D-BoT Alpha ReversalsHello traders, today I'm going to share with you a strategy that I use very frequently. I wanted to share this strategy that I use in my manual trades by translating it into code. I'm sharing it with you with completely open source code.
RSI of ROC: The indicator initially calculates RSI (Relative Strength Index) on ROC (Rate of Change). This is a method that tracks the rate of price change (ROC) over a certain period and applies it to the RSI calculation.
Adaptive RSI: The code then calculates the RSI for all periods between the minimum and maximum RSI lengths. It takes the average of these calculations and names it as avg_rsi66. In addition, it checks whether each RSI value exceeds the determined overbought and oversold limits.
Signal Triggers: If both RSI of ROC and avg_rsi66 are above or below the specified overbought or oversold levels and the difference between these two values is less than the specified threshold value (Extremities Sensitivity), a signal is triggered. In addition, the color of the bar is also checked: An overbought (sell) signal is triggered for a red bar and an oversold (buy) signal is triggered for a green bar.
Signal Visualization: Signals are shown on the chart at appropriate places with "Sell" or "Buy" shapes. Also, each of these conditions is defined as an alert condition.
The general purpose of this indicator is to determine the turning points of the market. Overbought and oversold signals are based on the idea that the price may turn from these areas. That is, a "Sell" signal indicates a turning point where the price may start to fall, while a "Buy" signal indicates a turning point where the price may start to rise.
These types of indicators usually have some weak points:
False Signals: Like any kind of technical analysis indicator, this indicator can also give false signals. That is, you may get a "Buy" or "Sell" signal but the price may not move in the expected direction.
Market Conditions: This indicator may perform better under certain market conditions. For example, a trend-following indicator usually works well in trending markets, but can be misleading in range-bound markets. This indicator too can perform better or worse in a particular market situation.
Parameter Selection: The choice of the parameters of the indicator (ROC and RSI lengths, overbought/oversold levels, etc.) can significantly affect the quality of the indicator signals. Parameters should be optimized for various assets and time frames.
In conclusion, it would be better to use this indicator not as a standalone trading system, but in conjunction with other technical analysis tools or fundamental analysis. Also, it is always beneficial to test a new trading strategy on past data or on a demo account before trading with real money."
Stay tuned for more of my original strategies :)
Happy trading...
Zmienność
Volume Tick Analysis and Order Blocks [Tcs] | ALGOThe indicator has been developed to provide the most complete vision possible of liquidity areas, highly traded past price levels, and how volume tick analysis affects price action.
It helps to draw on all the areas that generate a price move, or market inefficiency.
The indicator has different features:
- ORDER BLOCKS : The indicator draws different kinds of order blocks on the chart.
• Real valuable order blocks - where the price reaction is more probable. It's define by a calculation of the quantity tick volume exchanged between bulls and bears on a price level, which can create a candle event, such as engulfing candles. For this motivation the order blocks plotted will be a real valuable area.
The threshold can be adjusted based on the strategy's needs, in particular this set up has been added to adapt the strategy on different kind of asset. For Cryptocurrency for example the best threshold are between 0.5 and 1. The lower the value, the fewer order blocks will be plotted, but they will be more valuable. It's possible to show the volume exchanged, the percentage, and who controlled the valuable area, bulls or bears, on these order blocks.
For a better visualization, the order block will change color (more transparent) after it will be violated for the first time, and it will be deleted once the price will break trough it.
All order blocks can be extend
GENERAL OB VISUALIZATION
EXAMPLE OF TRADES ON OB
It's also possible to plot the footprint of past and invalidated order blocks on the chart, which can help to draw lines for future valuable areas.
• Secondary order blocks are less valuable order blocks where the probability of a price reaction is less. Usually, they work for small retracements and are more useful for scalpers. the concept is the same as Primary order blocks but without a too restricted calculation of tick volume exchanged
• LIQUIDITY GRABS: Liquidity grabs are plotted on candles that try to invalidate an order block, but high volumes move them to the opposite direction. They happen when opposite players try to move the market in the opposite direction. They are calculated only on primary order blocks.
A good entry usually is when a liquidity grab appear, the price come in the liquidity grab area to fry liquidity and price close again in the liquidity grab area.
• VOLUME VSA: All candles with high and above-average volume are plotted on the chart for both bull and bear volume. It highlights more than average volume, high volume, and extreme volume with different colors. This can help to spot good entries or detect beginning/end of a trend. For example abnormal high volume at the end of a big price movement, in the same direction, can define the end of a trend. If same situation of abnormal high volume, but in the opposite direction of the trend, could define the beginning of a market inversion.
• FAIR VALUE GAPS: It highlights all the inefficiencies of market moves, which can be used as retracement or price return areas. Here, they can be adjusted based on how effective they are adjusting the volume threshold. Bulls and bears FVG are defined in different colors. More effective FVG are plotted in less transparent colors, and you will find three levels of effectiveness.
Both OB and FVG will change color once the price retraces on them, and they will be removed when they are invalidated.
Please note that this indicator is for educational purposes only and should not be used for trading without further testing and analysis.
GKD-BT Multi-Ticker SCS Backtest [Loxx]The Giga Kaleidoscope GKD-BT Multi-Ticker SCS Backtest is a backtesting module included in Loxx's "Giga Kaleidoscope Modularized Trading System."
The Multi-Ticker SCS Backtest is a Solo Confirmation Simple backtest that allows traders to test single GKD-C confirmation indicators across 1-10 tickers. The purpose of this backtest is to enable traders to quickly evaluate GKD-C across hundreds of tickers within 30-60 minutes.
The backtest module supports testing with 1 take profit and 1 stop loss. It also offers the option to limit testing to a specific date range, allowing simulated forward testing using historical data. This backtest module only includes standard long and short signals. Additionally, users can choose to display or hide a trading panel that provides relevant information about the backtest, statistics, and the current trade. Traders can also select a highlighting treshold for Total Percent Wins and Percent Profitable, and Profit Factor.
To use this indicator:
1. Select the "Multi-ticker" option in the GKD-C Confirmation indicator.
2. Import 1-10 tickers into the GKD-C Confirmation indicator.
3. Import the same 1-10 indicators into the GKD-BT Multi-Ticker SCS Backtest.
4. Import the value "Input into NEW GKD-BT Multi-ticker Backtest" from the GKD-C Confirmation indicator into the GKD-BT Multi-Ticker SCS Backtest.
5. When importing tickers, ensure that you import the same type of tickers for all 1-10 tickers. For example, test only FX or Cryptocurrency or Stocks. Do not combine different tradable asset types.
6. Make sure that your chart is set to a ticker that corresponds to the tradable asset type. For cryptocurrency testing, set the chart to BTCUSDT. For Forex testing, set the chart to EURUSD.
This backtest includes the following metrics:
1. Net profit: Overall profit or loss achieved.
2. Total Closed Trades: Total number of closed trades, both winning and losing.
3. Total Percent Wins: Total wins, whether long or short, for the selected time interval regardless of commissions and other profit-modifying addons.
4. Percent Profitable: Total wins, whether long or short, that are also profitable, taking commissions into account.
5. Profit Factor: The ratio of gross profits to gross losses, indicating how much money the strategy made for every unit of money it lost.
6. Average Profit per Trade: The average gain or loss per trade, calculated by dividing the net profit by the total number of closed trades.
7. Average Number of Bars in Trade: The average number of bars that elapsed during trades for all closed trades.
Summary of notable settings:
Input Tickers separated by commas: Allows the user to input tickers separated by commas, specifying the symbols or tickers of financial instruments used in the backtest. The tickers should follow the format "EXCHANGE:TICKER" (e.g., "NASDAQ:AAPL, NYSE:MSFT").
Import GKD-C: Imports the "GKD-C" source, which provides signals or data for the backtest.
Initial Capital: Represents the starting account balance for the backtest, denominated in the base currency of the trading account.
Order Size: Determines the quantity of contracts traded in each trade.
Order Type: Specifies the type of order used in the backtest, either "Contracts" or "% Equity."
Commission: Represents the commission per order or transaction cost incurred in each trade.
**the backtest data rendered to the chart above uses $5 commission per trade and 10% equity per trade with $1 million initial capital. Each backtest result for each ticker assumes these same inputs. The results are NOT cumulative, they are separate and isolate per ticker and trading side, long or short**
Volatility Types included
The GKD system utilizes volatility-based take profits and stop losses. Each take profit and stop loss is calculated as a multiple of volatility. You can change the values of the multipliers in the settings as well.
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.
█ 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: Multi-Ticker SCS 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
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
GKD-M Baseline Optimizer
GKD-M Accuracy Alchemist
Volatility Impulse [VI] (Expo)█ Overview
The Volatility Impulse Indicator is a trading tool that measures the rate of change in an asset's price volatility. It helps identify potential market entry or exit points by signaling high or low volatility periods, which could suggest increased price momentum or consolidation. The Volatility Impulse Indicator will spike when the market is highly volatile, indicating a potential trend reversal or breakout. Conversely, when the market is less volatile, the indicator will be more stable, indicating a possible continuation of the current trend.
█ Trend Feature
Adding a Trend feature to the volatility line makes the indicator a complete trading tool that can be used in many strategies. This trend feature capitalizes on the historical price momentum to determine the current trend direction, providing additional context and insight for traders. The historical price momentum essentially encapsulates the speed and strength of price changes over a certain period. By integrating this information into the volatility indicator, traders gain a clearer picture of not only the magnitude of price fluctuations but also the prevailing trend in the market.
█ How is the Volatility Impulse calculated?
The Volatility Impulse Indicator is based on the principle that volatility precedes price action. Therefore, they are useful in predicting future price movements.
In this calculation, we're determining volatility by looking at the greatest absolute difference in price. This is done by comparing two separate things:
The highest price and a previous highest price: The code is essentially looking back at a specific number of bars ('Length') and finding the highest price during that period. It then compares that highest price to the previous highest price (found during the previous 'Length' period). The difference between these two gives a measure of how much the highest price is changing.
The lowest price and a previous lowest price: Similar to the highest price, the code looks back at a specific number of bars and finds the lowest price. It then compares that to the lowest price of the previous period. The difference gives a measure of how much the lowest price is changing.
The 'greatest absolute difference' means it's considering the magnitude of the change, not the direction. So whether the price is increasing or decreasing doesn't matter here - it's the size of the change that counts.
This way of calculating volatility is looking at how much the extreme values (the highest and lowest prices) are changing. If these values are changing a lot, it suggests that price movements are quite volatile. Conversely, if the highest and lowest prices aren't changing much, it suggests lower volatility.
█ How to use
Using the Volatility Impulse Indicator is relatively simple.
Identify potential trend reversals: When the Volatility Impulse Indicator shows a spike, indicating high volatility, traders can look for potential trend reversals.
Volatility Retracement: Volatility retracement takes place in the direction of the ongoing trend and can be interpreted as a sign that the retracement phase is over or exhausted. This typically indicates that enough retail stop losses have been triggered or that sufficient profit-taking has been completed. Both of these factors can contribute to a pause or a reversal in the trend's direction, leading to a temporary spike in volatility.
Volatility Breakout: Sudden and rapid price movement beyond a certain level may indicate a potential breakout. This event suggests that the price has enough momentum to continue its direction, marking the breakout as valid.
Trend Confirmation: When the volatility line reaches its upper or lower band, it indicates an increase in volatility, suggesting a strengthening trend. When the volatility line oscillates around the midline, it may indicate decreasing volatility and a weakening trend or consolidation.
Overbought/Oversold Conditions: If the volatility line is above the upper line, it could indicate an overbought situation, suggesting a potential reversal or pullback, a perfect place to take partial profit. Conversely, a volatility line below the lower band may signal an oversold market, suggesting a possible upward movement or reversal, a perfect place to take partial profit.
Manage risk: Traders can use the Volatility Impulse Indicator to manage risk. When the market is highly volatile, traders can place stop-loss orders at strategic levels, thereby limiting their risk.
█ Any Alert Function Call
Any alert function call allows traders to combine predefined alerts. For example, they can pair 'trend is positive' with 'volatility line spikes below the lower band,' and so on.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Adaptive Gaussian Moving AverageThe Adaptive Gaussian Moving Average (AGMA) is a versatile technical indicator that combines the concept of a Gaussian Moving Average (GMA) with adaptive parameters based on market volatility. The indicator aims to provide a smoothed trend line that dynamically adjusts to different market conditions, offering a more responsive analysis of price movements.
Calculation:
The AGMA is calculated by applying a weighted moving average based on a Gaussian distribution. The length parameter determines the number of bars considered for the calculation. The adaptive parameter enables or disables the adaptive feature. When adaptive is true, the sigma value, which represents the standard deviation, is dynamically calculated using the standard deviation of the closing prices over the volatilityPeriod. When adaptive is false, a user-defined fixed value for sigma can be input.
Interpretation:
The AGMA generates a smoothed line that follows the trend of the price action. When the AGMA line is rising, it suggests an uptrend, while a declining line indicates a downtrend. The adaptive feature allows the indicator to adjust its sensitivity based on market volatility, making it more responsive during periods of high volatility and less sensitive during low volatility conditions.
Potential Uses in Strategies:
-- Trend Identification : Traders can use the AGMA to identify the direction of the prevailing trend. Buying opportunities may arise when the price is above the AGMA line during an uptrend, while selling opportunities may be considered when the price is below the AGMA line during a downtrend.
-- Trend Confirmation : The AGMA can be used in conjunction with other technical indicators or trend-following strategies to confirm the strength and sustainability of a trend. A strong and steady AGMA line can provide additional confidence in the prevailing trend.
-- Volatility-Based Strategies : Traders can utilize the adaptive feature of the AGMA to build volatility-based strategies. By adjusting the sigma value based on market volatility, the indicator can dynamically adapt to changing market conditions, potentially improving the accuracy of entry and exit signals.
Limitations:
-- Lagging Indicator : Like other moving averages, the AGMA is a lagging indicator that relies on historical price data. It may not provide timely signals during rapidly changing market conditions or sharp price reversals.
-- Whipsaw in Sideways Markets : During periods of low volatility or when the market is moving sideways, the AGMA may generate false signals or exhibit frequent crossovers around the price, leading to whipsaw trades.
-- Subjectivity of Parameters : The choice of length, adaptive parameters, and volatility period requires careful consideration and customization based on individual preferences and trading strategies. Traders need to adjust these parameters to suit the specific market and timeframe they are trading.
Overall, the Adaptive Gaussian Moving Average can be a valuable tool in trend identification and confirmation, especially when combined with other technical analysis techniques. However, traders should exercise caution, conduct thorough analysis, and consider the indicator's limitations when incorporating it into their trading strategies.
Myfractalrange TrendHello Traders!
This is our main addition to MFR TradingView account: Myfractalrange Trend.
Many Trend signals exist out there, each trader has at some point created its own.
At Myfractalrange, we have developed a proprietary formula based on Price, Volume and Volatility.
Before going into how subscribers can use the Trend script, let't have a look at the different data point provided one by one:
- Bullish Trend: If the price of the asset is above this value, the asset is considered to be Bullish Trend. Default colour is green
- Bearish Trend : If the price of the asset is below this value, the asset is considered to be Bearish Trend. Default colour is red
- Neutral Trend: If the price of the asset is between the value of the Bullish Trend and the value of the Bearish Trend, the asset is considered to be Neutral Trend. Default colour is yellow
How does the script work?
The provided script is proprietary, so while the specific calculations and data sources cannot be disclosed, here is a broad explanation on how it works:
- It will retrieve the relevant data from the asset, could be volume, close, high, low, etc.
- The script will then check the length for the trend calculation of this specific asset and compute the Trend line
- From the value of this Trend line, we will then generate the "bullish" and "bearish" values
- The script will then plot the Bullish and Bearish values on the chart, the area between both being set as the Neutral area
How to use trend when trading?
When trading, understanding and utilising trends can be valuable for making informed trading decisions. Here are some key ways to use trends in trading:
- Trend Identification: Identifying the presence and direction of a trend is crucial
- Trend Following: One common trading strategy is trend following, which involves trading in the direction of the prevailing trend. In an uptrend, traders may look for opportunities to buy or go long, while in a downtrend, they may seek opportunities to sell or go short. Trend following strategies assume that trends are more likely to continue than reverse, and traders aim to capitalise on sustained price movements
- Trend Reversals: Identifying potential trend reversals is another approach. Traders may look for signs that a trend is losing momentum or showing signs of exhaustion. Traders may then consider taking contrarian positions or closing existing trades.
- Timing Entries and Exits: Trends can help with timing entry and exit points. Traders often aim to enter trades at favourable points within a trend, such as during pullbacks in an uptrend or rallies in a downtrend. This allows them to potentially capture favourable risk-to-reward ratios
- Risk Management: Incorporating trend analysis into risk management is crucial. Traders can set stop-loss orders or trailing stops based on the trend, aiming to protect profits or limit losses if the trend reverses. Position sizing can also be adjusted based on the strength or duration of a trend, with larger positions taken in strong, well-established trends
- Multiple Time Frame Analysis: Examining trends across different time frames can provide a broader perspective. Traders can look for alignment in trends across shorter-term and longer-term charts to gain confidence in their trading decisions. For example, a Trend on a daily chart may align with a Trend on a hourly chart, reinforcing the potential trading opportunity
The Myfractalrange Trend signal can be used for all the possibilities listed above
Here is an example of a Bullish Trend pattern: BTFD set up
Here is an example of a Bearish Trend pattern: STFR set up
Why use Trend in combination with other indicators, such as Hurst and probable Range?
Using Trend in combination with Hurst exponent and probable Range can provide traders with a more comprehensive view of market dynamics and potential trading opportunities. Here's how the three concepts can complement each other:
- Trend Analysis: Trend analysis helps identify the prevailing direction of the market. It provides insights into whether the market is in an uptrend (Bullish), downtrend (Bearish), or sideways consolidation (Neutral). Trend analysis helps traders align their positions with the dominant market direction, increasing the likelihood of successful trades
- Hurst exponent: Hurst exponent is a measure of the persistence or mean reversion characteristics of a time series. It provides insights into the strength and sustainability of price movements. Hurst momentum analysis helps traders understand whether the market is exhibiting trending behaviour or mean-reverting behaviour. It can help identify potential reversals or continuation patterns in the price action.
- Probable Range: The Range refers to the expected price range within which an asset is likely to fluctuate, in our case the MFR Ranges (normal and longer-term). It helps traders set realistic profit targets and stop-loss levels. By combining the probable range with the trend and the Hurst Exponent, traders can better gauge the potential extent of price movements and make more informed decisions regarding entry and exit points.
How to use these tools together?
- Confirmation and Confluence: Combining Trend with Hurst & Range can provide confirmation and confluence signals. For instance, when the trend analysis indicates an uptrend, Hurst confirms strong positive momentum and Range confirms the upside potential, it provides a stronger signal for potential bullish trades
- Timing Entries and Exits: The combination of trend analysis, Hurst and Range can assist in timing entry and exit points. For example, when trend analysis indicates an uptrend, traders can look for bullish signals from Hurst value and low of the MFR Range to identify potential entry points during pullbacks or periods of consolidation. Conversely, in a downtrend, bearish signals from Hurst at the top of the MFR Range can guide traders in identifying potential short-selling opportunities during corrective rallies
- Risk Management: The integration of trend analysis with Hurst and Range can also aid in risk management. Traders can adjust their stop-loss levels and profit targets based on the strength of the trend, its strength and its Range. Tighter stop-loss levels can be set when both trend analysis, Hurst value and Range are aligned, indicating a higher probability of trend continuation. Conversely, wider stop-loss levels may be used when conflicting signals or weakening trends are observed
By combining Trend analysis, Hurst exponent and MFR probable Range, traders can gain a more comprehensive understanding of the market's behaviour and make more informed trading decisions.
It's important to note that while Trend is a useful tool, it should not be relied upon solely for making trading decisions. It's recommended to use it in conjunction with other technical analysis tools and consider other factors such as market conditions, risk management, and fundamental analysis. Remember that the momentum indicator is just one tool among many, and it's important to consider other factors such as volume, momentum, volatility, and overall market conditions when making trading decisions. Additionally, using stop-loss orders and proper risk management techniques is crucial to mitigate potential losses.
We hope that you will find these explanations useful, please contact us by private message for access.
Enjoy!
DISCLAIMER: No sharing, copying, reselling, modifying, or any other forms of use are authorised. This script is strictly for individual use and educational purposes only. This is not financial or investment advice. Investments are always made at your own risk and are based on your personal judgement. Myfractalrange is not responsible for any losses you may incur. Please invest wisely.
Ultimate Trend ChannelThe "Ultimate Trend Channel" indicator is a comprehensive trend analysis tool that calculates and displays a series of upper and lower bands based on user-defined input lengths. It uses linear regression and standard deviation to determine these bands for each of the 21 different group lengths. The indicator then computes the averages of these upper and lower bands, as well as the average of all the bands combined.
The visualization on the chart includes the plotting of the average upper and lower bands, with the space between these bands shaded for easy visualization of the overall trend. Additionally, the average of all the bands, referred to as the "Ultimate Trend Line," is also plotted on the chart.
This indicator provides a robust way of assessing market trends and volatility over varying periods, which can be extremely useful for both short-term and long-term trading strategies.
BBWAS Enhanced with Webhook Alerts and Money ManagementThe Enhanced BBWAS Indicator is a powerful tool designed to identify breakouts in the price of a security or asset. It utilizes Bollinger Bands, which consist of three lines: the upper band, the lower band, and the middle band (or basis). These bands help define the expected price range within which the asset is likely to fluctuate.
When the price breaks above the upper band or below the lower band, it indicates a potential breakout. A bullish breakout occurs when the price closes above the upper band, while a bearish breakout occurs when the price closes below the lower band.
In this enhanced version of the indicator, several new features have been added to provide more flexibility and functionality:
Webhook Alerts: Traders now have the ability to configure webhook alerts to trigger a bot or any external system. This allows for timely notifications when a breakout occurs, enabling automated actions or manual intervention as desired.
Multiple Moving Average Types: The indicator now supports different types of moving averages for increased customization. Traders can choose from popular moving average types such as Simple Moving Average (SMA), Exponential Moving Average (EMA) and Weighted Moving Average (WMA). This enables users to experiment and find the moving average type that best suits their trading strategy.
Money Management: To assist traders in managing risk, a money management feature has been incorporated into the indicator. It calculates the optimal position size or number of units to purchase for each trade, considering the desired risk per trade. By specifying a maximum risk per trade, traders can ensure that their position sizes are adjusted accordingly, helping to maintain risk control in their trading activities.
Dear traders, while we strive to provide you with the best trading tools and resources, we want to remind you to exercise caution and diligence in your investing decisions.
It is important to always do your own research and analysis before making any trades. Remember, the responsibility for your investments ultimately lies with you.
Happy trading!
Volatility Compression BreakoutThe Volatility Compression Breakout indicator is designed to identify periods of low volatility followed by potential breakout opportunities in the market. It aims to capture moments when the price consolidates within a narrow range, indicating a decrease in volatility, and anticipates a subsequent expansion in price movement. This indicator can be applied to any financial instrument and timeframe.
When the close price is above both the Keltner Middle line and the Exponential Moving Average (EMA), the bars are colored lime green, indicating a potential bullish market sentiment. When the close price is positioned above the Keltner Middle but below the EMA, or below the Keltner Middle but above the EMA, the bars are colored yellow, signifying a neutral or indecisive market condition. Conversely, when the close price falls below both the Keltner Middle and the EMA, the bars are colored fuchsia, suggesting a potential bearish market sentiment.
Additionally, the coloration of the Keltner Middle line and the EMA provides further visual cues for assessing the trend. When the close price is above the Keltner Middle, the line is colored lime green, indicating a bullish trend. Conversely, when the close price is below the Keltner Middle, the line is colored fuchsia, highlighting a bearish trend. Similarly, the EMA line is colored lime green when the close price is above it, representing a bullish trend, and fuchsia when the close price is below it, indicating a bearish trend.
Parameters
-- Compression Period : This parameter determines the lookback period used to calculate the volatility compression. A larger value will consider a longer historical period for volatility analysis, potentially capturing broader market conditions. Conversely, a smaller value focuses on more recent price action, providing a more responsive signal to current market conditions.
-- Compression Multiplier : The compression multiplier is a factor applied to the Average True Range (ATR) to determine the width of the Keltner Channels. Increasing the multiplier expands the width of the channels, allowing for a larger price range before a breakout is triggered. Decreasing the multiplier tightens the channels and requires a narrower price range for a breakout signal.
-- EMA Period : This parameter sets the period for the Exponential Moving Average (EMA), which acts as a trend filter. The EMA helps identify the overall market trend and provides additional confirmation for potential breakouts. Adjusting the period allows you to capture shorter or longer-term trends, depending on your trading preferences.
How Changing Parameters Can Be Beneficial
Modifying the parameters allows you to adapt the indicator to different market conditions and trading styles. Increasing the compression period can help identify broader volatility patterns and major market shifts. On the other hand, decreasing the compression period provides more precise and timely signals for short-term traders.
Adjusting the compression multiplier affects the width of the Keltner Channels. Higher multipliers increase the breakout threshold, filtering out smaller price movements and providing more reliable signals during significant market shifts. Lower multipliers make the indicator more sensitive to smaller price ranges, generating more frequent but potentially less reliable signals.
The EMA period in the trend filter helps you align your trades with the prevailing market direction. Increasing the EMA period smoothes out the trend, filtering out shorter-term fluctuations and focusing on more sustained moves. Decreasing the EMA period allows for quicker responses to changes in trend, capturing shorter-term price swings.
Potential Downsides
While the Volatility Compression Breakout indicator can provide valuable insights into potential breakouts, it's important to note that no indicator guarantees accuracy or eliminates risk. False breakouts and whipsaw movements can occur, especially in volatile or choppy market conditions. It is recommended to combine this indicator with other technical analysis tools and consider fundamental factors to validate potential trade opportunities.
Making It Work for You
To maximize the effectiveness of the Volatility Compression Breakout indicator, consider the following:
-- Combine it with other indicators : Use complementary indicators such as trend lines, oscillators, or support and resistance levels to confirm signals and increase the probability of successful trades.
-- Practice risk management : Set appropriate stop-loss levels to protect your capital in case of false breakouts or adverse price movements. Consider implementing trailing stops or adjusting stop-loss levels as the trade progresses.
-- Validate with price action : Analyze the price action within the compression phase and look for signs of building momentum or weakening trends. Support your decisions by observing candlestick patterns and volume behavior during the breakout.
-- Backtest and optimize : Test the indicator's performance across different timeframes and market conditions. Optimize the parameters based on historical data to find the most suitable settings for your trading strategy.
Remember, no single indicator can guarantee consistent profitability, and it's essential to use the Volatility Compression Breakout indicator as part of a comprehensive trading plan. Regularly review and adapt your strategy based on market conditions and your trading experience. Monitor the indicator's performance and make necessary adjustments to parameter values if the market dynamics change.
By adjusting the parameters and incorporating additional analysis techniques, you can customize the indicator to suit your trading style and preferences. However, it is crucial to exercise caution, conduct thorough analysis, and practice proper risk management to increase the likelihood of successful trades. Remember that no indicator can guarantee profits, and continuous learning and adaptation are key to long-term trading success.
Average Variation Bands OscillatorSimilar to how a donchian% of channel helps to visualize trend and volatility, this tool helps identify those same characteristics, if the oscillator is generally above the 50 mark, it is considered to be trending upwards, and the reverse if it is generally bellow 50.
Vola2vola Volatility indicatorHello everyone!
For those who remember vola2vola volatility script, we are excited to bring it back within the Myfractalrange Tradingview account!
As you know, Volatility is very important to assets and many people use it to trade. This tool automate the calculation of the volatility of every asset as well as provide an estimated value of its "Trend" and "Trade".
The idea in this script is to allow users to have an idea of the current volatility regime of the asset he is monitoring: Is its volatility Bullish or Bearish Trend, Bearish or Bullish Trade? Is its volatility compressed to a previous minimum value? Is it about to experience a spike in volatility? Let's dig together into how this tool works and how you could integrate it into your trading shall we?
What are the data provided by the script, let see one by one:
- Volatility: The value of what vola2vola calls the "synthetic" volatility of the asset is calculated using a custom formula based on the VIXFIX formula. Default colour is blue
- Trade : Trade is generated using an arbitrary and fixed look back period, it acts as a short-term trend. It will give the user the possibility to know if the volatility of the asset is still trending short-term or not. Default colour is black
- Trend: Trend is also generated using an arbitrary and fixed look back period (20 times the one used for Trade), it acts as a longer-term trend. It works the same way as Trade and will give the user the possibility to know if the volatility of the asset is trending a longer-term basis or not. Default colours are: red when the Trend of the volatility of the asset is Bearish and green when the Trend of the volatility of the asset is Bullish
- 52-weeks high & low: Based on the highest and lowest value of Volatility in the past 52 weeks, a 52-weeks high and a 52-weeks low will be marked. These values usually acts as Resistance and Support for volatility. Default colour is black and they are in dotted lines
Here are some of the questions you need to know the answer to before using this script:
- How do you define a "Bullish/Bearish volatility Trade"? Volatility is Bullish Trade is when Volatility is above Trade and it is Bearish Trade when volatility is below Trade
- How do you define a "Bullish/Bearish volatility Trend"? Volatility is Bullish Trend is when Volatility is above Trend and it is Bearish Trend when volatility is below Trend
- On which time frame should i use this script? You want to use the Daily time frame. Although, for short term moves in the volatility space, users could monitor the Hourly timeframe
Understanding the volatility of an asset, along with the bullish or bearish nature of its Trade and Trend, is crucial for investors. Assets with decreasing volatility tend to appreciate in value, while those with increasing volatility tend to depreciate. Therefore, we recommend investors be aware of the volatility situation of the asset they are holding in their portfolio.
Here are the different scenarios that you will encounter on a Daily timeframe and how to interpret them:
- Volatility is below Trade & Trend and Volatility is Bearish Trade and Trend: It is the most Bullish set up for the price of an asset
- Volatility is above Trade & Trend and Volatility is Bullish Trade and Trend: It is the most Bearish set up for the price of an asset
- Any other set up suggests uncertainty, caution is therefore recommended
These are some cases that you could experience while using this script:
1) Bearish Volatility set up on a daily timeframe:
In this example using SPY, when its Volatility is Bearish Trend on a daily timeframe, the price of SPY tends to appreciate
2) Bullish Volatility set up on a daily timeframe:
In this example using SPY, when its Volatility is Bullish Trend on a daily timeframe, the price of SPY tends to depreciate
We hope that you will find these explanations useful, please contact us by private message for access.
Enjoy!
DISCLAIMER: No sharing, copying, reselling, modifying, or any other forms of use are authorised. This script is strictly for individual use and educational purposes only. This is not financial or investment advice. Investments are always made at your own risk and are based on your personal judgement. Myfractalrange is not responsible for any losses you may incur. Please invest wisely.
Volatility SpeedometerThe Volatility Speedometer indicator provides a visual representation of the rate of change of volatility in the market. It helps traders identify periods of high or low volatility and potential trading opportunities. The indicator consists of a histogram that depicts the volatility speed and an average line that smoothes out the volatility changes.
The histogram displayed by the Volatility Speedometer represents the rate of change of volatility. Positive values indicate an increase in volatility, while negative values indicate a decrease. The height of the histogram bars represents the magnitude of the volatility change. A higher histogram bar suggests a more significant change in volatility.
Additionally, the Volatility Speedometer includes a customizable average line that smoothes out the volatility changes over the specified lookback period. This average line helps traders identify the overall trend of volatility and its direction.
To enhance the interpretation of the Volatility Speedometer, color zones are used to indicate different levels of volatility speed. These color zones are based on predefined threshold levels. For example, green may represent high volatility speed, yellow for moderate speed, and fuchsia for low speed. Traders can customize these threshold levels based on their preference and trading strategy.
By monitoring the Volatility Speedometer, traders can gain insights into changes in market volatility and adjust their trading strategies accordingly. For example, during periods of high volatility speed, traders may consider employing strategies that capitalize on price swings, while during low volatility speed, they may opt for strategies that focus on range-bound price action.
Adjusting the inputs of the Volatility Speedometer indicator can provide valuable insights and flexibility to traders. By modifying the inputs, traders can customize the indicator to suit their specific trading style and preferences.
One input that can be adjusted is the "Lookback Period." This parameter determines the number of periods considered when calculating the rate of change of volatility. Increasing the lookback period can provide a broader perspective of volatility changes over a longer time frame. This can be beneficial for swing traders or those focusing on longer-term trends. On the other hand, reducing the lookback period can provide more responsiveness to recent volatility changes, making it suitable for day traders or those looking for short-term opportunities.
Another adjustable input is the "Volatility Measure." In the provided code, the Average True Range (ATR) is used as the volatility measure. However, traders can choose other volatility indicators such as Bollinger Bands, Standard Deviation, or custom volatility measures. By experimenting with different volatility measures, traders can gain a deeper understanding of market dynamics and select the indicator that best aligns with their trading strategy.
Additionally, the "Thresholds" inputs allow traders to define specific levels of volatility speed that are considered significant. Modifying these thresholds enables traders to adapt the indicator to different market conditions and their risk tolerance. For instance, increasing the thresholds may highlight periods of extreme volatility and help identify potential breakout opportunities, while lowering the thresholds may focus on more moderate volatility shifts suitable for range trading or trend-following strategies.
Remember, it is essential to combine the Volatility Speedometer with other technical analysis tools and indicators to make informed trading decisions.
Buy/Sell singal with RSI, MA, RSI DIV1. Overview
I'll explain a strategy that uses the simple but powerful technical analysis techniques RSI, MA, VOLUME, and RSI Divergence to identify Buy/Sell signals. This strategy utilizes Pine Script of TradingView.
Our strategy is based on four fundamental components.
- RSI (Relative Strength Index)
- MA (Moving Averages)
- Volume
- RSI Divergence
By using these four techniques together, we can find potential buy/sell signals.
2. Code Interpretation
To understand the TradingView code we used, let's examine each section one by one.
- RSI Calculation: RSI is a technical indicator that measures the relative strength of a price and is often used to identify overbought or oversold conditions. In our code, we calculate the RSI over a given period.
- Moving Averages: This code calculates short-term and long-term moving averages. Moving averages represent the average price over a specific period and are used to identify long-term price trends. Their intersections are considered potential buy/sell signals.
- RSI Divergence: RSI divergence represents a mismatch between the price trend and the RSI trend. It occurs when the price makes a new high or low, but the RSI does not. This indicates a weakening of the price trend and is considered a powerful signal of trend change.
- Volume Calculation: When the volume of transactions occurring during a specific period is x times more than the average volume, it is considered a signal of trend change.
- Buy/Sell Signals: Each technical indicator generates buy or sell signals. These signals are marked as labels on the chart. In our strategy, buy/sell signals are generated when the RSI exits overbought or oversold zones, when the moving averages cross, and when RSI divergence occurs.
3. Signal Detection
3.1 Buy/Sell Signals Using RSI
The RSI indicator has a value between 0 and 100, with values over 70 generally considered the overbought zone and those under 30 as the oversold zone.
A buy signal is generated when the RSI rises from the oversold zone.
Conversely, a sell signal is generated when the RSI falls from the overbought zone.
3.2 Detecting Buy/Sell Signals Through Moving Average Crosses
Moving averages help identify price trends.
A buy signal is generated when the short-term moving average crosses the long-term moving average upward.
Conversely, a sell signal is generated when the short-term moving average crosses the long-term moving average downward.
The color of each bar can be changed according to each signal.
3.3 Detecting Signals When Volume is X Times Higher Than Average
When the volume is x times higher than average, a marker is placed above each bar.
A green marker is displayed when the buy volume is high.
A red marker is displayed when the sell volume is high.
4. Conclusion
This technical analysis strategy is very simple but effective. Using RSI, moving averages, volume, and RSI divergence, you can find effective buy/sell signals.
By leveraging Pine Script in TradingView, you can easily apply this strategy and find signals in real-time.
Always remember that risk management is important in trading. This strategy may not be effective in all market conditions, so always use appropriate risk management strategies alongside it.
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1. 개요
간단하지만 강력한 기술적 분석 전략인 RSI, MA, VOLUME, RSI Divergence를 사용한 Buy/Sell 신호 표시 전략에 대해 설명드리겠습니다.
이 전략은 트레이딩뷰의 Pine Script를 활용합니다.
우리의 전략은 다음 네 가지 기본 구성 요소에 기반합니다.
- RSI (Relative Strength Index)
- MA (Moving Averages)
- 거래량
- RSI Divergence
이 네 가지 기법을 함께 사용하여 잠재적인 매수/매도 신호를 찾아냅니다.
2. 코드 해석
우리가 사용한 트레이딩뷰 코드를 이해하기 위해 각 섹션을 하나씩 살펴보겠습니다.
RSI 계산: RSI는 가격의 상대적 강도를 측정하는 기술적 지표로, 과매수 또는 과매도 조건을 식별하는 데 자주 사용됩니다. 우리의 코드에서는 주어진 기간 동안의 RSI를 계산합니다.
이동평균: 이 코드에서는 단기 이동평균과 장기 이동평균을 계산합니다. 이동평균은 특정 기간 동안의 가격 평균을 나타내며, 가격의 장기적인 트렌드를 식별하는 데 사용됩니다. 이들의 교차점은 잠재적인 매수/매도 신호로 간주됩니다.
RSI Divergence: RSI 다이버전스는 가격 추세와 RSI 추세 사이의 불일치를 나타냅니다. 가격이 새로운 고점 또는 저점을 만들면서 RSI가 그렇지 않을 때 발생합니다. 이것은 가격 트렌드의 약화를 나타내며 강력한 트렌드 변화 신호로 간주됩니다.
VOLUME 계산 : 특정 구간동안의 평균 거래량보다 x배 이상 거래량이 많이 발생하였을때 트렌드 변화 신호로 간주됩니다.
매수/매도 신호: 각 기술적 지표는 매수 또는 매도 신호를 생성합니다. 이러한 신호는 차트에 라벨로 표시됩니다. 우리의 전략에서는 RSI가 과매도 또는 과매수 영역을 벗어날 때, 이동평균이 교차할 때, 그리고 RSI 다이버전스가 발생할 때 매수/매도 신호를 생성합니다.
3. 신호 감지
3.1 RSI를 활용한 매수/매도 신호
RSI 지표는 0에서 100 사이의 값을 가지며, 일반적으로 70 이상은 과매수 영역, 30 이하는 과매도 영역으로 간주됩니다.
과매도 영역에서 RSI가 상승하면 매수 신호가 생성됩니다.
반대로, 과매수 영역에서 RSI가 하락하면 매도 신호가 생성됩니다.
3.2 이동평균 교차로 매수/매도 신호 감지
이동평균은 가격의 트렌드를 식별하는 데 도움이 됩니다.
단기 이동평균이 장기 이동평균을 상승으로 교차하면 매수 신호가 생성됩니다.
반대로, 단기 이동평균이 장기 이동평균을 하락으로 교차하면 매도 신호가 생성됩니다.
각 신호에 따라 해당 봉의 색깔도 변경할 수 있습니다.
3.3 평균 거래량보다 x배 이상 거래량이 발생했을 때 신호 감지
평균 거래량보다 x배 이상 거래량이 발생했을 때 각 봉 위에 표시가 됩니다.
매수 거래량이 많을 경우 초록색으로 표시가 됩니다.
매도 거래량이 많을 경우 빨간색으로 표시가 됩니다.
* 모든 기준이 되는 수치와 색상은 설정에서 개인의 취향에 맞게 설정 가능합니다.
4. 결론
이 기술적 분석 전략은 매우 간단하지만 효과적입니다. RSI, 이동평균, 거래량, RSI 다이버전스를 사용하여 효과적인 매수/매도 신호를 찾을 수 있습니다.
트레이딩뷰의 Pine Script를 활용하여 이 전략을 쉽게 적용하고, 실시간으로 신호를 찾아낼 수 있습니다.
항상 거래에 있어서는 리스크 관리가 중요하다는 점을 명심하십시오. 이 전략이 모든 시장 상황에 효과적이지는 않을 수 있으므로, 항상 적절한 리스크 관리 전략을 함께 사용해야 합니다.
[TTI] NDR 63-Day QQQ-QQEW ROC% SpreadWelcome to the NDR 63-Day QQQ-QQEW ROC% Spread script! This script is a powerful tool that calculates and visualizes the 63-day Rate of Change (ROC%) spread between the QQQ and QQEW tickers. This script is based on the research conducted by Ned Davis Research (NDR), a renowned name in the field of investment strategy.
⚙️ Key Features:
👉Rate of Change Calculation: The script calculates the 63-day Rate of Change (ROC%) for both QQQ and QQEW tickers. The ROC% is a momentum oscillator that measures the percentage price change over a given time period.
👉Spread Calculation: The script calculates the spread between the ROC% of QQQ and QQEW. This spread can be used to identify potential trading opportunities.
👉Visual Representation: The script plots the spread on the chart, providing a visual representation of the ROC% spread. This can help traders to easily identify trends and patterns.
👉Warning Lines: The script includes warning lines at +600 and -600 levels. These lines can be used as potential thresholds for trading decisions.
Usage:
To use this script, simply add it to your TradingView chart. The script will automatically calculate the ROC% for QQQ and QQEW and plot the spread on the chart. You can use this information to inform your trading decisions.
🚨 Disclaimer:
This script is provided for educational purposes only and is not intended as investment advice. Trading involves risk and is not suitable for all investors. Please consult with a financial advisor before making any investment decisions.
🎖️ Credits:
This script is based on the research conducted by Ned Davis Research (NDR). All credit for the underlying methodology and concept goes to NDR.
Opal - Aggr.Crypto█ OVERVIEW
The Multi-Exchange Crypto Aggregator is a unique concept ticker that gathers up to 10 tickers into one. A new OPAL Chart is created as an indicator, with its own candles and information. This information is meant to be interpreted as average information in order to reduce noise from a single ticker only. Everything is automated between assets. Our script will always check and ensure that data is received for calculations; otherwise, invalid tickers are ignored. This version is designed for Crypto Perpetual markets.
█ HOW DATA SLIPPAGE/DIFFERENCE IMPACT NOISE
This new average ticker aims to reduce noise in your candles and their live movements, avoiding most of the minor/last-second spikes, especially when they don't happen on every desired exchange at the same time. Our candles have different behaviors and highlight close-open slippage/gaps, as it seems to provide a strong reaction. Those gaps represent average slippage.
█ HOW TO USE
This should help you visualize market behaviors. Volume pressures are the origin of a lot of misunderstood things. Data analysis and observations show that makers target liquidity on both sides. Time and sessions have their own logic and will always need experience, as it is basically a gigantic Tetris game. Anyway, this should help with timing confirmations or bring confidence.
█ FEATURES
Aggregated (Tickers) Candles ▸ Aggregated OHLC candles, the idea behind the script. Set desired tickers to automate in settings. Value and Var% are displayed right next to the current candle.
Aggr. Dynamics/Levels ▸ Plot some strong levels as landmarks calculated on modified price, from Volume Weighted Average Price (VWAP) to Daily aggregated Open Price. The previous day's key level is included.
Aggr. Data Markers ▸ Plot some key markers on the chart, such as Open Pressure gaps, or estimated 3-scale liquidation bubbles with 2 confirmation modes (using different filters).
Aggr. Averages ▸ Plot up to 3 averages or HLC channels for visual ease.
█ SIGN
All of our contents are shared for educational purposes only.
Wishing you success;
OPAL - Strive for Greatness
Standard Deviation Buy Sell Signals [UOI]The "Standard Deviation Buy Sell Signals" which is a Mean and VWAP Deviation Super Pack that includes many additional features is an advanced technical analysis tool designed to assist traders in making well-informed decisions in the financial markets. It incorporates various functions and calculations to provide a comprehensive analysis of price movements, trends, and potential trading opportunities in different timeframes. The Super Pack combines elements of volume-weighted average price (VWAP), mean calculation on multiple time frames, standard deviation signals and bands, overbought and oversold signals, measures of central tendency, and multiple time frame calculations of mean reversion. A truly unique indicator.
Here is the details of the supper pack and what is included:
1. VWAP (Volume-Weighted Average Price): The Mean and VWAP Deviation Super Pack includes VWAP, which calculates the average price of a security weighted by its trading volume. This helps traders identify the average price at which a significant amount of trading activity has occurred and can serve as a reference point for determining whether the current price is overvalued or undervalued.
2. Standard Deviation Signals and Bands: The Super Pack incorporates standard deviation signals and bands to measure the volatility of price movements. By calculating the standard deviation of price data, it identifies price levels that deviate significantly from the average, indicating potential overbought or oversold conditions. The standard deviation bands provide visual boundaries that help traders assess the likelihood of a price reversal or continuation. The bands are hidden to avoid too many lines but you can enable them in the setting. See image below:
3. Overbought and Oversold Signals: Using the standard deviation calculations, the Mean and VWAP Deviation Super Pack generates overbought and oversold signals. These signals indicate when a security's price has moved to an extreme level, suggesting a potential reversal or correction in the near future. Traders can use these signals to time their entries or exits in the market. You can change the RSI number in the setting to get more or less signals.
4. Measures of Central Tendency: The Super Pack incorporates measures of central tendency, such as the mean, median, or mode, to provide a sense of the average or typical price behavior. These measures help traders identify the prevailing trend or price direction and assess the likelihood of a trend continuation or reversal. This provide reassurance of whether price is too far from center in multiple time frames.
5. Multiple Time Frame Calculation of Mean Reversion: The Mean and VWAP Deviation Super Pack employs multiple time frame calculations to identify mean reversion opportunities. It compares the current price with the historical average price over different time periods, allowing traders to identify situations where the price has deviated significantly from its mean and is likely to revert back to its average value. This can be useful for swing trading or short-term trading strategies.
By combining these various functions, the Mean and VWAP Deviation Super Pack provides traders with a comprehensive analysis of price dynamics, trend strength, potential reversals, and mean reversion opportunities. It aids in making more informed trading decisions and improving overall trading performance.
Why is this super pack indicator an essential trading strategy for every trader:
Standard deviation and mean reversion are valuable tools for traders, especially when the market is in a ranging phase. A ranging market is characterized by price movements that oscillate between defined support and resistance levels, with no clear trend in either direction. In such market conditions, standard deviation and mean reversion strategies can be particularly effective. Here's why:
1. Standard Deviation: Standard deviation is a statistical measure that quantifies the volatility or dispersion of price data around its average. In a ranging market, where prices tend to fluctuate within a certain range, standard deviation can help identify overbought and oversold levels. When the price reaches the upper end of the range, the standard deviation bands widen, indicating higher volatility and a potential selling opportunity. Conversely, when the price reaches the lower end of the range, the bands narrow, suggesting lower volatility and a potential buying opportunity. Traders can use these signals to anticipate price reversals and take advantage of the predictable nature of ranging markets.
2. Mean Reversion: Mean reversion is a concept that suggests prices tend to move back toward their average or mean over time. In a ranging market, where prices repeatedly move between support and resistance levels, mean reversion strategies can be highly effective. By identifying when the price has deviated significantly from its mean, traders can anticipate a potential reversal back toward the average. When the price reaches extreme levels, indicating overbought or oversold conditions, traders can enter positions in the opposite direction, expecting the price to revert to its mean. Mean reversion strategies can be implemented using various indicators, including Bollinger Bands, moving averages, or standard deviation bands.
3. Range Boundaries: In a ranging market, the upper and lower boundaries of the price range serve as reliable reference points for traders. Standard deviation and mean reversion strategies capitalize on the repetitive nature of price movements within these boundaries. Traders can set their entry and exit points based on the standard deviation bands or mean reversion signals to take advantage of price reversals near the range boundaries. By properly identifying and reacting to these levels, traders can profit from the price oscillations within the range.
4. Risk Management: Standard deviation and mean reversion strategies provide traders with clear entry and exit points, allowing for effective risk management. By placing stop-loss orders beyond the range boundaries or the standard deviation bands, traders can limit their potential losses if the price continues to move against their positions. Additionally, by taking profits near the opposite range boundary or when the price reverts back to the mean, traders can secure their gains and maintain a disciplined approach to trading.
Standard deviation and mean reversion strategies offer traders a systematic approach to capitalize on ranging markets. But the cherry on top is the overbought and oversold signals:
The concept of overbought and oversold levels is widely used in technical analysis to identify potential reversals in price trends. Typically, indicators like the Relative Strength Index (RSI) are employed to determine when an asset may be overbought or oversold. However, you have developed a unique approach by incorporating an interactive variable with RSI and Average True Range (ATR) to create a distinct overbought and oversold signal. Here's why this approach stands out:
1. Divergence: Your approach introduces a divergence concept by combining RSI and ATR. Traditionally, overbought and oversold signals rely solely on RSI readings. However, by considering the interaction between RSI and ATR, you bring a new dimension to these signals. The divergence occurs when the RSI indicates overbought conditions while simultaneously ATR crosses over into bearish territory, or when the RSI signals oversold conditions along with ATR crossing over into bullish territory. This divergence adds an extra layer of confirmation to the overbought and oversold signals.
2. Reduced False Signals: The incorporation of ATR in conjunction with RSI helps filter out false signals that may occur during trending market conditions or short squeezes. Trend days or periods of increased volatility can cause RSI to remain in overbought or oversold territory for an extended period, generating numerous signals that may not be reliable. By considering the crossing of ATR into bearish or bullish territory, your approach adds a dynamic element to the signal generation process. This interactive variable helps ensure that the overbought and oversold signals are not solely based on RSI getting hot, reducing the likelihood of false signals during trending or volatile periods.
3. Improved Timing: The interaction between RSI and ATR provides a more nuanced approach to timing overbought and oversold signals. By waiting for the ATR to confirm the RSI signal, you introduce an additional condition that enhances the precision of the timing. The bearish or bullish crossover of ATR serves as a confirmation that market conditions align with the overbought or oversold signal indicated by RSI. This combined approach allows for more accurate entry or exit points, increasing the potential profitability of trades.
4. Customization and Adaptability: By creating this interactive variable with RSI and ATR, you have developed a customizable approach that can be adapted to different trading styles and preferences. Traders can adjust the sensitivity of the signals by modifying the parameters of the RSI and ATR. This flexibility allows for a personalized trading experience and enables traders to align the signals with their specific risk tolerance and market conditions.
This approach to overbought and oversold signals utilizing RSI and ATR introduces a unique perspective to technical analysis. By incorporating divergence and interactive variables, you enhance the reliability of these signals while reducing false readings. This approach provides improved timing and adaptability, making it a valuable tool for traders seeking to identify potential reversals in price trends with greater accuracy and confidence.
HOW to avoid fake signals?
When it comes to trading with standard deviation as a strategy, it's important to note that on extreme trend days, this indicator may generate false signals. This occurs because standard deviation is primarily designed to measure volatility and deviations from the mean in a range-bound market. During strong trending periods, the price tends to move in one direction with minimal deviations, rendering the standard deviation less effective.
To avoid trading based solely on standard deviation during extreme trend days, it is advisable to incorporate additional indicators that can provide insights into the stock's trend or squeeze conditions. These indicators can help determine whether the market is experiencing a strong trend or a squeeze, allowing you to avoid false signals generated by standard deviation.
By utilizing complementary indicators such as trend-following indicators (e.g., moving averages, trendlines) or volatility indicators (e.g., Bollinger Bands), you can gain a more comprehensive understanding of the market environment. These indicators can help confirm whether the stock is in a trending phase or experiencing a squeeze, helping you avoid entering trades solely based on standard deviation during these extreme trend days.
In summary, while standard deviation is a valuable tool in range-bound markets, it may produce unreliable signals on extreme trend days. By incorporating other indicators that provide insights into the stock's trend or squeeze conditions, traders can better assess the market environment and avoid false signals generated by standard deviation during these periods. This approach enhances the overall effectiveness and accuracy of trading strategies, leading to more informed and profitable decision-making.
Trend-Range-Indicator - 3hrThe Trend and Range Indicator is a tool based on median calculation and volatility analysis. It helps identify trends and ranges in price charts. This indicator highlights consolidation areas.
Only work in 3 hours timeframe
N-Rho To Noise (Reinforcement Learning)N-Rho To Noise is a ratio of 2 components. Rho is my own calculation of a signal that is differenced (force time series stationary, allowing for more predictability) and its relation to a unit of a measure of noise. N is the amount of times it is differenced. Using a simplified q-learning reinforcement learning agent, the length of the ratio is calibrated to its optimal value.
- Purple indicates the undifferenced signal is above the RMSE error bands
- Red indicates both the differenced and undifferenced signals are above the threshold for a strong positive deviation, suggesting a short
- Blue indicates the undifferenced signal is below the RMSE error bands
- Green indicates both the differenced and undifferenced signals are below the threshold for a negative strong deviation, suggesting a long
- Strong long signal when you have both an undifferenced Rho and differenced Rho giving you local agreement (blue bar followed by green)
- Strong short signal when you have an undifferenced and differenced Rho giving you identical signals (purple bar followed by red)
Optimal length: the parameter of the length that the model configures to be the best parameter
Optimal reward: the reward corresponding to the optimal length (green=strong value, orange=intermediate strength, red=poor)
Average reward: the average reward of the set of lengths used over all episodes (green=strong value, orange=intermediate strength, red=poor)
Cumulative reward: the sum of all the rewards
Variance: a measure of how varied the data is (too much variance can suggest it cannot generalize too well to unseen data)
Cumulative TICK Trend[Pt]Cumulative TICK Trend indicator is a comprehensive trading tool that uses TICK data to define the market's cumulative trend. Trend is shown on ATR EMA bands, which is overlaid on the price chart. Cumulative TICK shown on the bottom pane is for reference only.
Main features of the Cumulative TICK Trend Indicator include:
Selectable TICK Source: You have the flexibility to choose your preferred TICK source from the following options, depending on the market you trade: USI:TICK, USI:TICKQ, USI:TICKI, and USI:TICKA.
TICK Data Type: Select the type of TICK data to use, options include: Close, Open, hl2, ohlc4, hlc3.
Simple Moving Average (SMA): You can choose to apply an SMA on the calculated Cumulative TICK values with a customizable length.
Average True Range (ATR) Bands: It provides the option to display ATR bands with adjustable settings. This includes the ATR period, EMA period, source for the ATR calculation, and the ATR multiplier for the upper band.
Trend Color Customization: You can customize the color of the bull and bear trends according to your preference.
Smooth Line Option: This setting allows you to smooth the ATR Bands with a customizable length.
How it Works:
This indicator accumulates TICK data during market hours (9:30-16:00) as per the New York time zone and resets at the start of a new session or the end of the regular session. This cumulative TICK value is then used to determine the trend.
The trend is defined as bullish if the SMA of cumulative TICK is equal to or greater than zero and bearish if it's less than zero. Additionally, this indicator plots the ATR bands, which can be used as volatility measures. The Upper ATR Band and Lower ATR Band can be made smoother using the SMA, according to the trader's preference.
The plot includes two parts for each trend: a stronger color (Red for bear, Green for bull) when the trend is ongoing, and a lighter color when the trend seems to be changing.
Remember, this tool is intended to be used as part of a comprehensive trading strategy. Always ensure you are managing risk appropriately and consulting various data sources to make informed trading decisions.
Z Algo (Expo)█ Overview
Z Algo (Expo) is a sophisticated and user-friendly trading tool designed to meet the needs of both novice and seasoned traders. With its real-time signals, trend analysis, and risk management capabilities, this tool can be a valuable addition to any trader's toolkit.
█ Main Features & How to Use
Buy/Sell signals: Z Algo provides real-time buy and sell signals, which assist traders in identifying the most opportune moments to enter or exit a trade.
Strong Buy/Sell signals: In addition to regular buy and sell signals, the tool also offers strong buy and sell signals. These are generated when the market conditions align with a higher probability of a significant price movement.
Sniper Signals: This feature is specifically designed for contrarian traders who look to exploit temporary market inefficiencies or take advantage of price reversals. When enabled, Sniper Signals identify potential market turning points, offering traders the opportunity to profit from sharp price fluctuations.
Reversal Cloud: The Reversal Cloud is a unique visual representation of the market's potential trend reversals. It offers traders an easy-to-understand display of changing market dynamics, enabling them to quickly identify potential entry and exit points based on trend reversals.
Support and Resistance (S/R) Levels: Z Algo automatically calculates and displays support and resistance levels on the chart. These are crucial price points where buying or selling pressure may change, providing valuable insights for traders looking to enter or exit positions based on these levels.
Trend Tracker: This feature helps traders monitor and analyze the prevailing market trend. Trend Tracker identifies and highlights the direction of the trend, allowing traders to align their strategies accordingly and increase their chances of success.
Trend Background Color: To improve the user experience and simplify the interpretation of market data, Z Algo changes the chart's background color based on the identified trend direction. This visual cue makes it easier for traders to recognize bullish or bearish trends at a glance.
Bar Coloring: In addition to the trend background color, Z Algo also provides bar coloring for both contrarian and trend bars. This feature helps traders visualize price movements and trends more effectively, enabling them to identify potential opportunities for both trend-following and contrarian trading strategies.
Risk Management: The tool incorporates risk management features that help traders to protect their capital and maximize potential returns. Users can set stop-loss and take-profit levels, as well as customize their risk exposure according to their individual preferences and trading style.
█ Calculations
█ What are the Buy/Sell signals based on?
The Buy/Sell signals use volatility and price range with a weighting function that can help reduce lag and respond faster to recent price changes. The function gives more weight to the most recent volatility values and absolute price changes, making the algorithm more responsive to changes in volatility and price moves. Using a model that factors in both price changes and volatility gives a bias toward more recent data. This advanced approach to trading signal generation incorporates the concepts of trend following and mean reversion while accounting for changing market volatility.
Traditional systems often use fixed parameters, which may not adapt quickly to changes in market conditions. This can lead to late entries or exits, potentially reducing profitability or increasing risk. Our algorithm uses a weighting function to give more importance to recent volatility values, and absolute price changes can make these signals more responsive. This is especially useful in dynamic markets where price swings and volatility can change rapidly.
Adapting to Recent Price Changes: Markets can often exhibit trending behavior over certain periods. By weighing recent price changes more heavily, the model can quickly identify and react to the emergence of new trends. This can lead to earlier entries in a new trend, potentially increasing profitability.
Adapting to Recent Volatility Changes: Markets can shift from low to high volatility regimes (and vice versa) quite rapidly. A model that gives more weight to recent volatility can adapt its signals to these changing conditions. For example, in high volatility conditions, the model might generate fewer signals to reduce the risk of false breakouts. Conversely, in low volatility conditions, the model might generate more signals to capitalize on trending behavior.
Adaptive Trading: The approach inherently leads to an adaptive trading system. Rather than using fixed parameters, the system can adjust its behavior based on recent market activity. This can lead to a more robust system that performs well across different market conditions.
█ What are the Sniper signals (contrarian signals) based on?
Our contrarian signals are based on deviation from the expected value. The algorithm quantifies the amount of variation or dispersion in a set of values. Non-expected values are the fundamental core of the signal generation process.
█ Reversal Cloud Calculation
The cloud uses the information of how much the price fluctuates over a specific time period and updates its equilibrium value automatically at new price changes. The price changes are used to predict what will happen next, and the band adapts accordingly. The algorithm assumes that past price changes can predict future market behavior.
█ Support and Resistance (S/R) Levels Calculation
The support and resistance levels use historical overbought and oversold levels combined with a weighted atr function to predict future support and resistance areas. This calculation can potentially give traders a great heads-up on where the price may find support and resistance at.
█ Trend & Bar coloring Calculation
Trend calculations with dynamic events are key in ever-changing markets. The main idea of the calculation method is to find the mathematical function that best fits the data points, by minimizing the sum of the squares of the vertical distances of each data point from the equilibrium. The outcome is a function that finds the best mathematical description of that data. Hence the trend output may vary depending on the asset and timeframe. A unique approach where the same settings can give different results.
█ Risk Management Calculation
The risk management system is not unique in itself and contains everything that can help traders to manage their risk, such as different types of stop losses, Take Profits calculations.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Open Interest Suite [Aggregated] - By LeviathanThis script is an all-in-one indicator that uses aggregated Open Interest data to plot OI candles, Open Interest Delta, OI x rVOL, and OI RSI. It also includes tools such as an OI Distribution profile, large OI increase/decrease coloring, a Stats Screener, and much more.
You can select and have the script plot the following:
- Open Interest in the form of OHLC candles
- Open Interest Delta in the form of a histogram
- Open Interest x Relative Volume in the form of a histogram
- Open Interest RSI in the form of a line
Additional features include:
- OI Distribution Profile (It shows the distribution of open interest in the visible range on y axis. This makes it easier to identify when Open Interest is relatively high or low and at which values most of the action took place)
- Stats screener (The screener includes the real-time net Open Interest value, Rekt Longs/Rekt Shorts based on large OI decreases and Aggressive Longs/Shorts based on large OI increases)
- Coloring (You can color OI Delta nodes, background and chart candles based on large OI increases/decreases)
- more
Instructions for the settings will be provided in the tooltips shortly.
Full credit goes to @KioseffTrading for the profile generation code.
Master Supertrend [Trendoscope]Are you a fan of supertrend? Me too!! Here is a supertrend indicator which provides multiple variation options to chose from.
🎲 Introduction
Supertrend is a popular technical indicator used by traders to identify potential trend reversals and determine entry and exit points in financial markets. It is a trend-following indicator that combines price and volatility to generate its signals. Generally supertrend is calculated based on ATR and multiplier value which is used for calculation of stops. In these adaptions, we look to provide few variations to classical methods.
🎲 Variations
Following variations are provided in the form of settings.
🎯 Range Type
Instead of ATR, different types of ranges can be used for stop calculation. Here is the complete list used in the script.
Plus/Minus Range - Calculates plus range and minus range for each candle and uses them for different sides of stop calculation
Ladder ATR - Based on the existing concept of Ladder ATR defined in Supertrend-Ladder-ATR
True Range - True range derived from standard function ta.tr
Standard Deviation - Standard deviation of close prices
🎯 Applied Calculation
In standard ATR, rma of TR is used for calculations. But, the application calculation provides option to users to use different mechanisms. It can be a type of moving average or few other types of calculations.
Available values are
sma
ema
hma
rma
wma
high
median
medianHigh (Highest of the last N medians)
medianLow (Lowest of the last N medians)
🎯 Other options
Few other options provided are
Use Close Price - If selected stops are calculated based on the close price instead of high/low prices
Wait for Close If selected, change of supertrend direction is calculated based on close price instead of high/low prices
Diminishing Stop Distance - When selected, stop distance for the trend direction can only reduce and cannot increase. This option is useful for keeping the tight stops on strong trends.
🎯 Plus Minus Range
One of the range type used is Plus/Minus Range. What it means and how are these ranges calculated? Let's have a look.
Plus Range is an upward movement of a candle from its last price or open price whichever is lower.
Minus Range is a downward movement of a candle from its last price or open price whichever is higher.
This divides True Range into two separate range for positive and negative side.
Here are the simple settings in nutshell which reflects the same.
custom Bollinger bands with filters - indicator (AS)-----------Description-------------
This indicator is basically Bollinger bands with many ways to customize. It uses highest and lowest values of upper and lower band for exits. I think something is wrong with the script but cant find any mistakes – most probably smoothing. The ATR filter is implemented but is working incorrectly. In code you can also turn it into strategy but I do not recommend it for now as it is not ready yet.
So this is my first script and I am looking for any advice, ideas to improve this script, sets of parameters, markets to apply, logical mistakes in code or any ideas that you may have. Indicator was initially designed for EURUSD 5MIN but I would be interested in other ideas.
-----------SETTINGS--------------
---START - In starting settings we can choose
Line 1: what parts to use BB/DC/ATR
Line 2: what parts to plot on chart
Line 3 Whether or not apply smoothing to BB or ATR filter
Line 4 Calculate deviation for BB from price or Moving average
Line 5 Fill colors and plot other parts for debug (overlay=false)
Line 6:( for strategy) – enable Long/Short Trades
---BB and DC – here we modify Bollinger bands and Donchian
Line 1: Length and type of BB middle line and also length of DC from BB
Line 2: Length and type of BB standard deviation and multiplier
Line 3: Length and type of BB smoothing and %width for BB filter
---ATR filter – (not ready fully yet)
Line 1: type and length of ATR
Line 2: threshold and smoothing value of ATR
---DATE and SESSION
Line 1: apply custom date or session?
Line 2: session hours settings
Line 3:Custom starting date
Line 4: Custom Ending date
-----------HOW TO USE--------------
We open Long if BB width is bigger than threshold and close when upper band is no longer highest in the period set. Exact opposite with Short
