuxAlgo's-ORB
Moving Average Trend Strategy V4.1 — Revised Version (Selectable✅ **Version Notes (V4.0)**
| Feature | Description |
| --------------------------------------- | -------------------------------------------------------- |
| 🧠 **Moving Average Type Options** | Choose from EMA / SMA / HMA / WMA |
| 🧱 **Take-Profit / Stop-Loss Switches** | Can be enabled or disabled independently |
| ⚙️ **Add Position Function** | Can be enabled or disabled independently |
| 🔁 **Add Position Signal Source** | Selectable between MA Crossover / MACD / RCI / RSI |
| 💹 **Adjustable Parameters** | All periods and percentages are customizable in settings |
---
✅ **Update Summary:**
| Function | Description |
| -------------------------------------- | --------------------------------------------------------------------- |
| **MA Type Selection** | Choose EMA / SMA / HMA / WMA in chart settings |
| **Take-Profit / Stop-Loss Percentage** | Configurable in the “Take-Profit & Stop-Loss” group |
| **Add / Reduce Position Percentage** | Adjustable separately in the “Add/Reduce Position” group |
| **MA Periods** | Customizable in the “Moving Average Parameters” section |
| **Code Structure** | Logic unchanged — only parameterization and selection functions added |
---
### **Strategy Recommendations:**
* **Trending Market:** Prefer EMA trend tracking or SAR indicators
* **Range-Bound Market:** Use ATR-based volatility stop-loss
* **Before Major Events:** Consider option hedging
* **Algorithmic Trading:** Recommend ATR + partial take-profit combination strategy
---
### **Key Parameter Optimization Logic:**
* Backtest different **ATR multipliers** (2–3× ATR)
* Test **EMA periods** (10–50 periods)
* Optimize **partial take-profit ratios**
* Adjust **maximum drawdown tolerance** (typically 30–50% of profit)
---
### **Risk Control Tips:**
* Avoid overly tight stop-losses that trigger too frequently
* During strong trends, consider widening take-profit targets
* Confirm trend continuation with **volume analysis**
* Adjust parameters based on **timeframe** (e.g., Daily vs Hourly)
---
### **Practical Example (Forex: EUR/USD):**
* **Entry:** Go long on breakout above 1.1200
* **Initial Stop-Loss:** 1.1150 (50 pips)
* **When profit reaches 1.1300:**
* Close 50% of position
* Move stop-loss to 1.1250 (lock in 50 pips profit)
* **When price rises to 1.1350:**
* Move stop-loss to 1.1300 (lock in 100 pips profit)
* **Final Outcome:**
* Price retraces to 1.1300, triggering take-profit
This method secured over **80% of trend profits** during the 2023 EUR rebound, capturing **23% more profit** compared to fixed take-profit strategies (based on backtest results).
Ekoparaloji Cyrpto StrategyEkoparaloji Crypto Strategy - User Information Document
📊 Strategy Overview
This strategy provides long-term position management in cryptocurrency markets using the averaging down (pyramiding) technique. The basic logic is to controllably grow positions as prices decline and exit when specific profit targets are reached.
🎯 Key Features
✅ Automatic Entry System
Market direction is determined using a proprietary trend identification algorithm
Trades are only opened in uptrends
Initial position opens automatically when specific conditions are met
📈 Pyramiding Mechanism
New positions are automatically added as price decreases
Up to 10 positions can be added maximum
Each addition occurs at predetermined decline levels
Risk management through dynamic position sizing
💰 Profit and Loss Management
Take Profit: All positions close when the specified percentage above average cost is reached
Stop Loss (Optional): Protects a specified percentage of total capital
A certain ratio of available capital is used in each trade
📊 Visual Tracking System
The following information is displayed in real-time on the chart:
✅ Average cost level
✅ Profit target level
✅ Stop loss level (if active)
✅ Next pyramiding level
✅ Liquidation (capital reset) level
✅ Trend indicator
🛡️ Risk Management Features
1. Dynamic Capital Protection
Automatic exit when losses exceed a specified percentage of total capital
Complete loss scenario can be previewed through liquidation level calculation
2. Position Control System
Protection preventing multiple trades on the same bar
Double trigger prevention mechanism
Maximum position limit
3. Time Filter
Optional trading within a date range
Ideal for testing on historical data
📱 Information Panel
Information table always visible in the upper right corner of the strategy:
When Position is Open:
Number of active positions
Average cost
Current price
Total capital status
Capital loss percentage
Profit target
Stop loss level and distance
Next entry level
Liquidation level and distance
When No Position:
Market trend (Uptrend/Downtrend)
Ready to trade?
Reason for waiting
Initial position size
Target profit percentage
⚙️ Adjustable Parameters
Customizable by user:
💵 Capital Amount: Base amount to be used for each position
📊 Profit Target: Profit percentage at which to exit
🛑 Stop Loss: Usage status and maximum loss percentage
📅 Time Filter: Start and end dates for testing
💬 Trade Comments: Custom labels for each trade
📘 Understanding Leverage Effect
1. What is the Leverage Effect?
Although there's no real leverage in the spot market, when Capital Amount is increased, capital usage works like leverage:
Capital Amount 5% (1.0x): 100% capital usage with full pyramiding = All your money in trades
Capital Amount 10% (2.0x): 200% capital usage with full pyramiding = Attempting to open trades worth 2x your capital
Capital Amount 15% (3.0x): 300% capital usage with full pyramiding = Attempting to open trades worth 3x your capital
⚠️ IMPORTANT: If your capital runs out in the spot market, you cannot open new positions, therefore it's recommended to keep Capital Amount at 5% or below!
⚠️ Important Warnings
Pyramiding Risk: If price continues to decline, position grows and risk increases
Capital Requirements: Up to 10 positions can be added, requiring sufficient capital
Trend Dependency: Only works in uptrends
Backtest Results: Past performance is not a guarantee of future results
Real Trading Risks: Slippage, commissions, and market conditions can affect results
🎓 How to Use
Add the strategy to your chart
Adjust parameters according to your risk appetite
Examine past performance by backtesting
Optionally set up alerts to activate notifications
Test with paper trading first
This strategy is for educational purposes. Do your own research and only trade with capital you can afford to lose.
Disclaimer: This strategy is not financial advice. All investment decisions are the user's responsibility.
Happy trading! 📊
Ekoparaloji Strategy Crypto Ekoparaloji Crypto Strategy - User Information Document
📊 Strategy Overview
This strategy provides long-term position management in cryptocurrency markets using the averaging down (pyramiding) technique. The basic logic is to controllably grow positions as prices decline and exit when specific profit targets are reached.
🎯 Key Features
✅ Automatic Entry System
Market direction is determined using a proprietary trend identification algorithm
Trades are only opened in uptrends
Initial position opens automatically when specific conditions are met
📈 Pyramiding Mechanism
New positions are automatically added as price decreases
Up to 10 positions can be added maximum
Each addition occurs at predetermined decline levels
Risk management through dynamic position sizing
💰 Profit and Loss Management
Take Profit: All positions close when the specified percentage above average cost is reached
Stop Loss (Optional): Protects a specified percentage of total capital
A certain ratio of available capital is used in each trade
📊 Visual Tracking System
The following information is displayed in real-time on the chart:
✅ Average cost level
✅ Profit target level
✅ Stop loss level (if active)
✅ Next pyramiding level
✅ Liquidation (capital reset) level
✅ Trend indicator
🛡️ Risk Management Features
1. Dynamic Capital Protection
Automatic exit when losses exceed a specified percentage of total capital
Complete loss scenario can be previewed through liquidation level calculation
2. Position Control System
Protection preventing multiple trades on the same bar
Double trigger prevention mechanism
Maximum position limit
3. Time Filter
Optional trading within a date range
Ideal for testing on historical data
📱 Information Panel
Information table always visible in the upper right corner of the strategy:
When Position is Open:
Number of active positions
Average cost
Current price
Total capital status
Capital loss percentage
Profit target
Stop loss level and distance
Next entry level
Liquidation level and distance
When No Position:
Market trend (Uptrend/Downtrend)
Ready to trade?
Reason for waiting
Initial position size
Target profit percentage
⚙️ Adjustable Parameters
Customizable by user:
💵 Capital Amount: Base amount to be used for each position
📊 Profit Target: Profit percentage at which to exit
🛑 Stop Loss: Usage status and maximum loss percentage
📅 Time Filter: Start and end dates for testing
💬 Trade Comments: Custom labels for each trade
📘 Understanding Leverage Effect
1. What is the Leverage Effect?
Although there's no real leverage in the spot market, when Capital Amount is increased, capital usage works like leverage:
Capital Amount 5% (1.0x): 100% capital usage with full pyramiding = All your money in trades
Capital Amount 10% (2.0x): 200% capital usage with full pyramiding = Attempting to open trades worth 2x your capital
Capital Amount 15% (3.0x): 300% capital usage with full pyramiding = Attempting to open trades worth 3x your capital
⚠️ IMPORTANT: If your capital runs out in the spot market, you cannot open new positions, therefore it's recommended to keep Capital Amount at 5% or below!
⚠️ Important Warnings
Pyramiding Risk: If price continues to decline, position grows and risk increases
Capital Requirements: Up to 10 positions can be added, requiring sufficient capital
Trend Dependency: Only works in uptrends
Backtest Results: Past performance is not a guarantee of future results
Real Trading Risks: Slippage, commissions, and market conditions can affect results
🎓 How to Use
Add the strategy to your chart
Adjust parameters according to your risk appetite
Examine past performance by backtesting
Optionally set up alerts to activate notifications
Test with paper trading first
This strategy is for educational purposes. Do your own research and only trade with capital you can afford to lose.
Disclaimer: This strategy is not financial advice. All investment decisions are the user's responsibility.
FirstStrike Long 200 - Daily Trend Rider [KedArc Quant]Strategy Description
FirstStrike Long 200 is a disciplined, long-only momentum strategy designed for daily "strike-first" entries in trending markets. It scans for RSI momentum above a customizable trigger (default 50), confirmed by EMA trend filters, and limits you to *exactly one trade per day* to avoid overtrading. It uses ATR for dynamic risk management (1.5x stop, 2:1 RR target) and optional trailing stops to ride winners. Backtested with realistic commissions and sizing, it prioritizes low drawdowns (<1% max in tests) over aggressive gains—ideal for swing traders seeking quality setups in bull runs.
Why It's Different from Other Strategies
Unlike generic RSI crossover bots or EMA ribbon mashups that spam signals and bleed in chop, FirstStrike enforces a "one-and-done" daily gate, blending precision momentum (RSI modes with grace/sustain) with robust filters (volume, sessions, rearm dips).
How It Helps Traders
- Reduces Emotional Trading: One entry/day forces discipline—miss a setup? Wait for tomorrow. Perfect for busy pros avoiding screen fatigue.
- Adapts to Regimes: Switch modes for trends ("Cross+Grace") vs. ranges ("Any bar")—boosts win rates 5-10% in backtests on high-beta names like .
- Risk-First Design: ATR scales stops to vol capping DD at 0.2% while targeting 2R winners. Trailing option locks +3-5% runs without early exits.
- Quick Insights: Labels/alerts flag entries with RSI values; bgcolor highlights signals for visual scanning. Helps spot "first-strike" edges in uptrends, filtering ~60% noise.
Why This Is Not a Mashup
This isn't a Frankenstein of off-the-shelf indicators—while it uses standard RSI/EMA/ATR (core Pine primitives), the innovation lies in:
- Custom Trigger Engine: Switchable modes (e.g., "Cross+Grace+Sustain" requires post-cross hold) prevent perpetual signals, unlike basic `ta.crossover()`.
- Daily Rearm Gate: Resets eligibility only after a dip (if enabled), tying momentum to mean-reversion—original logic not found in common scripts.
- Per-Day Isolation: `var` vars + `ta.change(time("D"))` ensure zero pyramiding/overlaps, beyond simple session filters.
All formulae are derived in-house for "first-strike" (early RSI pops in trends), not copied from public repos.
Input Configurations
Let's break down every input in the FirstStrike Long 200 strategy. These settings let you tweak the strategy like a dashboard—start with defaults for quick testing,
then adjust based on your asset or timeframe (5m for intraday). They're grouped logically to keep things organized, and most have tooltips in the script for quick reminders.
RSI / Trigger Group: The Heart of Momentum Detection
This is where the magic starts—the strategy hunts for "upward energy" using RSI (Relative Strength Index), a tool that measures if a stock is overbought (too hot) or oversold (too cold) on a 0-100 scale.
- RSI Length: How many bars (candles) back to calculate RSI. Default is 14, like a 14-day window for daily charts. Shorter (e.g., 9) makes it snappier for fast markets; longer (21) smooths out noise but misses quick turns.
- Trigger Level (RSI >= this): The key RSI value where the strategy says, "Go time!" Default 50 means enter when RSI crosses or holds above the neutral midline. Why is this trigger required? It acts as your "green light" filter—without it, you'd enter on every tiny price wiggle, leading to endless losers. RSI above this shows building buyer power, avoiding weak or sideways moves. It's essential for quality over quantity, especially in one-trade-per-day setups.
- Trigger Mode: Picks how strict the RSI signal must be. Options: "Cross only" (exact RSI crossover above trigger—super precise, fewer trades); "Cross+Grace" (crossover or within a grace window after—gives a second chance); "Cross+Grace+Sustain" (crossover/grace plus RSI holding steady for bars—best for steady climbs); "Any bar >= trigger" (looser, any bar above—more opportunities but riskier in chop). Start with "Any bar" for trends, switch to "Cross only" for caution.
- Grace Window (bars after cross): If mode allows, how many bars post-RSI-cross you can still enter if RSI dips but recovers. Default 30 (about 2.5 hours on 5m). Zero means no wiggle room—pure precision.
- Sustain Bars (RSI >= trigger): In sustain mode, how many straight bars RSI must stay above trigger. Default 3 ensures it's not a fluke spike.
- Require RSI Dip Below Rearm Before Any Entry?: A yes/no toggle. If on, the strategy "rearms" only after RSI dips below a low level (like a breather), preventing back-to-back signals in overextended rallies.
- Rearm Level (if requireDip=true): The dip threshold for rearming. Default 45—RSI must go below this to reset eligibility. Lower (30) for deeper pullbacks in volatile stocks.
For the trigger level itself, presets matter a lot—default 50 is neutral and versatile for broad trends. Bump to 55-60 for "strong momentum only" (fewer but higher-win trades, great in bull runs like tech surges); drop to 40-45 for "early bird" catches in recoveries (more signals but watch for fakes in ranges). The optimize hint (40-60) lets you test these in TradingView to match your risk—higher presets cut noise by 20-30% in backtests.
Trend / Filters Group: Keeping You on the Right Side of the Market
These EMAs (Exponential Moving Averages) act like guardrails, ensuring you only long in uptrends.
- EMA (Fast) Confirmation: Short-term EMA for price action. Default 20 periods—price must be above this for "recent strength." Shorter (10) reacts faster to intraday pops.
- EMA (Trend Filter): Long-term EMA for big-picture trend. Default 200 (classic "above the 200-day" rule)—price above it confirms bull market. Minimum 50 to avoid over-smoothing.
Optional Hour Window Group: Timing Your Strikes
Avoid bad hours like lunch lulls or after-hours tricks.
- Restrict by Session?: Yes/no for using exact market hours. Default off.
- Session (e.g., 0930-1600 for NYSE): Time string like "0930-1600" for open to close. Auto-skips pre/post-market noise.
- Restrict by Hour Range?: Fallback yes/no for simple hours. Default off.
- Start Hour / End Hour: Clock times (0-23). Defaults 9-15 ET—focus on peak volume.
Volume Filter Group: No Volume, No Party
Confirms conviction—big moves need big participation.
- Require Volume > SMA?: Yes/no toggle. Default off—only fires on above-average volume.
- Volume SMA Length: Periods for the average. Default 20—compares current bar to recent norm.
Risk / Exits Group: Protecting and Profiting Smartly
Dynamic stops based on volatility (ATR = Average True Range) keep things realistic.
- ATR Length: Bars for ATR calc. Default 14—measures recent "wiggle room" in price.
- ATR Stop Multiplier: How far below entry for stop-loss. Default 1.5x ATR—gives breathing space without huge risk
- Take-Profit R Multiple: Reward target as multiple of risk. Default 2.0 (2:1 ratio)—aims for twice your stop distance.
- Use Trailing Stop?: Yes/no for profit-locking trail. Default off—activates after entry.
- Trailing ATR Multiplier: Trail distance. Default 2.0x ATR—looser than initial stop to let winners run.
These inputs make the strategy plug-and-play: Defaults work out-of-box for trending stocks, but tweak RSI trigger/modes first for your style.
Always backtest changes—small shifts can flip a 40% win rate to 50%+!
Outputs (Visuals & Alerts):
- Plots: Blue EMA200 (trend line), Orange EMA20 (price filter), Green dashed entry price.
- Labels: Green "LONG" arrow with RSI value on entries.
- Background: Light green highlight on signal bars.
- Alerts: "FirstStrike Long Entry" fires on conditions (integrates with TradingView notifications).
Entry-Exit Logic
Entry (Long Only, One Per Day):
1. Daily Reset: New day clears trade gate and (if required) rearm status.
2. Filters Pass: Time/session OK + Close > EMA200 (trend) + Close > EMA20 (price) + Volume > SMA (if enabled) + Rearmed (dip below rearm if toggled).
3. Trigger Fires: RSI >= trigger via selected mode (e.g., crossover + grace window).
4. Execute: Enter long at close; set daily flag to block repeats.
Exit:
- Stop-Loss: Entry - (ATR * 1.5) – dynamic, vol-scaled.
- Take-Profit: Entry + (Risk * 2.0) – fixed RR.
- Trailing (Optional): Activates post-entry; trails at Close - (ATR * 2.0), updating on each bar for trend extension.
No shorts or hedging—pure long bias.
Formulae Used
- RSI: `ta.rsi(close, rsiLen)` – Standard 14-period momentum oscillator (0-100).
- EMAs: `ta.ema(close, len)` – Exponential moving averages for trend/price filters.
- ATR: `ta.atr(atrLen)` – True range average for stop sizing: Stop = Entry - (ATR * mult).
- Volume SMA: `ta.sma(volume, volLen)` – Simple average for relative strength filter.
- Grace Window: `bar_index - lastCrossBarIndex <= graceBars` – Counts bars since RSI crossover.
- Sustain: `ta.barssince(rsi < trigger) >= sustainBars` – Consecutive bars above threshold.
- Session Check: `time(timeframe.period, sessionStr) != 0` – TradingView's built-in session validator.
- Risk Distance: `riskPS = entry - stop; TP = entry + (riskPS * RR)` – Asymmetric reward calc.
FAQ
Q: Why only one trade/day?
A: Prevents revenge trading in volatile sessions . Backtests show it cuts losers by 20-30% vs. multi-entry bots.
Q: Does it work on all assets/timeframes?
A: Best for trending stocks/indices on 5m-1H. Test on crypto/forex with wider ATR mult (2.0+).
Q: How to optimize?
A: Use TradingView's optimizer on RSI trigger (40-60) and EMA fast (10-30). Aim for PF >1.0 over 1Y data.
Q: Alerts don't fire—why?
A: Ensure `alertcondition` is enabled in script settings. Test with "Any alert() function calls only."
Q: Trailing stop too loose?
A: Tune `trailMult` to 1.5 for tighter; it activates alongside fixed TP/SL for hybrid protection.
Glossary
- Grace Window: Post-RSI-cross period (bars) where entry still allowed if RSI holds trigger.
- Rearm Dip: Optional pullback below a low RSI level (e.g., 45) to "reset" eligibility after signals.
- Profit Factor (PF): Gross profit / gross loss—>1.0 means winners outweigh losers.
- R Multiple: Risk units (e.g., 2R = 2x stop distance as target).
- Sustain Bars: Consecutive bars RSI stays >= trigger for mode confirmation.
Recommendations
- Backtest First: Run on your symbols (/) over 6-12M; tweak RSI to 55 for +5% win rate.
- Live Use: Start paper trading with `useSession=true` and `useVol=true` to filter noise.
- Pairs Well With: Higher TF (daily) for bias; add ADX (>25) filter for strong trends (code snippet in prior chats).
- Risk Note: 10% sizing suits $100k+ accounts; scale down for smaller. Not financial advice—past performance ≠ future.
- Publish Tip: Add tags like "momentum," "RSI," "long-only" on TradingView for visibility.
Strategy Properties & Backtesting Setup
FirstStrike Long 200 is configured with conservative, realistic backtesting parameters to ensure reliable performance simulations. These settings prioritize capital preservation and transparency, making it suitable for both novice and experienced traders testing on stocks.
Initial Capital
$100,000 Standard starting equity for portfolio-level testing; scales well for retail accounts. Adjust lower (e.g., $10k) for smaller simulations.
Base Currency
Default (USD) Aligns with most US equities (e.g., NASDAQ symbols); auto-converts for other assets.
Order Size
1 (Quantity) Fixed share contracts for simplicity—e.g., buys 1 share per trade. For % of equity, switch to "Percent of Equity" in strategy code.
Pyramiding
0 Orders No additional entries on open positions; enforces strict one-trade-per-day discipline to avoid overexposure.
Commission
0.1% Realistic broker fee (e.g., Interactive Brokers tier); factors in round-trip costs without over-penalizing winners.
Verify Price for Limit Orders
0 Ticks No slippage delay on TPs—assumes ideal fills for historical accuracy.
Slippage
0 Ticks Zero assumed slippage for clean backtests; real-world trading may add 1-2 ticks on volatile opens.
These defaults yield low drawdowns (<0.3% max in tests) while capturing trend edges. For live trading, enable slippage (1-3 ticks) to mimic execution gaps. Always forward-test before deploying!
⚠️ Disclaimer
This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
Signalgo VSignalgo V: Technical Overview and Unique Aspects
Signalgo V is a technical indicator for TradingView that integrates multiple layers of analysis: moving averages, MACD, Bollinger Bands and RSI to deliver buy and sell signals. Below is an informational breakdown of how the indicator functions, its input parameters, signal logic, exit methodology, and how it stands apart from traditional moving average (MA) tools, without disclosing specifics that allow for code duplication.
How Signalgo V Works
1. Multi-Layered Technical Synthesis
Signalgo V processes several technical studies simultaneously:
Fast/Slow Moving Averages: Uses either EMA or SMA (user-selected) with adjustable periods. These are central to initial trend detection through crossovers.
MACD Filter: MACD line vs. signal line cross-check ensures trend direction is supported by both momentum and MA structure.
RSI Confirmation: The RSI is monitored to verify that signals are not excessively overbought or oversold, tuning the system to changing momentum regimes.
Bollinger Bands Context: Entry signals are only considered when price action is beyond the Bollinger Bands envelope, which further filters for unusually strong movements.
These strict, multi-indicator entry criteria are designed to ensure only the most robust signals are surfaced, each is contingent on the presence of aligned trend, momentum and volatility.
2. Exit Methodology
Take-Profit Levels: After entering a trade, the strategy automatically sets three predefined profit targets (TP1, TP2, TP3). If the price reaches any of these targets, the system marks it, helping you lock in profits at different stages.
Stop-Loss System: Simultaneously, a stop-loss (SL) value is set, protecting you from significant losses if the market moves against your position.
Dynamic Adjustment: When the first profit target (TP1) is hit, the system can automatically move the stop-loss to your entry price. This means your worst-case outcome is break-even from that point, reducing downside risk.
Trailing Stop-Loss: After TP1 is reached, a dynamic trailing stop can activate. This allows the stop-loss to follow the price as it moves in your favor, aiming to capture more profit if the trend continues, while still protecting your gains if the price reverses.
Visual Markers: The system plots all important exit levels (profit targets, stop-loss, trailing stop) directly on the chart. Optional labels also appear whenever a target or stop-loss is hit, making it easy to see progress.
Visual cues (labels) are plotted directly on the bar where a buy or sell signal triggers, clarifying entry points and aiding manual exit/risk management decisions.
Input Parameters
rsiLen: Lookback period for RSI calculation.
rsiOB and rsiOS: Overbought/oversold thresholds, adaptive to the indicator’s multi-layered logic.
maFastLen and maSlowLen: Periods for fast and slow MAs.
maType: EMA or SMA selectable for both MAs.
bbLen: Length for Bollinger Bands mean calculation.
bbMult: Standard deviation multiplier for BB width.
macdFast, macdSlow, macdSig: Standard MACD parameterization for nuanced momentum oversight.
What Separates Signalgo V from Traditional Moving Average Indicators
Composite Signal Architecture: Where traditional MA systems generate signals solely on MA crossovers, Signalgo V requires layered, cross-confirmational logic across trend (MAs), momentum (MACD), volatility (Bollinger Bands), and market strength (RSI).
Adaptive Volatility Context: MA signals only “count” when price is meaningfully breaking out of its volatility envelope, filtering out most unremarkable crosses that plague basic MA strategies.
Integrated Multi-Factor Filters: Strict compliance with all layers of signal logic is enforced. A marked improvement over MA strategies that lack secondary or tertiary confirmation.
Non-Redundant Event Limiting: Each entry is labeled as a unique event. The indicator does not repeat signals on subsequent bars unless all entry conditions are freshly met.
Trading Strategy Application
Trend Identification: By requiring concurrence among MA, MACD, RSI, and BB, this tool identifies only those trends with robust, multifactor support.
Breakout and Momentum Entry: Signals are bias-toward trades that initiate at likely breakout points (outside BB range), combined with fresh momentum and trend alignment.
Manual Discretion for Exits: The design is to empower traders with high-confidence entries and leave risk management or partial profit-taking adaptive to trader style, using visual cues from all component indicators.
Alert Generation: Each buy/sell event optionally triggers an alert, supporting systematic monitoring without constant chart watching.
AltCoin & MemeCoin Index Correlation [Eddie_Bitcoin]🧠 Philosophy of the Strategy
The AltCoin & MemeCoin Index Correlation Strategy by Eddie_Bitcoin is a carefully engineered trend-following system built specifically for the highly volatile and sentiment-driven world of altcoins and memecoins.
This strategy recognizes that crypto markets—especially niche sectors like memecoins—are not only influenced by individual price action but also by the relative strength or weakness of their broader sector. Hence, it attempts to improve the reliability of trading signals by requiring alignment between a specific coin’s trend and its sector-wide index trend.
Rather than treating each crypto asset in isolation, this strategy dynamically incorporates real-time dominance metrics from custom indices (OTHERS.D and MEME.D) and combines them with local price action through dual exponential moving average (EMA) crossovers. Only when both the asset and its sector are moving in the same direction does it allow for trade entries—making it a confluence-based system rather than a single-signal strategy.
It supports risk-aware capital allocation, partial exits, configurable stop loss and take profit levels, and a scalable equity-compounding model.
✅ Why did I choose OTHERS.D and MEME.D as reference indices?
I selected OTHERS.D and MEME.D because they offer a sector-focused view of crypto market dynamics, especially relevant when trading altcoins and memecoins.
🔹 OTHERS.D tracks the market dominance of all cryptocurrencies outside the top 10 by market cap.
This excludes not only BTC and ETH, but also major stablecoins like USDT and USDC, making it a cleaner indicator of risk appetite across true altcoins.
🔹 This is particularly useful for detecting "Altcoin Season"—periods where capital rotates away from Bitcoin and flows into smaller-cap coins.
A rising OTHERS.D often signals the start of broader altcoin rallies.
🔹 MEME.D, on the other hand, captures the speculative behavior of memecoin segments, which are often driven by retail hype and social media activity.
It's perfect for timing momentum shifts in high-risk, high-reward tokens.
By using these indices, the strategy aligns entries with broader sector trends, filtering out noise and increasing the probability of catching true directional moves, especially in phases of capital rotation and altcoin risk-on behavior.
📐 How It Works — Core Logic and Execution Model
At its heart, this strategy employs dual EMA crossover detection—one pair for the asset being traded and one pair for the selected market index.
A trade is only executed when both EMA crossovers agree on the direction. For example:
Long Entry: Coin's fast EMA > slow EMA and Index's fast EMA > slow EMA
Short Entry: Coin's fast EMA < slow EMA and Index's fast EMA < slow EMA
You can disable the index filter and trade solely based on the asset’s trend just to make a comparison and see if improves a classic EMA crossover strategy.
Additionally, the strategy includes:
- Adaptive position sizing, based on fixed capital or current equity (compound mode)
- Take Profit and Stop Loss in percentage terms
- Smart partial exits when trend momentum fades
- Date filtering for precise backtesting over specific timeframes
- Real-time performance stats, equity tracking, and visual cues on chart
⚙️ Parameters & Customization
🔁 EMA Settings
Each EMA pair is customizable:
Coin Fast EMA: Default = 47
Coin Slow EMA: Default = 50
Index Fast EMA: Default = 47
Index Slow EMA: Default = 50
These control the sensitivity of the trend detection. A wider spread gives smoother, slower entries; a narrower spread makes it more responsive.
🧭 Index Reference
The correlation mechanism uses CryptoCap sector dominance indexes:
OTHERS.D: Dominance of all coins EXCLUDING Top 10 ones
MEME.D: Dominance of all Meme coins
These are dynamically calculated using:
OTHERS_D = OTHERS_cap / TOTAL_cap * 100
MEME_D = MEME_cap / TOTAL_cap * 100
You can select:
Reference Index: OTHERS.D or MEME.D
Or disable the index reference completely (Don't Use Index Reference)
💰 Position Sizing & Risk Management
Two capital allocation models are supported:
- Fixed % of initial capital (default)
- Compound profits, which scales positions as equity grows
Settings:
- Compound profits?: true/false
- % of equity: Between 1% and 200% (default = 10%)
This is critical for users who want to balance growth with risk.
🎯 Take Profit / Stop Loss
Customizable thresholds determine automatic exits:
- TakeProfit: Default = 99999 (disabled)
- StopLoss: Default = 5 (%)
These exits are percentage-based and operate off the entry price vs. current close.
📉 Trend Weakening Exit (Scale Out)
If the position is in profit but the trend weakens (e.g., EMA color signals trend loss), the strategy can partially close a configurable portion of the position:
- Scale Position on Weak Trend?: true/false
- Scaled Percentage: % to close (default = 65%)
This feature is useful for preserving profits without exiting completely.
📆 Date Filter
Useful for segmenting performance over specific timeframes (e.g., bull vs bear markets):
- Filter Date Range of Backtest: ON/OFF
- Start Date and End Date: Custom time range
OTHER PARAMETERS EXPLANATION (Strategy "Properties" Tab):
- Initial Capital is set to 100 USD
- Commission is set to 0.055% (The ones I have on Bybit)
- Slippage is set to 3 ticks
- Margin (short and long) are set to 0.001% to avoid "overspending" your initial capital allocation
📊 Visual Feedback and Debug Tools
📈 EMA Trend Visualization
The slow EMA line is dynamically color-coded to visually display the alignment between the asset trend and the index trend:
Lime: Coin and index both bullish
Teal: Only coin bullish
Maroon: Only index bullish
Red: Both bearish
This allows for immediate visual confirmation of current trend strength.
💬 Real-Time PnL Labels
When a trade closes, a label shows:
Previous trade return in % (first value is the effective PL)
Green background for profit, Red for losses.
📑 Summary Table Overlay
This table appears in a corner of the chart (user-defined) and shows live performance data including:
Trade direction (yellow long, purple short)
Emojis: 💚 for current profit, 😡 for current loss
Total number of trades
Win rate
Max drawdown
Duration in days
Current trade profit/loss (absolute and %)
Cumulative PnL (absolute and %)
APR (Annualized Percentage Return)
Each metric is color-coded:
Green for strong results
Yellow/orange for average
Red/maroon for poor performance
You can select where this appears:
Top Left
Top Right
Bottom Left
Bottom Right (default)
📚 Interpretation of Key Metrics
Equity Multiplier: How many times initial capital has grown (e.g., “1.75x”)
Net Profit: Total gains including open positions
Max Drawdown: Largest peak-to-valley drop in strategy equity
APR: Annualized return calculated based on equity growth and days elapsed
Win Rate: % of profitable trades
PnL %: Percentage profit on the most recent trade
🧠 Advanced Logic & Safety Features
🛑 “Don’t Re-Enter” Filter
If a trade is closed due to StopLoss without a confirmed reversal, the strategy avoids re-entering in that same direction until conditions improve. This prevents false reversals and repetitive losses in sideways markets.
🧷 Equity Protection
No new trades are initiated if equity falls below initial_capital / 30. This avoids overleveraging or continuing to trade when capital preservation is critical.
Keep in mind that past results in no way guarantee future performance.
Eddie Bitcoin
- Trading Bot – Dynamic RSI (Professional) - Robot Strategy -1. General Concept and Philosophy
This strategy was designed for systematic traders and work especially well on short timeframes (1 to 5 minutes), who seek to capture trend reversal movements with a high degree of confirmation. The goal is not to follow the trend, but to identify precise entry points in oversold or overbought zones, and then to exit the position dynamically to adapt to changing market conditions.
The originality of Trading Bot Dynamic RSI lies not in a single indicator, but in the intelligent fusion of several concepts:
Dynamic RSI bands for both entries and exits .
A triple confirmation filter to secure trade entries.
A fully parameterizable design ready for automation .
2. Originality at the Core of the Strategy: Key Features
Dynamic Exits on RSI Bands: This is a main original feature of this script. Unlike traditional strategies that use fixed Take-Profits and Stop-Losses, this one uses an exit RSI band, calculated with parameters independent of the entry ones. This allows the strategy to:
Adapt to Volatility: In a volatile market, the exit band will move further away, allowing for the capture of larger moves. In a ranging market, it will tighten to secure smaller gains.
Optimize Profits: The exit occurs when momentum genuinely fades, not at an arbitrary price level, thus maximizing the potential of each trade.
Triple Confirmation Filter for Precise Entries: To avoid false signals, each entry is validated by the convergence of three distinct conditions:
The base signal is generated when the price reaches an overbought or oversold zone, materialized by an RSI band calculated directly on the chart.
The WaveTrend oscillator must also be in an extreme zone, confirming that the short-term momentum is ready for a reversal.
Finally, the StochRSI must validate that the RSI itself is in an overbought or oversold condition, adding an extra layer of security.
"Automation Ready" Design: The strategy was developed with automation in mind.
Customizable Alert Messages: All messages for entries and exits (Long/Short) can be formatted to be compatible with automated trade execution platforms.
Precise Capital Management: The position size calculation can be set as a fixed amount (e.g., 100 USDT), a percentage of the total capital, or of the available capital, and includes leverage. These parameters are crucial for a trading bot.
3. Detailed Operation
Entry Logic: A position is opened only if the following three conditions are met:
The market price touches (or closes below/above) the entry RSI band (lower for a buy, upper for a sell).
The WaveTrend indicator is in the oversold zone (for a buy) or overbought zone (for a sell).
The Stochastic RSI indicator is also in the oversold zone (for a buy) or overbought zone (for a sell).
The order is placed as a limit order on the RSI band, allowing for execution at the best possible price.
Exit Logic: The primary exit is dynamic.
For a Long position, the trade is closed when the price reaches the upper exit RSI band.
For a Short position, the trade is closed when the price reaches the lower exit RSI band.
Optionally, a percentage-based Stop-Loss and Take-Profit can be activated for more traditional risk management, although the dynamic exit is the recommended default mechanism.
4. Ease of Use and Customization
Despite its internal complexity, the strategy is designed to be user-friendly :
Clear Settings Panel: Parameters are grouped by function (Long Entry, Long Exit, Quantity, etc.), and each option comes with an explanatory tooltip.
Integrated Display: All key information (performance, current settings) is displayed in clean and discreet tables directly on the chart, allowing you to see at a glance how the strategy is configured.
Total Flexibility: Although default settings are provided, every parameter (RSI lengths, levels, filters) can be adjusted to optimize the strategy on any asset (cryptocurrencies, Forex, indices...) and any timeframe.
5. Detailed Guide to User Settings
A comprehensive set of parameters
To offer you complete control and maximum flexibility, the strategy exposes a comprehensive set of parameters. Here is an overview of what you can customize:
Trading Mode and Display
Trading Mode: Choose to enable only long positions ("Long Only"), only short positions ("Short Only"), or both simultaneously ("Long and Short").
Display: Manage the information panels on the chart. You can opt for a full display, a minimal window showing the profit, or hide all information for a clean chart.
Filters Smoothing (StochRSI K)
Filters Smoothing: This key parameter adjusts the smoothing of the Stochastic RSI. A lower value will make the filter more responsive, generating more signals. A higher value will make it smoother, generating fewer but potentially more reliable signals.
LONG Position Settings
Long Only mode
Entry: Define the RSI length and Oversold level that draw the lower band for long position entries.
Exit: Independently configure the RSI length and Overbought level that draw the upper band for the dynamic position exit.
Options: Optionally enable a percentage-based Take-Profit and/or Stop-Loss.
SHORT Position Settings
Short Only Mode
Entry: Define the RSI length and Overbought level for the upper entry band for short positions.
Exit: Independently configure the RSI length and Oversold level for the lower dynamic exit band.
Options: Just like for long positions, you can enable a percentage-based Take-Profit and/or Stop-Loss.
Quantity and Leverage
Quantity Type: Calculate your position size in three ways: as a fixed cash amount, as a percentage of available capital, or as a percentage of the total account balance.
Amount: Specify the dollar amount or percentage to commit per trade.
Leverage: Set the leverage to be applied. This is crucial for automation.
Backtest Period
Backtest Period: Enable this option to limit the strategy's calculations to a specific time period. This is a powerful tool for testing performance under particular market conditions.
Bot Alert Messages
Bot Alert Messages: This section is dedicated to automation. Customize the exact text messages that will be sent by TradingView alerts for each event (enter long, exit long, etc.).
Other Settings (Advanced - Optional)
Other Settings: This section allows experienced users to fine-tune the confirmation engine. You can adjust the parameters of the WaveTrend and Stochastic RSI oscillators in detail.
Spread Calculator (Informative Only)
Spread Calculator: This handy tool helps you estimate the actual fees of your exchange to run a much more realistic backtest. This panel has no impact on the trading logic itself.
Disclaimer
This strategy provides signals based on past market conditions. Past performance is not indicative of future results. Trading involves risk, and it is the responsibility of each user to manage their risk appropriately. It is strongly recommended to conduct thorough backtests and to understand the functioning of each parameter before using this strategy in live conditions or automating it. Take into account transaction fees, spread, and slippage, which can impact real results.
EMA ZONE MASTER [By TraderMan]🟢 EMA Zone Master Indicator Explanation 🚀
🌟 What is the EMA Zone Master?
The EMA Zone Master is a powerful TradingView Pine Script indicator designed to help traders identify trends, entry points, and manage trades with precision. It leverages a 200-period EMA (Exponential Moving Average) to create a dynamic zone for spotting bullish 📈 and bearish 📉 trends. The indicator provides clear buy/sell signals, take-profit (TP) levels, and stop-loss (SL) levels, making it ideal for both novice and experienced traders! 💪
🔍 How Does It Work?
The indicator uses the 200-period EMA as its core, surrounded by a zone defined by a percentage offset (default 0.3%). Here's how it operates:
Trend Detection 🧠:
The price's position relative to the EMA zone determines the trend:
Above the zone (with tolerance and minimum distance) signals a bullish trend (BUY 📈).
Below the zone signals a bearish trend (SELL 📉).
A neutral trend occurs when the price is within the zone or lacks momentum.
A trend is confirmed after a set number of bars (default 3) to filter out noise. 🔎
Trade Signals 🚦:
Buy Signal: Triggered when the price breaks above the EMA zone with confirmation.
Sell Signal: Triggered when the price breaks below the EMA zone with confirmation.
Signals are visualized with labels ("BUY" or "SELL") on the chart for clarity. ✅
Position Management 🎯:
Entry Price: Set at the closing price when a signal is triggered.
Take-Profit Levels: Three TP levels (TP1, TP2, TP3) are calculated based on a Risk/Reward Ratio (default 0.7).
Stop-Loss: Calculated using the ATR (Average True Range) with a multiplier (default 6.0) for volatility-based protection. 🛡️
Lines and labels for entry, TP, and SL are drawn on the chart for easy tracking.
Trend Strength 💪:
The indicator calculates trend strength (0-100%) and categorizes it as Very Strong, Strong, Moderate, Weak, or Very Weak. This helps gauge the reliability of the trend. 🌡
Analysis Comment 📝:
A dynamic comment provides professional insights based on trend strength, guiding traders on whether to act or wait. 🧑💼
Visuals & Alerts 🔔:
The EMA, zone boundaries, and candlestick colors change based on the trend (green for bullish, red for bearish, gray for neutral).
A table in the top-right corner summarizes key data: trend direction, strength, entry price, TP/SL levels, and success rate.
Alerts are generated with detailed trade information when a new signal appears.
🛠 How to Use It?
Setup on TradingView ⚙️:
Add the EMA Zone Master to your chart via the TradingView Pine Script editor.
Customize settings like EMA Length (default 200), Zone Width (0.3%), ATR Period (50), and Risk/Reward Ratio (0.7) to suit your trading style. 🛠
Interpreting Signals 📊:
Buy Signal (AL): Look for a "BUY" label and green candlesticks when the price breaks above the EMA zone. 📈
Sell Signal (SAT): Look for a "SELL" label and red candlesticks when the price breaks below the EMA zone. 📉
Check the table for trend strength and analysis comments to confirm the signal's reliability.
Opening a Position 💸:
Long Position: Enter a buy trade when a "BUY" signal appears. Set your take-profit at TP1, TP2, or TP3 and stop-loss at the SL level shown on the chart.
Short Position: Enter a sell trade when a "SELL" signal appears. Use the TP and SL levels provided.
The indicator automatically plots these levels as lines and labels for easy reference. 🎯
Managing Trades 🕒:
Monitor the trade's progress via the table and labels.
The indicator tracks if TP1, TP2, or TP3 is hit or if the trade stops out, updating the Last Result in the table (e.g., "✅ TP1 SUCCESS" or "❌ STOPPED OUT").
Use the Success Rate (displayed in the table) to gauge historical performance (75% for BUY, 65% for SELL, 50% for NEUTRAL).
Using Alerts 🔔:
Set up alerts in TradingView to receive notifications when a buy or sell signal is triggered.
The alert message includes the trend, strength, entry price, TP/SL levels, success rate, and analysis comment for quick decision-making.
📈 How to Open a Position?
Wait for a Signal: Ensure a "BUY" or "SELL" label appears, and the trend strength is at least Moderate (40%+) for higher confidence. ✅
Check the Table: Review the trend direction, strength, and analysis comment to confirm the trade setup. 📊
Enter the Trade:
For a Buy: Enter at the entry price shown, set TP1/TP2/TP3 and SL as indicated by the lines/labels.
For a Sell: Same process, but for a short position.
Monitor: Watch for TP or SL hits. The indicator will update the table with the result (e.g., "✅ TP3 SUCCESS"). 🕒
Risk Management: Always adhere to the stop-loss level to limit losses, and consider partial profit-taking at TP1 or TP2 for safer trading. 🛡️
🎉 Why Use EMA Zone Master?
Clear Signals: Easy-to-read buy/sell signals with visual cues. 🚦
Automated Levels: Pre-calculated TP and SL levels save time and reduce errors. 🧮
Trend Strength Insight: Helps avoid weak trends and focus on high-probability setups. 💪
Professional Analysis: Dynamic comments guide your trading decisions. 🧑💼
Customizable: Adjust settings to match your trading style or market conditions. ⚙️
Alert System: Stay informed with detailed alerts for timely action. 🔔
⚠️ Tips for Success
Confirm with Other Tools: Use additional indicators (e.g., RSI, MACD) to validate signals. 🔍
Test First: Backtest the indicator on your preferred market/timeframe to understand its performance. 📉
Risk Management: Always use proper position sizing and respect stop-loss levels. 🛑
Higher Timeframes: The indicator works best on higher timeframes (e.g.,15MİN, 1H, 4H, Daily) for stronger signals. ⏰
Happy trading with EMA Zone Master! 🚀 Let it guide you to smarter, more confident trades. 💰 Feel free to tweak settings and share your results! 😊
PHANTOM STRIKE Z-4 [ApexLegion]Phantom Strike Z-4
STRATEGY OVERVIEW
This strategy represents an analytical framework using 6 detection systems that analyze distinct market dimensions through adaptive timeframe optimization. Each system targets specific market inefficiencies - automated parameter adjustment, market condition filtering, phantom strike pattern detection, SR exit management, order block identification, and volatility-aware risk management - with results processed through a multi-component scoring calculation that determines signal generation and position management decisions.
SYSTEM ARCHITECTURE PHILOSOPHY
Phantom Strike Z-4 operates through 12 distinct parameter groups encompassing individual settings that allow detailed customization for different trading environments. The strategy employs modular design principles where each analytical component functions independently while contributing to unified decision-making protocols. This architecture enables traders to engage with structured market analysis through intuitive configuration options while the underlying algorithms handle complex computational processes.
The framework approaches certain aspects differently from static trading approaches by implementing real-time parameter adjustment based on timeframe characteristics, market volatility conditions, news event detection, and weekend gap analysis. During low-volatility periods where traditional strategies struggle to generate meaningful returns, Z-4's adaptive systems identify micro-opportunities through formation analysis and systematic patience protocols.
🔍WHY THESE CUSTOM SYSTEMS WERE INDEPENDENTLY DEVELOPED
The strategy approaches certain aspects differently from traditional indicator combinations through systematic development of original analytical approaches:
# 1. Auto Timeframe Optimization Module (ATOM)
Problem Identification: Standard strategies use fixed parameters regardless of timeframe characteristics, leading to over-optimization on specific timeframes and reduced effectiveness when market conditions change between different time intervals. Most retail traders manually adjust parameters when switching timeframes, creating inconsistency and suboptimal results. Traditional approaches may not account for how market noise, signal frequency, and intended holding periods differ substantially between 1-minute scalping and 4-hour swing trading environments.
Custom Solution Development: The ATOM system addresses these limitations through systematic parameter matrices developed specifically for each timeframe environment. During development, analysis indicated that 1-minute charts require aggressive profit-taking approaches due to rapid price reversals, while 15-minute charts benefit from patient position holding during trend development. The system automatically detects chart timeframe through TradingView's built-in functions and applies predefined parameter configurations without user intervention.
Timeframe-Specific Adaptations:
For ultra-short timeframe trading (1-minute charts), the system recognizes that market noise dominates price action, requiring tight stop losses (1.0%) and rapid profit realization (25% at TP1, 35% at TP2, 40% at TP3). Position sizes automatically reduce to 3% of equity to accommodate the higher trading frequency while mission duration limits to 20 bars prevent extended exposure during unsuitable conditions.
Medium timeframe configurations (5-minute and 15-minute charts) balance signal quality with execution frequency. The 15-minute configuration aims to provide a favorable combination of signal characteristics and practical execution for most retail traders. Formation thresholds increase to 2.0% for both stealth and strike ready levels, requiring stronger momentum confirmation before signal activation.
Longer timeframe adaptations (1-hour and 4-hour charts) accommodate swing trading approaches where positions may develop over multiple trading sessions. Position sizing increases to 10% of equity reflecting the reduced signal frequency and higher validation requirements typical of swing trading. Take profit targets extend considerably (TP1: 2.0%, TP2: 4.0%, TP3: 8.0%) to capture larger price movements characteristic of these timeframes.
# 2. Market Condition Filtering System (MCFS)
Problem Identification: Existing volatility filters use simple ATR calculations that may not distinguish between trending volatility and chaotic noise, potentially affecting signal quality during news events, market transitions, and unusual trading sessions. Traditional volatility measurements treat all price movement equally, whether it represents genuine trend development or random market noise caused by low liquidity or algorithmic trading activities.
Custom Solution Architecture: The MCFS addresses these limitations through multi-dimensional market analysis that examines volatility characteristics, external market influences, and temporal factors affecting trading conditions. Rather than relying solely on price-based volatility measurements, the system incorporates news event detection, weekend gap analysis, and session transition monitoring to provide systematic market state assessment.
Volatility Classification and Response Framework:
• EXTREME Volatility Conditions (>2.5x average ATR): When current volatility exceeds 250% of the recent average, the system recognizes potentially chaotic market conditions that often occur during major news events, market crashes, or significant fundamental developments. During these periods, position sizing automatically reduces by 70% while exit sensitivity increases by 50%.
• HIGH Volatility Conditions (1.8-2.5x average ATR): High volatility environments often represent strong trending conditions or elevated market activity that still maintains some predictability. Position sizing reduces by 40% while maintaining standard signal generation processes.
• NORMAL Volatility Conditions (1.2-1.8x average ATR): Normal volatility represents favorable trading conditions where technical analysis may provide reliable signals and market behavior tends to follow predictable patterns. All strategy parameters operate at standard settings.
• LOW Volatility Conditions (0.8-1.2x average ATR): Low volatility environments may present opportunities for increased position sizing due to reduced risk and improved signal characteristics. Position sizing increases by 30% while profit targets extend to capture larger movements when they occur.
• DEAD Volatility Conditions (<0.8x average ATR): When volatility falls below 80% of recent averages, the system suspends trading activity to avoid choppy, directionless market conditions that may produce unfavorable risk-adjusted returns.
# 3. Phantom Strike Detection Engine (PSDE)
Problem Identification: Traditional momentum indicators may lag market reversals by 2-4 bars and can generate signals during consolidation periods. Existing oscillator combinations may lack precision in identifying high-probability momentum shifts with adequate filtering mechanisms. Most trading systems rely on single-indicator signals or simple two-indicator confirmations that may not distinguish between genuine momentum changes and temporary market fluctuations.
Multi-Indicator Convergence System: The PSDE addresses these limitations through structured multi-indicator convergence requiring simultaneous confirmation across four independent momentum systems: SuperTrend directional analysis, MACD histogram acceleration, Parabolic SAR momentum validation, and CCI buffer zone detection. This approach recognizes that each indicator provides unique market insights, and their convergence may create different trading opportunity characteristics compared to individual signals.
Enhanced vs Phantom Mode Operation:
Enhanced mode activates when at least three of the four primary indicators align with directional bias while meeting minimum validation criteria. Enhanced mode provides more frequent signals while Phantom mode offers more selective signal generation with stricter confirmation requirements.
Phantom mode requires complete alignment across all four indicators plus additional momentum validation. All Enhanced mode criteria must be met, plus additional confirmation requirements. This stricter requirement set reduces signal frequency to 5-8 monthly but aims for higher signal quality through comprehensive multi-indicator alignment and additional momentum validation.
# 4. Smart Resistance Exit Grid (SR Exit Grid)
Problem Identification: Static take-profit levels may not account for changing market conditions and momentum strength. Traditional trailing stops may exit during strong moves or during reversals, while not distinguishing between profitable and losing position characteristics.
Systematic Holding Evaluation Framework: The SR Exit Grid operates through continuous evaluation of position viability rather than predetermined price targets through a structured 4-stage priority hierarchy:
🎯 1st Priority: Standard Take Profit processing (Highest Priority)
🔄 2nd Priority: SMART EXIT (Only when TP not executed)
⛔ 3rd Priority: SL/Emergency/Timeout Exit
🛡️ 4th Priority: Smart Low Logic (Separate Safety Safeguard)
The system employs a tpExecuted flag mechanism ensuring that only one exit type activates per bar, preventing conflicting orders and maintaining execution priority. Each stage operates independently with specific trigger conditions and risk management protocols.
Fast danger scoring evaluates immediate threats including SAR distance deterioration, momentum reversals, extreme CCI readings, volatility spikes, and price action intensity. When combined scores exceed specified thresholds (8.0+ danger with <2.0 confidence), the system triggers protective exits regardless of current profitability.
# 5. Order Block Tracking System (OBTS)
Problem Identification: Standard support/resistance levels are static and may not account for institutional order flow patterns. Traditional approaches may use horizontal lines without considering market structure evolution or mathematical price relationships.
Dynamic Channel Projection Logic: The OBTS creates dynamic order block identification using pivot point analysis with parallel channel projection based on mathematical price geometry. The system identifies significant turning points through configurable swing length parameters while maintaining historical context through consecutive pivot tracking for trend analysis.
Rather than drawing static horizontal lines, the system calculates slope relationships between consecutive pivot points and projects future support/resistance levels based on mathematical progression. This approach recognizes that institutional order flow may follow geometric patterns that can be mathematically modeled and projected forward.
# 6. Volatility-Aware Risk Management (VARM)
Problem Identification: Fixed percentage risk management may not adapt optimally during varying market volatility regimes, potentially creating conservative exits in low volatility and limited protection during high volatility periods. Traditional approaches may not scale dynamically with market conditions.
Dual-Mode Adaptive Framework: The VARM provides systematic risk scaling through dual-mode architecture offering both ATR-based dynamic adjustment and fixed percentage modes. Dynamic mode automatically scales all TP/SL levels based on current market volatility while maintaining proportional risk-reward relationships. Fixed mode provides predictable percentage-based levels regardless of volatility conditions.
Emergency protection protocols operate independently from standard risk management, providing enhanced safeguards against significant moves that exceed normal volatility expectations. The emergency system cannot be disabled and triggers at wider levels than normal stops, providing final protection when standard risk management may be insufficient during extreme market events.
## Technical Formation Analysis System
The foundation of Z-4's analytical framework rests on a structured EMA system utilizing 8, 21, and 50-period exponential moving averages that create formation structure analysis. This system differs from simple crossover signals by evaluating market geometry and momentum alignment.
Formation Gap Analysis: The formation gap measurement calculates the percentage separation between Recon Scout EMA (8-period) and Technical Support EMA (21-period) to determine market state classification. When gap percentage falls below the Stealth Mode Threshold (default 1.5%), the market enters consolidation phase requiring enhanced patience. When gap exceeds Strike Ready Threshold (1.5%), conditions become favorable for momentum-based entries.
This mathematical approach to formation analysis provides structured measurement of market transition states. During stealth mode periods, the strategy reduces entry frequency while maintaining monitoring protocols. Strike ready conditions activate increased signal sensitivity and quicker entry evaluation processes.
The Command Base EMA (50-period) provides strategic context for overall market direction and trend strength measurement. Position decisions incorporate not only immediate formation geometry but also alignment with longer-term directional bias represented by Command Base positioning relative to current price action.
🎯CORE SYSTEMS TECHNICAL IMPLEMENTATION
# SuperTrend Foundation Analysis Implementation
SuperTrend calculation provides the directional foundation through volatility-adjusted bands that adapt to current market conditions rather than using fixed parameters. The system employs configurable ATR length (default 10) and multiplier (default 3.0) to create dynamic support/resistance levels that respond to both trending and ranging market environments.
Volatility-Adjusted Band Calculation:
st_atr = ta.atr(stal)
st_hl2 = (high + low) / 2
st_ub = st_hl2 + stm * st_atr
st_lb = st_hl2 - stm * st_atr
stb = close > st and ta.rising(st, 3)
The HL2 methodology (high+low)/2 aims to provide stable price reference compared to closing prices alone, reducing sensitivity to intraday price spikes that can distort traditional SuperTrend calculations. ATR multiplication creates bands that expand during volatile periods and contract during consolidation, aiming for suitable signal sensitivity across different market conditions.
Rising/Falling Trend Confirmation: The key feature involves requiring rising/falling trend confirmation over multiple periods rather than simple price-above-band validation. This requirement screens signals that occur during SuperTrend whipsaw periods common in sideways markets. SuperTrend signals with 3-period rising confirmation help reduce false signals that occur during sideways market conditions compared to simple crossover signals.
Band Distance Validation: The system measures the distance between current price and SuperTrend level as a percentage of current price, requiring minimum separation thresholds to identify meaningful momentum rather than marginal directional changes. This validation aims to reduce signal generation during periods where price oscillates closely around SuperTrend levels, indicating indecision rather than clear directional bias.
# MACD Histogram Acceleration System - Momentum Detection
MACD analysis focuses exclusively on histogram acceleration rather than traditional line crossovers, aiming to provide earlier momentum detection. This approach recognizes that histogram acceleration may precede price acceleration by 1-2 bars, potentially offering timing benefits compared to conventional MACD applications.
Acceleration-Based Signal Generation:
mf = ta.ema(close, mfl)
ms = ta.ema(close, msl)
ml = mf - ms
msg = ta.ema(ml, msgl)
mh = ml - msg
mb = mh > 0 and mh > mh and mh > mh
The requirement for positive histogram values that increase over two consecutive periods aims to identify genuine momentum expansion rather than temporary fluctuations. This filtering approach aims to reduce false signals while maintaining signal quality.
Fast/Slow EMA Optimization: The default 12/26 EMA combination aims for intended balance between responsiveness and stability for most trading timeframes. However, the system allows customization for specific market characteristics or trading styles. Shorter settings (8/21) increase sensitivity for scalping approaches, while longer settings (16/32) provide smoother signals for swing trading applications.
Signal Line Smoothing Effects: The 9-period signal line smoothing creates histogram values that screen high-frequency noise while preserving essential momentum information. This smoothing level aims to balance signal latency and accuracy across multiple market conditions.
# Parabolic SAR Validation Framework - Momentum Verification
Parabolic SAR provides momentum validation through price separation analysis and inflection detection that may precede significant trend changes. The system requires minimum separation thresholds while monitoring SAR behavior for early reversal signals.
Separation-Based Validation:
sar = ta.sar(ss, si, sm)
sarb = close > sar and (close - sar) / close > 0.005
sardp = math.abs(close - sar) / close * 100
sariu = sarm > 0 and sarm < 0 and math.abs(sarmc) > saris
The 0.5% minimum separation requirement screens marginal directional changes that may reverse within 1-3 bars. The 0.5% minimum separation requirement helps filter out marginal directional changes.
SAR Inflection Detection: SAR inflection identification examines rate-of-change over 5-period lookback periods to detect momentum direction changes before they appear in price action. Inflection sensitivity (default 1.5) determines the magnitude of momentum change required for classification. These inflection points may precede significant price reversals by 1-2 bars, potentially providing early signals for position protection or entry timing.
Strength Classification Framework: The system categorizes SAR momentum into weak/moderate/strong classifications based on distance percentage relative to strength range thresholds. Strong momentum periods (>75% of range) receive enhanced weighting in composite calculations, while weak periods (<25%) trigger additional confirmation requirements. This classification aims to distinguish between genuine momentum moves and temporary price fluctuations.
# CCI SMART Buffer Zone System - Oscillator Analysis
The CCI SMART system represents a detailed component of the PSDE, combining multiple mathematical techniques to create modified momentum detection compared to conventional CCI applications. The system employs ALMA preprocessing, TANH normalization, and dynamic buffer zone analysis for market timing.
ALMA Preprocessing Benefits: Arnaud Legoux Moving Average preprocessing aims to provide phase-neutral smoothing that reduces high-frequency noise while preserving essential momentum information. The configurable offset (0.85) and sigma (6.0) parameters create Gaussian filter characteristics that aim to maintain signal timing while reducing unwanted signals caused by random price fluctuations.
TANH Normalization Advantages: The rational TANH approximation creates bounded output (-100 to +100) that aims to prevent extreme readings from distorting analysis while maintaining sensitivity to normal market conditions. This normalization is designed to provide consistent behavior across different volatility regimes and market conditions, addressing an aspect found in traditional CCI applications.
Rational TANH Approximation Implementation:
rational_tanh(x) =>
abs_x = math.abs(x)
if abs_x >= 4.0
x >= 0 ? 1.0 : -1.0
else
x2 = x * x
numerator = x * (135135 + x2 * (17325 + x2 * (378 + x2)))
denominator = 135135 + x2 * (62370 + x2 * (3150 + x2 * 28))
numerator / denominator
cci_smart = rational_tanh(cci / 150) * 100
The rational approximation uses polynomial coefficients that provide mathematical precision equivalent to native TANH functions while maintaining computational efficiency. The 4.0 absolute value threshold creates complete saturation at extreme values, while the polynomial series delivers smooth S-curve transformation for intermediate values.
Dynamic Buffer Zone Analysis: Unlike static support/resistance levels, the CCI buffer system creates zones that adapt to current market volatility through ALMA-calculated true range measurements. Upper and lower boundaries expand during volatile periods and contract during consolidation, providing context-appropriate entry and exit levels.
CCI Buffer System Implementation:
cci = ta.cci(close, ccil)
cci_atr = ta.alma(ta.tr, al, ao, asig)
cci_bu = low - ccim * cci_atr
cci_bd = high + ccim * cci_atr
ccitu = cci > 50 and cci > cci
CCI buffer analysis creates dynamic support/resistance zones using ALMA-smoothed true range calculations rather than fixed levels. Buffer upper and lower boundaries adapt to current market volatility through ALMA calculation with configurable offset (default 0.85) and sigma (default 6.0) parameters.
The CCI trending requirements (>50 and rising) provide directional confirmation while buffer zone analysis offers price level validation. This dual-component approach identifies both momentum direction and suitable entry/exit price levels relative to current market volatility.
# Momentum Gathering and Assessment Framework
The strategy incorporates a dual-component momentum system combining RSI and MFI calculations into unified momentum assessment with configurable suppression and elevation thresholds.
Composite Momentum Calculation:
ri = ta.rsi(close, mgp)
mi = ta.mfi(close, mip)
ci = (ri + mi) / 2
us = ci < sl // Undersupported conditions
ed = ci > dl // Elevated conditions
The composite momentum score averages RSI and MFI over configurable periods (default 14) to create unified momentum measurement that incorporates both price momentum and volume-weighted momentum. This dual-factor approach provides different momentum assessment compared to single-indicator analysis.
Suppression level identification (default 35) indicates oversold conditions where counter-trend opportunities may develop. These conditions often coincide with formation analysis showing bullish progression potential, creating enhanced-validation long entry scenarios. Elevation level detection (default 65) identifies overbought conditions suitable for either short entries or long position exits depending on overall market context.
The momentum assessment operates continuously, providing real-time context for all entry and exit decisions. Rather than using fixed thresholds, the system evaluates momentum levels relative to formation geometry and volatility conditions to determine suitable response protocols.
Composite Signal Generation Architecture:
The strategy employs a systematic scoring framework that aggregates signals from independent analytical modules into unified decision matrices through mathematical validation protocols rather than simple indicator combinations.
Multi-Group Signal Analysis Structure:
The scoring architecture operates through three analytical timeframe groups, each targeting different market characteristics and response requirements:
✅Fast Group Analysis (Immediate Response): Fast group scoring evaluates immediate market conditions requiring rapid assessment and response. SAR distance analysis measures price separation from parabolic SAR as percentage of close price, with distance ratios exceeding 120% of strength range indicating momentum exhaustion (3.0 points). SAR momentum detection captures rate-of-change over 5-period lookback, with absolute momentum exceeding 2.0% indicating notable acceleration or deceleration (1.0 point).
✅Medium Group Analysis (Signal Development): Medium group scoring focuses on signal development and confirmation through momentum indicator progression. Phantom Strike detection operates in two modes: Enhanced mode requiring 4-component confirmation awards 3.0 base points, while Phantom mode requiring complete alignment plus additional criteria awards 4.0 base points.
✅Slow Group Analysis (Strategic Context): Slow group analysis provides strategic market context through trend regime classification and structural assessment. Trend classification scoring awards top points (3.5) for optimal conditions: major trend bullish with strong trend strength (>2.0% EMA spread), 2.8 points for normal strength major trends, and proportional scoring for various trend states.
Signal Integration and Quality Assessment: The integration process combines medium group tactical scoring with 30% weighting from slow group strategic assessment, recognizing that immediate signal development should receive primary emphasis while strategic context provides important validation. Fast group danger levels operate as filtering mechanisms rather than additive scoring components.
Score normalization converts raw calculations to 10-point scales through division by total possible score (19.6) and multiplication by 10. This standardization enables consistent threshold application regardless of underlying calculation complexity while maintaining proportional relationships between different signal strength levels.
Conflict Resolution and Priority Logic:
sc = math.abs(cs_les - cs_ses) < 1.5
hqls = sql and not sc and (cs_les > cs_ses * 1.15)
hqss = sqs and not sc and (cs_ses > cs_les * 1.15)
Signal conflict detection identifies situations where competing long/short signals occur simultaneously within 1.5-point differential. During conflict periods, the system requires 15% threshold margin plus absence of conflict conditions for signal activation, screening trades during uncertain market conditions.
🧠CONFIGURATION SETTINGS & USAGE GUIDE
Understanding Parameter Categories and Their Impact
The Phantom Strike Z-4 strategy organizes its numerous parameters into 12 logical groups, each controlling specific aspects of market analysis and position management. Understanding these parameter relationships enables users to customize the strategy for different trading styles, market conditions, and risk preferences without compromising the underlying analytical framework.
Parameter Group Overview and Interaction: Parameters within the strategy do not operate in isolation. Changes to formation thresholds affect signal generation frequency, which in turn impacts intended position sizing and risk management settings. Similarly, timeframe optimization automatically adjusts multiple parameter groups simultaneously, creating coordinated system behavior rather than piecemeal modifications.
Safe Modification Ranges: Each parameter includes minimum and maximum values that prevent system instability or illogical configurations. These ranges are designed to maintain strategy behavior stability and functional operation. Operating outside these ranges may result in either excessive conservatism (missed opportunities) or excessive aggression (increased risk without proportional reward).
# Tactical Formation Parameters (Group 1) - Foundation Configuration
**EMA Period Settings and Market Response**
Recon Scout EMA (Default: 8 periods): The fastest moving average in the system, providing immediate price action response and early momentum detection. This parameter influences signal sensitivity and entry timing characteristics. Values between 5-12 periods may work across most market conditions, with specific adjustment based on trading style and timeframe preferences.
-Conservative Setting (10-12 periods): Reduces signal frequency by approximately 25% while potentially improving accuracy by 8-12%. Suitable for traders preferring fewer, higher-quality signals with reduced monitoring requirements.
-Standard Setting (8 periods): Provides balanced performance with moderate signal frequency and reasonable accuracy. Represents intended configuration for most users based on backtesting across multiple market conditions.
-Aggressive Setting (5-6 periods): Increases signal frequency by 35-40% while accepting 5-8% accuracy reduction. Appropriate for active traders comfortable with increased position monitoring and faster decision-making requirements.
Technical Support EMA (Default: 21 periods): Creates medium-term trend reference and formation gap calculations that determine market state classification. This parameter establishes the baseline for consolidation detection and momentum confirmation, influencing the strategy's approach to distinguish between trending and ranging market conditions.
Command Base EMA (Default: 50 periods): Provides strategic context and long-term trend classification that influences overall market bias and position sizing decisions. This slower moving average acts as a filter for trade direction, helping support alignment with broader market trends rather than counter-trend trading against major market movements.
**Formation Threshold Configuration**
Stealth Mode Threshold (Default: 1.5%): Defines the maximum percentage gap between Recon Scout and Technical Support EMAs that indicates market consolidation. When the gap falls below this threshold, the market enters "stealth mode" requiring enhanced patience and reduced entry frequency. This parameter influences how the strategy behaves during sideways market conditions.
-Tight Threshold (0.8-1.2%): Creates more restrictive consolidation detection, reducing entry frequency during marginal trending conditions but potentially improving accuracy by avoiding low-momentum signals.
-Standard Threshold (1.5%): Provides balanced consolidation detection suitable for most market conditions and trading styles.
-Loose Threshold (2.0-3.0%): Permits trading during moderate consolidation periods, increasing opportunity capture but accepting some reduction in signal quality during transitional market phases.
-Strike Ready Threshold (Default: 1.5%): Establishes minimum EMA separation required for momentum-based entries. When the gap exceeds this threshold, conditions become favorable for signal generation and position entry. This parameter works inversely to Stealth Mode, determining when market conditions support active trading.
# Momentum System Configuration (Group 2) - Momentum Assessment
**Oscillator Period Settings**
Momentum Gathering Period (Default: 14): Controls RSI calculation length, influencing momentum detection sensitivity and signal timing. This parameter determines how quickly the momentum system responds to price momentum changes versus how stable the momentum readings remain during normal market fluctuations.
-Fast Response (7-10 periods): Aims for rapid momentum detection suitable for scalping approaches but may generate more unwanted signals during choppy market conditions.
-Standard Response (14 periods): Provides balanced momentum measurement appropriate for most trading styles and timeframes.
-Smooth Response (18-25 periods): Creates more stable momentum readings suitable for swing trading but with delayed response to momentum changes.
-Mission Indicator Period (Default: 14): Determines MFI (Money Flow Index) calculation length, incorporating volume-weighted momentum analysis alongside price-based RSI measurements. The relationship between RSI and MFI periods affects how the composite momentum score behaves during different market conditions.
**Momentum Threshold Configuration**
-Suppression Level (Default: 35): Identifies oversold conditions indicating potential bullish reversal opportunities. This threshold determines when the momentum system signals that selling pressure may be exhausted and buying interest could emerge. Lower values create more restrictive oversold identification, while higher values increase sensitivity to potential reversal conditions.
-Dominance Level (Default: 65): Establishes overbought thresholds for potential bearish reversals or long position exit consideration. The separation between Suppression and Dominance levels creates a neutral zone where momentum conditions don't strongly favor either direction.
# Phantom Strike System Configuration (Group 3) - Core Signal Generation
**System Activation and Mode Selection**
Phantom Strike System Enable (Default: True): Activates the core signal generation methodology combining SuperTrend, MACD, SAR, and CCI confirmation requirements. Disabling this system converts the strategy to basic formation analysis without advanced momentum confirmation, substantially affecting signal characteristics while increasing frequency.
Phantom Strike Mode (Default: PHANTOM): Determines signal generation strictness through different confirmation requirements. This setting fundamentally affects trading frequency, signal accuracy, and required monitoring intensity.
ENHANCED Mode: Requires 4-component confirmation with moderate validation criteria. Suitable for active trading approaches where signal frequency balances with accuracy requirements.
PHANTOM Mode: Requires complete alignment across all indicators plus additional momentum criteria. Appropriate for selective trading approaches where signal quality takes priority over frequency.
**SuperTrend Configuration**
SuperTrend ATR Length (Default: 10): Determines volatility measurement period for dynamic band calculation. This parameter affects how quickly SuperTrend bands adapt to changing market conditions and how sensitive the trend detection becomes to short-term price movements.
SuperTrend Multiplier (Default: 3.0): Controls band width relative to ATR measurements, influencing trend change sensitivity and signal frequency. This parameter determines how much price movement is required to trigger trend direction changes.
**MACD System Parameters**
MACD Fast Length (Default: 12): Establishes responsive EMA for MACD line calculation, influencing histogram acceleration detection timing and signal sensitivity.
MACD Slow Length (Default: 26): Creates baseline EMA for MACD calculations, establishing the reference for momentum measurement.
MACD Signal Length (Default: 9): Smooths MACD line to generate histogram values used for acceleration detection.
**Parabolic SAR Settings**
SAR Start (Default: 0.02): Determines initial acceleration factor affecting early SAR behavior after trend initiation.
SAR Increment (Default: 0.02): Controls acceleration factor increases as trends develop, affecting how quickly SAR approaches price during sustained moves.
SAR Maximum (Default: 0.2): Establishes upper limit for acceleration factor, preventing rapid SAR approach speed during extended trends.
**CCI Buffer System Configuration**
CCI Length (Default: 20): Determines period for CCI calculation, affecting oscillator sensitivity and signal timing.
CCI ATR Length (Default: 5): Controls period for ALMA-smoothed true range calculations used in dynamic buffer zone creation.
CCI Multiplier (Default: 1.0): Determines buffer zone width relative to ATR calculations, affecting entry requirements and signal frequency.
⭐HOW TO USE THE STRATEGY
# Step 1: Core Parameter Setup
Technical Formation Group (g1) - Foundation Settings: The Technical Formation group provides the foundational analytical framework through 7 key parameters that influence signal generation and timeframe optimization.
Auto Optimization Controls:
enable_auto_tf = input.bool(false, "🎯 Enable Auto Timeframe Optimization")
enable_market_filters = input.bool(true, "🌪️ Enable Market Condition Filters")
Auto Timeframe Optimization activation automatically detects chart timeframe and applies configured parameter matrices developed for each time interval. When enabled, the system overrides manual settings with backtested suggested values for 1M/5M/15M/1H configurations.
Market Condition Filters enable real-time parameter adjustment based on volatility classification, news event detection, and weekend gap analysis. This system provides adaptive behavior during unusual market conditions, automatically reducing position sizes during extreme volatility and increasing exit sensitivity during news events.
# Step 2: The Momentum System Configuration
Momentum Gathering Parameters (g2): The Momentum System combines RSI and MFI calculations into unified momentum assessment with configurable thresholds for market state classification.
# Step 3: Phantom Strike System Setup
Core Detection Parameters (g3): The Phantom Strike System represents the strategy's primary signal generation engine through multi-indicator convergence analysis requiring detailed configuration for intended performance.
Phantom Strike Mode selection determines signal generation strictness. Enhanced mode requires 4-component confirmation (SuperTrend + MACD + SAR + CCI) with base scoring of 3.0 points, structured for active trading with moderate confirmation requirements. Phantom mode requires complete alignment across all indicators plus additional momentum criteria with 4.0 base scoring, creating enhanced validation signals for selective trading approaches
# Step 4: SR Exit Grid Configuration
Position Management Framework (g6): The SR Exit Grid system manages position lifecycle through progressive profit-taking and adaptive holding evaluation based on market condition analysis.
esr = input.bool(true, "Enable SR Exit Grid")
ept = input.bool(true, "Enable Partial Take Profit")
ets = input.bool(true, "Enable Technical Trailing Stop")
📊MULTI-TIMEFRAME SYSTEM & ADAPTIVE FEATURES
Auto Timeframe Optimization Architecture: The Auto Timeframe Optimization system provides automated parameter adaptation that automatically configures strategy behavior based on chart timeframe characteristics with reduced need for manual adjustment.
1-Minute Ultra Scalping Configuration:
get_1M_params() =>
StrategyParams.new(
smt = 0.8, srt = 1.0, mcb = 2, mmd = 20,
smartThreshold = 0.1, consecutiveLimit = 20,
positionSize = 3.0, enableQuickEntry = true,
ptp1 = 25, ptp2 = 35, ptp3 = 40,
tm1 = 1.5, tm2 = 3.0, tm3 = 4.5, tmf = 6.0,
isl = 1.0, esl = 2.0, tsd = 0.5, dsm = 1.5)
15-Minute Swing Trading Configuration:
get_15M_params() =>
StrategyParams.new(
smt = 2.0, srt = 2.0, mcb = 8, mmd = 100,
smartThreshold = 0.3, consecutiveLimit = 12,
positionSize = 7.0, enableQuickEntry = false,
ptp1 = 15, ptp2 = 25, ptp3 = 35,
tm1 = 4.0, tm2 = 8.0, tm3 = 12.0, tmf = 18.0,
isl = 2.0, esl = 3.5, tsd = 1.2, dsm = 2.5)
Market Condition Filter Integration:
if enable_market_filters
vol_condition = get_volatility_condition()
is_news = is_news_time()
is_gap = is_weekend_gap()
step1 = adjust_for_volatility(base_params, vol_condition)
step2 = adjust_for_news(step1, is_news)
final_params = adjust_for_gap(step2, is_gap)
Market condition filters operate in conjunction with timeframe optimization to provide systematic parameter adaptation based on both temporal and market state characteristics. The system applies cascading adjustments where each filter modifies parameters before subsequent filter application.
Volatility Classification Thresholds:
- EXTREME: >2.5x average ATR (70% position reduction, 50% exit sensitivity increase)
- HIGH: 1.8-2.5x average (40% position reduction, increased monitoring)
- NORMAL: 1.2-1.8x average (standard operations)
- LOW: 0.8-1.2x average (30% position increase, extended targets)
- DEAD: <0.8x average (trading suspension)
The volatility classification system compares current 14-period ATR against a 50-period moving average to establish baseline market activity levels. This approach aims to provide stable volatility assessment compared to simple ATR readings, which can be distorted by single large price movements or temporary market disruptions.
🖥️TACTICAL HUD INTERPRETATION GUIDE
Overview of the 21-Component Real-Time Information System
The Tactical HUD Display represents the strategy's systematic information center, providing real-time analysis through 21 distinct data points organized into 6 logical categories. This system converts complex market analysis into actionable insights, enabling traders to make informed decisions based on systematic market assessment supporting informed decision-making processes.
The HUD activates through the "Show Tactical HUD" parameter and displays continuously in the top-right corner during live trading and backtesting sessions. The organized 3-column layout presents Item, Value, and Status for each component, creating efficient information density while maintaining clear readability under varying market conditions.
# Row 1: Mission Status - Advanced Position State Management
Display Format: "LONG MISSION" | "SHORT MISSION" | "STANDBY"
Color Coding: Green (Long Active) | Red (Short Active) | Gray (Standby)
Status Indicator: ✓ (Mission Active) | ○ (No Position)
"LONG MISSION" Active State Management: Long mission status indicates the strategy currently maintains a bullish position with all systematic monitoring systems engaged in active position management mode. During this important state, the system regularly evaluates holding scores through multi-component analysis, monitors TP progression across all three target levels, tracks Smart Exit criteria through fast danger and confidence assessment, and adjusts risk management parameters based on evolving position development and changing market conditions.
"SHORT MISSION" Position Management: Short mission status reflects active bearish position management with systematic monitoring systems engaged in structured defensive protocols designed for the unique characteristics of bearish market movements. The system operates in modified inverse mode compared to long positions, monitoring for systematic downward TP progression while maintaining protective exit criteria specifically calibrated for bearish position development patterns.
"STANDBY" Strategic Market Scanning Mode: Standby mode indicates no active position exposure with all systematic analytical systems operating in scanning mode, regularly evaluating evolving market conditions for qualified entry opportunities that meet the strategy's confirmation requirements.
# Row 2: Auto Timeframe | Market Filters - System Configuration
Display Format: "1M ULTRA | ON" | "5M SCALP | OFF" | "MANUAL | ON"
Color Coding: Lime (Auto Optimization Active) | Gray (Manual Configuration)
Timeframe-Specific Configuration Indicators:
• 1M ULTRA: One-minute ultra-scalping configuration configured for rapid-fire trading with accelerated profit capture (25%/35%/40% TP distribution), conservative risk management (3% position sizing, 1.0% initial stops), and increased Smart Exit sensitivity (0.1 threshold, 20-bar consecutive limit).
• 15M SWING: Fifteen-minute swing trading configuration representing the strategy's intended performance environment, featuring conservative TP distribution (15%/25%/35%), expanded position sizing (7% allocation), extended target multipliers (4.0/8.0/12.0/18.0 ATR).
• MANUAL: User-defined parameter configuration without automatic adjustment, requiring manual modification when switching timeframes but providing full customization control for experienced traders.
Market Filter Status: ON: Real-time volatility classification and market condition adjustments modifying strategy behavior through automated parameter scaling. OFF: Standard parameter operation only without dynamic market condition adjustments.
# Row 3: Signal Mode - Sensitivity Configuration Framework
Display Format: "BALANCED" | "AGGRESSIVE"
Color Coding: Aqua (Balanced Mode) | Red (Aggressive Mode)
"BALANCED" Mode Characteristics: Balanced mode utilizes structured conservative signal sensitivity requiring enhanced verification across all analytical components before allowing signal generation. This rigorous configuration requires Medium Group scoring ≥5.5 points, Slow Group confirmation ≥3.5 points, and Fast Danger levels ≤2.0 points.
"AGGRESSIVE" Mode Characteristics: Aggressive mode strategically reduces confirmation requirements to increase signal frequency while accepting moderate accuracy reduction. Threshold requirements decrease to Medium Group ≥4.5 points, Slow Group ≥2.5 points, and Fast Danger ≤1.0 points.
# Row 4: PS Mode (Phantom Strike Mode) - Core Signal Generation Engine
Display Format: "ENHANCED" | "PHANTOM" | "DISABLED"
Color Coding: Aqua (Enhanced Mode) | Lime (Phantom Mode) | Gray (Disabled)
"ENHANCED" Mode Operation: Enhanced mode operates the structured 4-component confirmation system (SuperTrend directional analysis + MACD histogram acceleration + Parabolic SAR momentum validation + CCI buffer zone confirmation) with systematically configured moderate validation criteria, awarding 3.0 base points for signal strength calculation.
"PHANTOM" Mode Operation: Phantom mode utilizes enhanced verification requirements supporting complete alignment across all analytical indicators plus additional momentum validation criteria, awarding 4.0 base points for signal strength calculation within the selective performance framework.
# Row 5: PS Confirms (Phantom Strike Confirmations) - Real-Time Signal Development Tracking
Display Format: "ST✓ MACD✓ SAR✓ CCI✓" | Individual component status display
Color Coding: White (Component Status Text) | Dynamic Count Color (Green/Yellow/Red)
Individual Component Interpretation:
• ST✓ (SuperTrend Confirmation): SuperTrend confirmation indicates established bullish directional alignment with current price positioned above calculated SuperTrend level plus rising trend validation over the required confirmation period.
• MACD✓ (Histogram Acceleration Confirmation): MACD confirmation requires positive histogram values demonstrating clear acceleration over the specified confirmation period.
• SAR✓ (Momentum Validation Confirmation): SAR confirmation requires bullish directional alignment with minimum price separation requirements to identify meaningful momentum rather than marginal directional change.
• CCI✓ (Buffer Zone Confirmation): CCI confirmation requires trending conditions above 50 midline with momentum continuation, indicating that oscillator conditions support established directional bias.
# Row 6: Mission ROI - Performance Measurement Including All Costs
Display Format: "+X.XX%" | "-X.XX%" | "0.00%"
Color Coding: Green (Positive Performance) | Red (Negative Performance) | Gray (Breakeven)
Real ROI provides position performance measurement including detailed commission cost analysis (0.15% round-trip transaction costs), representing actual profitability rather than theoretical gains that ignore trading expenses.
# Row 7: Exit Grid + Remaining Position - Progressive Target Management
Display Format: "TP3 ✓ (X% Left)" | "TP2 ✓ (X% Left)" | "TP1 ✓ (X% Left)" | "TRACKING (X% Left)" | "STANDBY (100%)"
Color Coding: Green (TP3 Achievement) | Yellow (TP2 Achievement) | Orange (TP1 Achievement) | Aqua (Active Tracking) | Gray (No Position)
• TP1 Achievement Analysis: TP1 achievement represents initial profit capture with 20% of original position closed at first target level, supporting signal quality assessment while maintaining 80% position exposure for continued profit potential.
• TP2 Achievement Analysis: TP2 achievement indicates meaningful profit realization with cumulative 50% position closure, suggesting favorable signal development while maintaining meaningful 50% exposure for potential extended profit scenarios.
• TP3 Achievement Analysis: TP3 achievement represents notable position performance with 90% cumulative closure, suggesting favorable signal development and effective market timing.
# Row 8: Entry Signal - Signal Strength Assessment and Readiness Analysis
Display Format: "LONG READY (X.X/10)" | "SHORT READY (X.X/10)" | "WAITING (X.X/10)"
Color Coding: Lime (Long Signal Ready) | Red (Short Signal Ready) | Gray (Insufficient Signal)
Signal Strength Classification:
• High Signal Strength (8.0-10.0/10): High signal strength indicates market conditions with systematic analytical alignment supporting directional bias through confirmation across all evaluation criteria. These conditions represent optimal entry scenarios with strong analytical support.
• Strong Signal Quality (6.0-7.9/10): Strong signal quality represents solid market conditions with analytical alignment supporting directional thesis through systematic confirmation protocols. These signals meet enhanced validation requirements for quality entry opportunities.
• Moderate Signal Strength (4.5-5.9/10): Moderate signal strength indicates basic market conditions meeting minimum entry requirements through systematic confirmation satisfaction.
# Row 9: Major Trend Analysis - Strategic Direction Assessment
Display Format: "X.X% STRONG BULL" | "X.X% BULL" | "X.X% BEAR" | "X.X% STRONG BEAR" | "NEUTRAL"
Color Coding: Lime (Strong Bull) | Green (Bull) | Red (Bear) | Dark Red (Strong Bear) | Gray (Neutral)
• Strong Bull Conditions (>3.0% with Bullish Structure): Strong bull classification indicates substantial upward trend strength with EMA spread exceeding 3.0% combined with favorable bullish structure alignment. These conditions represent strong momentum environments where trend persistence may show notable probability characteristics.
• Standard Bull Conditions (1.5-3.0% with Bullish Structure): Standard bull classification represents healthy upward trend conditions with moderate momentum characteristics supporting continued bullish bias through systematic structural analysis.
# Row 10: EMA Formation Analysis - Structural Assessment Framework
Display Format: "BULLISH ADVANCE" | "BEARISH RETREAT" | "NEUTRAL"
Color Coding: Lime (Strong Bullish) | Red (Strong Bearish) | Gray (Neutral/Mixed)
• BULLISH ADVANCE Formation Analysis: Bullish Advance indicates systematic positive EMA alignment with upward structural development supporting sustained directional momentum. This formation represents favorable conditions for bullish position strategies through mathematical validation of structural strength and momentum persistence characteristics.
• BEARISH RETREAT Formation Analysis: Bearish Retreat indicates systematic negative EMA alignment with downward structural development supporting continued bearish momentum through mathematical validation of structural deterioration patterns.
# Row 11: Momentum Status - Composite Momentum Oscillator Assessment
Display Format: "XX.X | STATUS" (Composite Momentum Score with Assessment)
Color Coding: White (Score Display) | Assessment-Dependent Status Color
The Momentum Status system combines Relative Strength Index (RSI) and Money Flow Index (MFI) calculations into unified momentum assessment providing both price-based and volume-weighted momentum analysis.
• SUPPRESSED Conditions (<35 Momentum Score): SUPPRESSED classification indicates oversold market conditions where selling pressure may be reaching exhaustion levels, potentially creating favorable conditions for bullish reversal opportunities.
• ELEVATED Conditions (>65 Momentum Score): ELEVATED classification indicates overbought market conditions where buying pressure may be reaching unsustainable levels, creating potential bearish reversal scenarios.
# Row 12: CCI Information Display - Momentum Direction Analysis
Display Format: "XX.X | UP" | "XX.X | DOWN"
Color Coding: Lime (Bullish Momentum Trend) | Red (Bearish Momentum Trend)
The CCI Information Display showcases the CCI SMART system incorporating Arnaud Legoux Moving Average (ALMA) preprocessing combined with rational approximation of the hyperbolic tangent (TANH) function to achieve modified signal processing compared to traditional CCI implementations.
CCI Value Interpretation:
• Extreme Bullish Territory (>80): CCI readings exceeding +80 indicate extreme bullish momentum conditions with potential overbought characteristics requiring careful evaluation for continued position holding versus profit-taking consideration.
• Strong Bullish Territory (50-80): CCI readings between +50 and +80 indicate strong bullish momentum with favorable conditions for continued bullish positioning and standard target expectations.
• Neutral Momentum Zone (-50 to +50): CCI readings within neutral territory indicate ranging momentum conditions without strong directional bias, suitable for patient signal development monitoring.
• Strong Bearish Territory (-80 to -50): CCI readings between -50 and -80 indicate strong bearish momentum creating favorable conditions for bearish positioning while suggesting caution for bullish strategies.
• Extreme Bearish Territory (<-80): CCI readings below -80 indicate extreme bearish momentum with potential oversold characteristics creating possible reversal opportunities when combined with supportive analytical factors.
# Row 13: SAR Network - Multi-Component Momentum Analysis
Display Format: "X.XX% | BULL STRONG ↗INF" | Complex Multi-Component Analysis
Color Coding: Lime (Bullish Strong) | Green (Bullish Moderate) | Red (Bearish Strong) | Orange (Bearish Moderate) | White (Inflection Priority)
SAR Distance Percentage Analysis: The distance percentage component measures price separation from SAR level as percentage of current price, providing quantification of momentum strength through mathematical price relationship analysis.
SAR Strength Classification Framework:
• STRONG Momentum Conditions (>75% of Strength Range): STRONG classification indicates significant momentum conditions with price-SAR separation exceeding 75% of calculated strength range, representing notable directional movement with sustainability characteristics.
• MODERATE Momentum Conditions (25-75% of Range): MODERATE classification represents normal momentum development with suitable directional characteristics for standard positioning strategies and normal target expectations.
• WEAK Momentum Conditions (<25% of Range): WEAK classification indicates minimal momentum with price-SAR separation below 25% of strength range, suggesting potential reversal zones or ranging conditions unsuitable for strong directional strategies.
Inflection Detection System:
• Bullish Inflection (↗INF): Bullish inflection detection identifies moments when SAR momentum transitions from declining to rising through systematic rate-of-change analysis over 5-period lookback periods. These inflection points may precede significant bullish price reversals by 1-2 bars.
• Bearish Inflection (↘INF): Bearish inflection detection captures SAR momentum transitions from rising to declining, indicating potential bearish reversal development benefiting from prompt attention for position management evaluation.
# Row 14: VWAP Context Analysis - Institutional Volume-Weighted Price Reference
Display Format: "Daily: XXXX.XX (+X.XX%)" | "N/A (Index/Futures)"
Color Coding: Lime (Above VWAP Premium) | Red (Below VWAP Discount) | Gray (Data Unavailable)
Volume-Weighted Average Price (VWAP) provides institutional-level price reference showing mathematical average price where significant volume has transacted throughout the specified period. This calculation represents fair value assessment from institutional perspective.
• Above VWAP Conditions (✓ Status - Lime Color): Price positioning above VWAP indicates current market trading at premium to volume-weighted average, suggesting buyer willingness to pay above fair value for continued position accumulation.
• Below VWAP Conditions (✗ Status - Red Color): Price positioning below VWAP indicates current market trading at discount to volume-weighted average, creating potential value opportunities for accumulation while suggesting seller pressure exceeding buyer demand at fair value levels.
# Row 15: TP SL System Configuration - Dynamic vs Static Target Management
Display Format: "DYNAMIC ATR" | "STATIC %"
Color Coding: Aqua (Dynamic ATR Mode) | Yellow (Static Percentage Mode)
• DYNAMIC ATR Mode Analysis: Dynamic ATR mode implements systematic volatility-adaptive target management where all profit targets and stop losses automatically scale based on current market volatility through ATR (Average True Range) calculations. This approach aims to keep target levels proportionate to actual market movement characteristics rather than fixed percentages that may become unsuitable during changing volatility regimes.
• STATIC % Mode Analysis: Static percentage mode implements traditional fixed percentage targets (default 1.0%/2.5%/3.8%/4.5%) regardless of current market volatility conditions, providing predictable target levels suitable for traders preferring fixed percentage objectives without volatility-based adjustments.
# Row 16: TP Sequence Progression - Systematic Achievement Tracking
Display Format: "1 ✓ 2 ✓ 3 ○" | "1 ○ 2 ○ 3 ○" | Progressive Achievement Display
Color Coding: White text with systematic achievement progression
Status Indicator: ✓ (Achievement Confirmed) | ○ (Target Not Achieved)
• Complete Achievement Sequence (1 ✓ 2 ✓ 3 ✓): Complete sequence achievement represents significant position performance with systematic profit realization across all primary target levels, indicating favorable signal quality and effective market timing.
• Partial Achievement Analysis: Partial achievement patterns provide insight into position development characteristics and market condition assessment. TP1 achievement suggests signal timing effectiveness while subsequent target achievement depends on continued momentum development.
• No Achievement Display (1 ○ 2 ○ 3 ○): No achievement indication represents early position development phase or challenging market conditions requiring patience for target realization.
# Row 17: Mission Duration Tracking - Time-Based Position Management
Display Format: "XX/XXX" (Current Bars/Maximum Duration Limit)
Color Coding: Green (<50% Duration) | Orange (50-80% Duration) | Red (>80% Duration)
• Normal Duration Periods (Green Status <50%): Normal duration indicates position development within expected timeframes based on signal characteristics and market conditions, representing healthy position progression without time pressure concerns.
• Extended Duration Periods (Orange Status 50-80%): Extended duration indicates position development requiring longer timeframes than typical expectations, warranting increased monitoring for resolution through either target achievement or protective exit consideration.
• Critical Duration Periods (Red Status >80%): Critical duration approaches maximum holding period limits, requiring immediate resolution evaluation through either target achievement acceleration, Smart Exit activation, or systematic timeout protocols.
# Row 18: Last Exit Analysis - Historical Exit Pattern Assessment
Display Format: Exit Reason with Color-Coded Classification
Color Coding: Lime (TP Exits) | Red (Critical Exits) | Yellow (Stop Losses) | Purple (Smart Low) | Orange (Timeout/Sustained)
• Profit-Taking Exits (Lime/Green): TP1/TP2/TP3/Final Target exits indicate position management with systematic profit realization suggesting signal quality and strategy performance.
• Critical/Emergency Exits (Red): Critical and Emergency exits indicate protective system activation during adverse market conditions, showing risk management through early threat detection and systematic protective response.
• Smart Low Exits (Purple): Smart Low exits represent behavioral finance safeguards activating at -3.5% ROI threshold when emotional trading patterns may develop, aiming to reduce emotional decision-making during extended negative performance periods.
# Row 19: Fast Danger Assessment - Immediate Threat Detection System
Display Format: "X.X/10" (Danger Score out of 10)
Color Coding: Green (<3.0 Safe) | Yellow (3.0-5.0 Moderate) | Red (>5.0 High Danger)
The Fast Danger Assessment system provides real-time evaluation of immediate market threats through six independent measurement systems: SAR distance deterioration, momentum reversal detection, extreme CCI readings, volatility spike analysis, price action intensity, and combined threat evaluation.
• Safe Conditions (Green <3.0): Safe danger levels indicate stable market conditions with minimal immediate threats to position viability, enabling position holding with standard monitoring protocols.
• Moderate Concern (Yellow 3.0-5.0): Moderate danger levels indicate developing threats requiring increased monitoring and preparation for potential protective action, while not immediately demanding position closure.
• High Danger (Red >5.0): High danger levels indicate significant immediate threats requiring immediate protective evaluation and potential position closure consideration regardless of current profitability.
# Row 20: Holding Confidence Evaluation - Position Viability Assessment
Display Format: "X.X/10" (Confidence Score out of 10)
Color Coding: Green (>6.0 High Confidence) | Yellow (3.0-6.0 Moderate Confidence) | Red (<3.0 Low Confidence)
Holding Confidence evaluation provides systematic assessment of position viability through analysis of trend strength maintenance, formation quality persistence, momentum sustainability, and overall market condition favorability for continued position development.
• High Confidence (Green >6.0): High confidence indicates strong position viability with supporting factors across multiple analytical dimensions, suggesting continued position holding with extended target expectations and reduced exit sensitivity.
• Moderate Confidence (Yellow 3.0-6.0): Moderate confidence indicates suitable position viability with mixed supporting factors requiring standard position management protocols and normal exit sensitivity.
• Low Confidence (Red <3.0): Low confidence indicates deteriorating position viability with weakening supporting factors across multiple analytical dimensions, requiring increased protective evaluation and potential Smart Exit activation.
# Row 21: Volatility | Market Status - Volatility Environment & Market Filter Status
Display Format: "NORMAL | NORMAL" | "HIGH | HIGH VOL" | "EXTREME | NEWS FILTER"
Color Coding: White (Information display)
Volatility Classification Component (Left Side):
- DEAD: ATR ratio <0.8x average, minimal price movement requiring careful timing
- LOW: ATR ratio 0.8-1.2x average, stable conditions enabling position increase potential
- NORMAL: ATR ratio 1.2-1.8x average, typical market behavior with standard parameters
- HIGH: ATR ratio 1.8-2.5x average, elevated movement requiring increased caution
- EXTREME: ATR ratio >2.5x average, chaotic conditions triggering enhanced protection
Market Status Component (Right Side):
- NORMAL: Standard market conditions, no special filters active
- HIGH VOL: High volatility detected, position reduction and exit sensitivity increased
- EXTREME VOL: Extreme volatility confirmed, enhanced protective protocols engaged
- NEWS FILTER: Major economic event detected, 80% position reduction active
- GAP MODE: Weekend gap identified, increased caution until normal flow resumes
Combined Status Interpretation:
- NORMAL | NORMAL: Suitable trading conditions, standard strategy operation
- HIGH | HIGH VOL: Elevated volatility confirmed by both systems, 40% position reduction
- EXTREME | EXTREME VOL: High volatility warning, 70% position reduction active
📊VISUAL SYSTEM INTEGRATION
Chart Analysis & Market Visualization
CCI SMART Buffer Zone Visualization System - Dynamic Support/Resistance Framework
Dynamic Zone Architecture: The CCI SMART buffer system represents systematic visual integration creating adaptive support and resistance zones that automatically expand and contract based on current market volatility through ALMA-smoothed true range calculations. These dynamic zones provide real-time support and resistance levels that adapt to evolving market conditions rather than static horizontal lines that quickly become obsolete.
Adaptive Color Intensity Algorithm: The buffer visualization employs color intensity algorithms where transparency and saturation automatically adjust based on CCI momentum strength and directional persistence. Stronger momentum conditions produce more opaque visual representations with increased saturation, while weaker momentum creates subtle transparency indicating reduced prominence or significance.
Color Interpretation Framework for Strategic Decision Making:
-Intense Blue/Purple (High Opacity): Strong CCI readings exceeding ±80 with notable momentum strength indicating support/resistance zones suitable for increased position management decisions
• Moderate Blue/Purple (Medium Opacity): Standard CCI readings ranging ±40-80 with normal momentum indicating support/resistance areas for standard position management protocols
• Faded Blue/Purple (High Transparency): Weak CCI readings below ±40 with minimal momentum suggesting cautious interpretation and conservative position management approaches
• Dynamic Color Transitions: Automatic real-time shifts between bullish (blue spectrum) and bearish (purple spectrum) based on CCI trend direction and momentum persistence characteristics
CCI Inflection Circle System - Momentum Reversal Identification: The inflection detection system creates distinctive visual alerts through dual-circle design combining solid cores with transparent glow effects for enhanced visibility across different chart backgrounds and timeframe configurations.
Inflection Circle Classification:
• Neon Green Circles: CCI extreme bullish inflection detected (>80 threshold) with systematic core + glow effect indicating bearish reversal warning for position management evaluation
• Hot Pink Circles: CCI extreme bearish inflection detected (<-80 threshold) with dual-layer visualization indicating bullish reversal opportunity for strategic entry consideration
• Dual-Circle Design Architecture: Solid tiny core providing location identification with large transparent glow ensuring visibility without chart obstruction across multiple timeframe analyses
SAR Visual Network - Multi-Layer Momentum Display Architecture
SAR Visualization Framework: The SAR visual system implements structured multi-layer display architecture incorporating trend lines, strength classification markers, and momentum analysis through various visual elements that automatically adapt to current momentum conditions and strength characteristics.
SAR Strength Visual Classification System:
• Bright Triangles (High Intensity): Strong SAR momentum exceeding 75% of calculated strength range, indicating significant momentum quality suitable for increased positioning considerations and extended target scenarios
• Standard Circles (Medium Intensity): Moderate SAR momentum within 25-75% strength range, representing normal momentum development appropriate for standard positioning approaches and regular target expectations
• Faded Markers (Low Intensity): Weak SAR momentum below 25% strength range, suggesting caution and conservative positioning during minimal momentum conditions with increased exit sensitivity
⚠️IMPORTANT DISCLAIMERS AND RISK WARNINGS
Past Performance Limitations: The backtesting results presented represent hypothetical performance based on historical market data and do not guarantee future results. All trading involves substantial risk of loss. This strategy is provided for informational purposes and does not constitute financial advice. No trading strategy can guarantee 100% success or eliminate the risk of loss.
Users must approach trading with appropriate caution, never risking more than they can afford to lose.
Users are responsible for their own trading decisions, risk management, and compliance with applicable regulations in their jurisdiction.
MA Crossover Strategy with TP/SL (5 EMA Filter)How the Strategy Works on a 5-Minute Chart:
Data Input (5-Minute Candles):
Every single data point (candle) on your chart will represent 5 minutes of price action (Open, High, Low, Close for that 5-minute period).
All calculations (MAs, EMA, signals) will be based on these 5-minute price data points.
Moving Average Calculations:
Fast MA (10-period SMA): This will be the Simple Moving Average of the closing prices of the last 10 five-minute candles. It reacts relatively quickly to recent price changes.
Slow MA (30-period SMA): This will be the Simple Moving Average of the closing prices of the last 30 five-minute candles. It represents a slightly longer-term trend compared to the Fast MA.
5 EMA (5-period EMA): This is the Exponential Moving Average of the closing prices of the last 5 five-minute candles. Being an EMA, it gives more weight to the most recent 5-minute prices, making it very responsive to immediate price action.
Signal Generation (Entry Conditions):
Long Entry Signal:
The 10-period SMA crosses above the 30-period SMA (indicating a potential bullish shift in the short-to-medium term trend).
AND the current 5-minute candle's closing price is above the 5-period EMA (confirming that the immediate price momentum is also bullish and supporting the crossover).
If both conditions are met at the close of a 5-minute candle, a "Buy" signal is generated.
Short Entry Signal:
The 10-period SMA crosses below the 30-period SMA (indicating a potential bearish shift).
AND the current 5-minute candle's closing price is below the 5-period EMA (confirming immediate bearish momentum).
If both conditions are met at the close of a 5-minute candle, a "Sell" signal is generated.
Trade Execution:
When a signal is triggered, the strategy enters a trade (long or short) at the closing price of that 5-minute candle.
Immediately upon entry, it places two contingent orders:
Take Profit (Target): Set at 2% (by default) away from your entry price. For a long trade, it's 2% above; for a short trade, 2% below.
Stop Loss: Set at 1% (by default) away from your entry price. For a long trade, it's 1% below; for a short trade, 1% above.
The trade will remain open until either the Take Profit or Stop Loss price is hit by subsequent 5-minute candles.
Implications for Trading on a 5-Minute Chart:
Increased Trade Frequency: You will likely see many more signals and trades compared to higher timeframes (like 1-hour or daily charts). This means more potential opportunities but also more transaction costs (commissions, slippage).
Sensitivity to Noise: Lower timeframes are more prone to "market noise" – small, random price fluctuations that don't indicate a true trend. While the 5 EMA filter helps, some false signals might still occur.
Faster Price Action: Price movements can be very rapid on a 5-minute chart. Your take profit or stop loss levels might be hit very quickly, sometimes within the same or next few candles.
Parameter Optimization is Crucial: The default MA lengths (10, 30) and EMA (5) might not be optimal for every asset or market condition on a 5-minute chart. You'll need to backtest extensively and potentially adjust these lengths, as well as the targetPerc and stopPerc, to find what works best for the specific instrument you're trading.
Risk Management: The fixed percentage stop loss is vital on a 5-minute chart due to its volatility. Without it, a few unfavorable moves could lead to significant losses.
