White NoiseThe "White Noise" indicator is designed to visualize the dispersion of price movements around a moving average, providing insights into market noise and potential trend changes. It highlights periods of increased volatility or noise compared to the underlying trend.
Code Explanation:
Inputs:
mlen: Input for the length of the noise calculation.
hlen: Input for the length of the Hull moving average.
col_up: Input for the color of the up movement.
col_dn: Input for the color of the down movement.
Calculations:
ma: Calculate the simple moving average of the high, low, and close prices (hlc3) over the specified mlen period.
dist: Calculate the percentage distance between the hlc3 and the moving average ma, then scale it by 850. This quantifies the deviation from the moving average as a value.
sm: Smooth the calculated dist values using a weighted moving average (WMA) twice, with different weights, and subtract one from the other. This provides a smoothed representation of the dispersion.
Coloring:
col_wn: Determine the color of the bars based on whether dist is positive or negative and whether it's greater or less than the smoothed sm value. This creates color-coded columns indicating upward or downward movements with varying opacity.
col_switch: Define the color for the current trend state. It switches color when the smoothed sm crosses above or below its previous value, indicating potential trend changes.
col_switch2: Define the color for the horizontal line that separates the two trend states. It switches color based on the same crossover and crossunder conditions as col_switch.
Plots:
plot(dist): Plot the dispersion values as columns with color defined by col_wn.
plot(sm): Plot the smoothed dispersion line with a white color and thicker linewidth.
plot(sm ): Plot the previous smoothed dispersion value with a lighter white color to create a visual distinction.
Usage:
This indicator can help traders identify periods of increased market noise, visualize potential trend reversals, and assess the strength of price movements around the moving average. The colored columns and smoothed line offer insights into the ebb and flow of market sentiment, aiding in decision-making.
ps. This can be used as a long-term TPI component if you dabble in Modern Portfolio Theory (MPT)
Recommended for timeframes on the 1D or above:
Średnie kroczące
AlpHay : ToolKitToolKit:
First Impressions for Securities; (like crime scene investigators) 🧐
Our first job is to understand "What did happen here?" (historically, like Price Ranges or Price Performances) 🤔
Secondly, we try to figure out "where are we now?" (like common indicators or Moving Averages) 🤔
Then "What was the chain of events?" (macro, local, fundamentals, shorts, etc.)
Note: There are a lot of useful scripts out there, but If you want to see my approach for "Fundamentals" or "Finra Short Report" scripts, have a look.
Now we have a Clue. 😎
Includes;
1. Daily Metrics (Price performance, Price Difference, Volume, Trade)
2. Historic Price Performances
3. Historic Price ranges
4. RSI and MACD (you can change) Indicators for four "Time Frame" (you can change also)
5. Moving Averages (also shows daily values on the chart)
* Easy to customize.
* You can be positioned where ever you need. (be careful about overlays)
* You can turn on/off tables for your daily usage.
* You can flip Horizontally for some of the tables.
* Always look at tooltips (mouse over for Averages etc.)
I hope you enjoy it.
Disclaimer and Warning!
* Do not forget this is my Interpolation of the data sets. You can't invest in relying on this indicator. This is just a visual representation of the data sets.
* Just be careful what you wish for. And search for anomalies.
// ToDO List.
* Pre/Post Market Price and Volume
MACD HIstgramMA signl CrossingThis indicator highlights points where the MACD's Signal and Simple Moving Average of Histogram cross as entry points.
By incorporating the Simple Moving Average of the Histogram, it aims to avoid false entries during MACD and Signal crosses when volatility is low.
However, since it employs the Simple Moving Average of the Histogram, the appearance of entry points is less frequent and lagging compared to the cross of MACD and Signal.
Trend Confirmation StrategyThe profitability and uniqueness of a trading strategy depend on various factors including market conditions, risk management, and the strategy's ability to capitalize on price movements. I'll describe the strategy provided and highlight its potential benefits and differences compared to other strategies:
Strategy Overview:
The provided strategy combines three technical indicators: Supertrend, MACD, and VWAP. It aims to identify potential entry and exit points by confirming trend direction and considering the proximity to the VWAP level. The strategy also incorporates stop-loss and take-profit mechanisms, as well as a trailing stop.
Unique Aspects and Potential Benefits:
Trend Confirmation: The strategy uses both Supertrend and MACD to confirm the trend direction. This dual confirmation can increase the likelihood of accurate trend identification and filter out false signals.
VWAP Confirmation: The strategy considers the proximity of the price to the VWAP level. This dynamic level can act as a support or resistance and provide additional context for entry decisions.
Adaptive Stop Loss: The strategy sets a stop-loss range, which helps provide some tolerance for minor price fluctuations. This adaptive approach considers market volatility and helps prevent premature stop-loss triggers.
Trailing Stop: The strategy incorporates a trailing stop mechanism to lock in profits as the trade moves in the desired direction. This can potentially enhance profitability during strong trends.
Partial Profit Booking: While not explicitly implemented in the provided code, you could consider booking partial profits when the MACD shows a crossover in the opposite direction. This aspect could help secure gains while still keeping exposure to potential further price movements.
Key Differences from Other Strategies:
Dual Indicator Confirmation: The combination of Supertrend and MACD for trend confirmation is a unique aspect of this strategy. It adds an extra layer of filtering to enhance the accuracy of entry signals.
Dynamic VWAP: Incorporating the VWAP level into the decision-making process adds a dynamic element to the strategy. VWAP is often used by institutional traders, and its inclusion can provide insights into the market sentiment.
Adaptive Stop Loss and Trailing: The strategy's use of an adaptive stop-loss range and a trailing stop can help manage risk and protect profits more effectively during changing market conditions.
Partial Profit Booking: The suggestion to consider partial profit booking upon MACD crossovers in the opposite direction is a practical approach to secure gains while staying in the trade.
Caution and Considerations:
Backtesting: Before deploying any strategy in real trading, it's crucial to thoroughly backtest it on historical data to understand its performance under various market conditions.
Risk Management: While the strategy has built-in risk management mechanisms, it's essential to carefully manage position sizes and overall portfolio risk.
Market Conditions: No strategy works well in all market conditions. It's important to be flexible and adjust the strategy or refrain from trading during particularly volatile or unpredictable periods.
Continuous Monitoring: Even though the strategy includes automated components, continuous monitoring of the trades and market conditions is necessary.
Adaptability: Markets can change over time. Traders need to be prepared to adapt the strategy as necessary to stay aligned with evolving market dynamics.
HighLowBox+220MAs[libHTF]HighLowBox+220MAs
This is a sample script of libHTF to use HTF values without request.security().
import nazomobile/libHTFwoRS/1
HTF candles are calculated internally using 'GMT+3' from current TF candles by libHTF .
To calcurate Higher TF candles, please display many past bars at first.
The advantage and disadvantage is that the data can be generated at the current TF granularity.
Although the signal can be displayed more sensitively, plots such as MAs are not smooth.
In this script, assigned ➊,➋,➌,➍ for htf1,htf2,htf3,htf4.
HTF candles
Draw candles for HTF1-4 on the right edge of the chart. 2 candles for each HTF.
They are updated with every current TF bar update.
Left edge of HTF candles is located at the x-postion latest bar_index + offset.
DMI HTF
ADX/+DI/DI arrows(8lines) are shown each timeframes range.
Current TF's is located at left side of the HighLowBox.
HTF's are located at HighLowBox of HTF candles.
The top of HighLowBox is 100, The bottom of HighLowBox is 0.
HighLowBox HTF
Enclose in a square high and low range in each timeframe.
Shows price range and duration of each box.
In current timeframe, shows Fibonacci Scale inside(23.6%, 38.2%, 50.0%, 61.8%, 76.4%)/outside of each box.
Outside(161.8%,261.8,361.8%) would be shown as next target, if break top/bottom of each box.
In HTF, shows Fibonacci Level of the current price at latest box only.
Boxes:
1 for current timeframe.
4 for higher timeframes.(Steps of timeframe: 5, 15, 60, 240, D, W, M, 3M, 6M, Y)
HighLowBox TrendLine
Draw TrendLine for each HighLow Range. TrendLine is drawn between high and return high(or low and return low) of each HighLowBox.
Style of TrendLine is same as each HighLowBox.
HighLowBox RSI
RSI Signals are shown at the bottom(RSI<=30) or the top(RSI>=70) of HighLowBox in each timeframe.
RSI Signal is color coded by RSI9 and RSI14 in each timeframe.(current TF: ●, HTF1-4: ➊➋➌➍)
In case of RSI<=30, Location: bottom of the HighLowBox
white: only RSI9 is <=30
aqua: RSI9&RSI14; <=30 and RSI9RSI14
green: only RSI14 <=30
In case of RSI>=70, Location: top of the HighLowBox
white: only RSI9 is >=70
yellow: RSI9&RSI14; >=70 and RSI9>RSI14
orange: RSI9&RSI14; >=70 and RSI9=70
blue/green and orange/red could be a oversold/overbought sign.
20/200 MAs
Shows 20 and 200 MAs in each TFs(tfChart and 4 Higher).
TFs:
current TF
HTF1-4
MAs:
20SMA
20EMA
200SMA
200EMA
Gaussian Average Rate Oscillator
Within the ALMA calculation, the Gaussian function is applied to each price data point within the specified window. The idea is to give more weight to data points that are closer to the center and reduce the weight for points that are farther away.
The strategy calculates and compares two different Rate of Change (ROC) indicators: one based on the Arnaud Legoux Moving Average (ALMA) and the other based on a smoothed Exponential Moving Average (EMA). The primary goal of this strategy is to identify potential buy and sell signals based on the relationship between these ROC indicators.
Here's how the strategy logic works
Calculating the ROC Indicators:
The script first calculates the ROC (Rate of Change) of the smoothed ALMA and the smoothed EMA. The smoothed ALMA is calculated using a specified window size and is then smoothed further with a specified smoothing period. The smoothed EMA is calculated using a specified EMA length and is also smoothed with the same smoothing period.
Comparing ROCs:
The script compares the calculated ROC values of the smoothed ALMA and smoothed EMA.
The color of the histogram bars representing the ROC of the smoothed ALMA depends on its relationship with the ROC of the smoothed EMA. Green indicates that the ROC of ALMA is higher, red indicates that it's lower, and black indicates equality.
Similarly, the color of the histogram bars representing the ROC of the smoothed EMA is determined based on its relationship with the ROC of the smoothed ALMA, they are simply inversed so that they match.
With the default color scheme, green bars indicate the Gaussian average is outperforming the EMA within the breadth and red bars mean it's underperforming. This is regardless of the rate of average price changes.
Generating Trade Signals:
Based on the comparison of the ROC values, the strategy identifies potential crossover points and trends. Buy signals could occur when the ROC of the smoothed ALMA crosses above the ROC of the smoothed EMA. Sell signals could occur when the ROC of the smoothed ALMA crosses below the ROC of the smoothed EMA.
Additional Information:
The script also plots a zero rate line at the zero level to provide a reference point for interpreting the ROC values.
In summary, the strategy attempts to capture potential buy and sell signals by analyzing the relationships between the ROC values of the smoothed ALMA and the smoothed EMA. These signals can provide insights into potential trends and momentum shifts in the price data.
Golden Transform The Golden Transform Oscillator contains multiple technical indicators and conditions for making buy and sell decisions. Here's a breakdown of its components and what it's trying to achieve:
Strategy Setup:
The GT is designed to be plotted on the chart without overlaying other indicators.
Rate of Change (ROC) Calculation:
The Rate of Change (ROC) indicator is calculated with a specified period ("Rate of Change Length").
The ROC measures the percentage change in price over the specified period.
Hull Modified TRIX Calculation:
The Hull Modified TRIX indicator is calculated with a specified period ("Hull TRIX Length").
The Hull MA (Moving Average) formula, a modified WMA, is used to calculate a modified TRIX indicator, which is a momentum oscillator.
Hull MA Calculation:
A Hull Moving Average (Hull MA) is calculated as an entry filter.
Fisher Transform Calculation:
The Fisher Transform indicator is calculated to serve as a preemptive exit filter.
It involves mathematical transformations of price data to create an oscillator that can help identify potential reversals. The Fisher Transform is further smoothed using a Hull Moving Average (HMA).
Conditions and Signals:
Long conditions are determined based on crossovers between ROC and TRIX, as well as price relative the the MA. Short conditions are inversed.
Exit Conditions:
Exit conditions are defined for both long and short positions.
For long positions, the strategy exits if ROC crosses under TRIX, or if the smoothed Fisher Transform crosses above a threshold and declines. Once again, short conditions are the inverse.
Visualization and Plotting:
The script uses background colors for entry and shapes for exits to highlight different levels and conditions for the ROC/TRIX correlation.
It plots the Fisher Transform values and a lag trigger on the chart.
Overall, this script is a complex algorithm that combines multiple technical indicators and conditions to generate trading signals and manage positions in the financial markets. It aims to identify potential entry and exit points based on the interplay of the mentioned indicators and conditions.
Ultimate Momentum OscillatorThe Ultimate Momentum Oscillator is a tool designed to help traders identify the current trend direction and the momentum of the prices.
This oscillator is composed of one histogram and one line, paired with the two overbought and the two oversold levels.
The histogram is a trend-based algorithm that allows the user to read the market bias with multiple trend lengths combined.
The line is a momentum-based formula that allows traders to identify potential reversal and the speed of the price.
This tool can be used to:
- Identify the current trend direction
- Identify the momentum of the price
- Identify oversold and overbought levels
Gaussian Detrended ReversionThis strategy, titled "Gaussian Detrended Reversion Strategy," aims to identify potential price reversals using the customized Gaussian Detrended Price Oscillator (GDPO) in combination with smoothed price cycles.
Key Elements of the Strategy:
GDPO Calculation: The strategy first calculates the Detrended Price Oscillator (DPO) by comparing the close price to an Exponential Moving Average (EMA) of a specified period. This calculation helps identify short-term price cycles by detrending the price data.
Gaussian Smoothing: The DPO values are then smoothed using the Arnaud Legoux Moving Average (ALMA), applying a Gaussian smoothing technique. This smoothed version of the DPO is intended to filter out noise and provide a clearer picture of price trends.
Entry and Exit Conditions: The strategy defines conditions for both long and short entry points as well as exit points. It looks for specific crossover events between the smoothed GDPO and its lagged version. The strategy enters a long position when the smoothed GDPO crosses above the lag and is negative, and exits the long position when the smoothed GDPO crosses below the lag or the zero line. Similarly, the strategy enters a short position when the smoothed GDPO crosses below the lag and is positive, and exits the short position when the smoothed GDPO crosses above the lag or the zero line.
Visualization: The smoothed GDPO and its lag are plotted on the chart using distinct colors. The zero line is also displayed as a reference point. Additionally, the chart background changes color when the strategy enters a long or short position. Cross markers are also plotted at the crossover points as exit cues.
Overall, this strategy aims to capture potential price reversals using the GDPO and Gaussian smoothing, with specific entry and exit conditions to guide trading decisions.
EMA X Oscillator
This indicator combines elements of the Exponential Moving Average (EMA) crossover and Rate of Change (ROC), generating a solid simple tool for technical analysis.
Overall, this script creates an oscillator by calculating the Rate of Change between two Exponential Moving Averages (Fast and Slow) based on the chosen smoothing methods and lengths. The oscillator helps identify potential trends. It offers customization options for the types of smoothing and other parameters, making it versatile for various strategies.
Custom EMA from X Days AgoThis is an indicator to plot the selected EMA value from X days ago on today's candle.
Or it will helps to plot the previous candle's EMA value on current candle.
LNL Trend SystemLNL Trend System is an ATR based day trading system specifically designed for intra-day traders and scalpers. The System works on any chart time frame & can be applied to any market. The study consist of two components - the Trend Line and the Stop Line. Trend System is based on a special ATR calculation that is achieved by combining the previous values of the 13 EMA in relation to the ATR which creates a line of deviations that visually look similar to the basic moving average but actually produce very different results ESPECIALLY in sideways market.
Trend Line:
Trend Line is a simple line which is basically a fast gauge represented by the 13 EMA that can change the color based on the current trend structure defined by multiple averages (8,13,21,34 EMAs). Trend Line is there to simply add the confluence for the current trend. Colors of the line are pretty much self-explanatory. Whenever the line turns red it states that the current structure is bearish. Vice versa for green line. Gray line represents neutral market structure.
Stop Line:
Stop Line is an ATR deviaton line with special calculation based on the previous bar ATRs and position of the price in relation to the current and previous values of 13 EMA. As already stated, this creates an ATR deviation marker either above or below the price that trails the price up or down until they touch. Whenever the price comes into the Stop Line it means it is making an ATR expansion move up or down .This touch will usually resolve into a reaction (a bounce) which provides trade opportunities.
Trend Bars:
When turned ON, Trend Bars can provide additional confulence of the current trend alongside with the Trend Line color. Trend Bars are based on the DMI and ADX indicators. Whenever the DMI is bearish and ADX is above 20 the candles paint themselfs red. And vice versa applies for the green candles and bullish DMI. Whenever the ADX falls below the 20, candles are netural (Gray) which means there is no real trend in place at the moment.
Trend Mode:
There are total of 5 different trend modes available. Each mode is visualizing different ATR settings which provides either aggressive or more conservative approach. The more tigher the mode, the more closer the distance between the price and the Stop Line. First two modes were designed for slower markets, whereas the "Loose" and "FOMC" modes are more suitable for products with high volatility.
Trend Modes:
1. Tight
Ideal for the slowest markets. Slowest market can be any market with unusually small average true range values or just simply a market that does have a personality of a "sleeper". Tight Mode can be also used for aggresive entries in the most ridiculous trends. Sometimes price will barely pullback to the Trend Line not even the Stop Line.
2. Normal
Normal Mode is the golden mean between the modes. "Normal" provides the ideal ATR lengths for the most used markets such as S&P Futures (ES) or SPY, AAPL and plenty of other highly popular stocks. More often than not, the length of this mode is respected considering there is no breaking news or high impact market event scheduled.
3. Loose
The "Loose" mode is basically a normal mode but a little bit more loose. This mode is useful whenever the ATRs jump higher than usual or during the days of highly anticipated news events. This mode is also better suited for more active markets such as NQ futures.
4. FOMC
The FOMC mode is called FOMC for a reason. This mode provides the maximum amount of wiggle room between the price and the Stop Line. This mode was designed for the extreme volatility, breaking news events or post-FOMC trading. If the market quiets down, this mode will not get the Stop Line touch as frequently as othete modes, thus it is not very useful to run this on markets with the average volatlity. Although never properly tested, perhaps the FOMC mode can find its value in the crypto market?
5. The Net
The net mode is basically a combination of all modes into one stop line system which creates "the net" effect. The Net provides the widest Stop Line zone which can be mainly appreciated by traders that like to use scale-in scale-out methods for their trading. Not to mention the visual side of the indicator which looks pretty great with the net mode on.
HTF (Higher Time Frame) Trend System:
The system also includes additional higher time frame (HTF) trend system. This can be set to any time frame by manual HTF mode. HTF mode set to "auto" will automatically choose the best suitable higher time frame trend system based on how appropriate the aggregation is. For everything below 5min the HTF Trend System will stay on 5min. Anything between 5-15min = 30min. 30min - 120min will turn on the 240min. 180min and higher will result in Daily time frame. Anything above the Daily will result in Weekly HTF aggregation, above W = Monthly, above M = Quarterly.
Background Clouds:
In terms of visualization, each trend system is fully customizable through the inputs settings. There is also an option to turn on/off the background clouds behind the stop lines. These clouds can make the charts more clean & visible.
Tips & Tricks:
1. Different Trend Modes
Try out different modes in different markets. There is no one single mode that will fit to everyone on the same type of market. I myself actually prefer more Loose than the Normal.
2. Stop Line Mirroring
Whenever the Stop Lines start to mirror each other (there is one above the price and one below) this means the price is entering a ranging sideways market. It does not matter which Stop Line will the price touch first. They can both be faded until one of them flips.
3. Signs of the Ranging Market
Watch out for signs of ranging market. Whenever the Trend System looses its colors whether on trend line or trend bars, if everything turns neutral (gray) that is usually a solid indication of a range type action for the following moments. Also as already stated before, the Stop Line mirroring is a good sign of the range market.
4. Trailing Tool, Trend System as an Additional Study?
In case you are not a fan of the colorful green / red charts & candles. You can switch all of them off and just leave the Stop Line on. This way you can use the benefits of the trend system and still use other studies on top of that. Similarly as the Parabolic SAR is often used.
5. The Flip Setup
One of my favorite trades is the Flip Setup on the 5min charts. Whenever the Stop Line is broken , the very first opposing touch after the Trend System flips is a usually a highly participated touch. If there is a strong reaction, this means this is likely a beginning of a new trend. Once I am in the position i like to trail the Stop Line on the 1min charts.
Hope it helps.
EMA Deviation ReboundThe " EMA Deviation Rebound " indicator I've created utilizes calculations involving the standard deviation of closing prices and exponential moving averages (EMA) to generate a line. The color of this line changes based on whether the EMA value is above or below the current closing price. This can be interpreted as an indicator for potential buy or sell signals:
Buy Signal: If the price crosses the indicator from bottom to top, this can be considered a buy signal. This could indicate that the price has overcome a resistance and a potential upward movement may be forthcoming.
Sell Signal: If the price crosses the indicator from top to bottom, this could serve as a sell signal. This might suggest that the price has broken a support downward and possibly indicates an impending downward movement.
The indicator is named "EMA Deviation Rebound" because I use it to identify potential resistance and support levels. When the price rebounds at the indicator, this could signify a price movement in the opposite direction.
It's important to use such indicators in conjunction with other analysis techniques and market information to make informed trading decisions.
Price Depth Analysis to the MAHello Traders! Today, I bring you an indicator that can greatly assist you in your trading. This indicator aims to analyze the Expansion and Contraction process of the price in relation to a moving average. We refer to "Expansion" when the price moves away from the moving average; a significant expansion could signal that the asset is in a strong trend. On the other hand, when we refer to "Contraction", it's when the price approaches or returns to the moving average. A contraction could signal that the asset is losing momentum and might be preparing for a trend change or consolidation.
To use the indicator, the first thing you need to do is define the type of analysis you want to perform (from the indicator settings) whether you want to evaluate prices above the moving average or below. You should also select the type of moving average and its period.
The indicator will search for the maximum distance in all the chart bars, which will be represented with a yellow label.
From that value, the indicator will generate a certain number of proportional levels (configurable up to 20) and will count all the bars that reached each level. This will be represented in a table showing both the number of bars that reached each range and the percentage in relation to the total bars of all ranges.
Additionally, there's the possibility to view the ranges directly for the current price, providing a good reference.
>> Alerts:
The indicator comes with alerts that notify traders about specific price movements in relation to a moving average (MA). These alerts are triggered when the price enters different ranges, either above or below the MA.
>> Settings:
- Type of Analysis: Users can choose to analyze the price either above or below the MA.
- Length of the moving average: Length of the MA.
- Source of the moving average: Source to calculate the MA (e.g., close, open).
- Type of moving average: Type of MA (SMA, EMA, WMA, VWMA, HMA).
- Show Moving Average: Option to display or hide the MA on the chart.
- Number of levels: Number of levels or ranges to categorize the distance between the price and the MA.
- Number of decimals: Number of decimals to display in labels and tables.
- Show Ranges: Option to display or hide the ranges on the chart.
- Extend Range: Extension of the ranges into future bars.
- Range Fill Transparency: Transparency of the range fill.
>> Potential Utility of the Indicator:
- Entry and Exit Optimization:
By understanding the percentages of each range, traders can identify optimal levels to enter or exit a trade, maximizing profits and minimizing losses.
- Risk Management:
Range percentages can help determine market volatility. A range with a high percentage indicates greater volatility, which can be useful for setting wider stop losses or adjusting position size.
- Overbought and Oversold Zone Identification:
If a price is at the upper or lower extreme of its percentage range, it may indicate overbought or oversold conditions, respectively. These zones can be opportunities for counter-trend trades.
- Momentum Assessment:
A rapid change in range percentages can indicate strong momentum in a particular direction. Traders can use this information to ride the momentum wave or prepare for a potential reversal.
- False Signal Filtering:
By combining range percentage knowledge with other indicators, traders can filter out signals that might be less reliable, thus improving trade accuracy.
- Strategic Planning:
Knowing range percentages allows traders to adapt their strategies according to market conditions. For instance, in a market with narrow ranges and low percentages, they might opt for range strategies. In markets with wide ranges and high percentages, they might look for trend strategies.
- Trend Strength Evaluation:
If range percentages show that the price consistently stays at one end of the range, this may signal a strong and sustained trend.
- Improved Trading Discipline:
By basing trading decisions on quantitative data like range percentages, traders can trade more objectively and disciplined, avoiding impulsive or emotion-based decisions.
>> Future Indicator Update:
- In future versions, we plan to incorporate a detailed analysis based on the historical behavior of candles after the price enters a specific range. For instance, if after an upward movement the price enters a certain range and historically, the next candle tends to be bearish in a high percentage of occasions, this information will be highlighted and presented clearly to the user. The idea behind this addition is to provide traders with a statistical edge, allowing them to anticipate potential market movements with greater accuracy. Moreover, this information could be used to seek trading opportunities in smaller timeframes, aligning the trade direction based on the probability of this mentioned candle.
>> Conclusions:
- In summary, a detailed understanding of each range's percentages in an indicator provides traders with a valuable tool to analyze the market, make informed decisions, and enhance their trading. By grasping the significance of these percentages, traders can adapt their strategies and techniques to fully leverage the opportunities the market presents.
FastlaneIt will show a Marking (dot) above/below the candle where the Volume is 500000 and is up more than 5%.
VWAP, AVWAP and MVWAP - Omkar BanneThis indicator plots the VWAP, MVWAP and Anchored VWAP.
AVWAP: Anchored VWAP sometimes doesn't work the way it should. In such times, trades can use the default AVWAP on the right ribbon.
MVWAP: Moving average length can be changed; the default is 10.
Magic Trend By Market Mindset - Zero To EndlessMagic Trend indicator is an indicator combining the Commodity Channel Index (CCI) and the Average True Range (ATR) indicators.
The indicator is represented by a line that turns red when CCI readings are below 0 and converts to blue when CCI reaches above 0.
Color of the line can be treated as a trend indicator.
When CCI > 0 (Blue Color), price is assumed to be in uptrend and a buying momentum could be seen.
When CCI < 0 (Red Color), price is assumed to be in downtrend and a selling pressure could be seen.
Two Multipliers of ATR have been used. Default values for multiploier are : 1.5 and 3.0
It tells about the volatality in the price and also helps in deciding Entry poits, Stop loss points and sometimes Exit points.
If trend magic lines are not straight and moving upward/downward, continuition of the trend is expected and so Holding the position is adviced.
If the farther line (line with multiplier 3.0) is broken, a trend reversal can be seen soon.
In this case, squaring off and making reverse position is adviced near the other (1.5 mult) line.
If price is revolving in between these two lines... a sideways movement is expected.
Happy Trading
Market Mindset
Auto-Length Adaptive ChannelsIntroduction
The key innovation of the ALAC is the implementation of dynamic length identification, which allows the indicator to adjust to the "market beat" or dominant cycle in real-time.
The Auto-Length Adaptive Channels (ALAC) is a flexible technical analysis tool that combines the benefits of five different approaches to market band and price deviation calculations.
Traders often tend to overthink of what length their indicators should use, and this is the main idea behind this script. It automatically calculates length based on pivot points, averaging the distance that is in between of current market highs and lows.
This approach is very helpful to identify market deviations, because deviations are always calculated and compared to previous market behavior.
How it works
The indicator uses a Detrended Rhythm Oscillator (DRO) to identify the dominant cycle in the market. This length information is then used to calculate different market bands and price deviations. The ALAC combines five different methodologies to compute these bands:
1 - Bollinger Bands
2 - Keltner Channels
3 - Envelope
4 - Average True Range Channels
5 - Donchian Channels
By averaging these calculations, the ALAC produces an overall market band that generalizes the approaches of these five methods into a single, adaptive channel.
How to Use
When the price is at the upper band, this might suggest that the asset is overbought and may be due for a price correction. Conversely, when the price is at the lower band, the asset may be oversold and due for a price increase.
The space between the bands represents the market's volatility. Wider bands indicate higher volatility, while narrower bands suggest lower volatility.
Indicator Settings
The settings of the ALAC allow for customization to suit different trading strategies:
Use Autolength?: This allows the indicator to automatically adjust the length of the dominant cycle.
Usual Length: If "Use Autolength?" is disabled, this setting allows the user to manually specify the length of the cycle.
Moving Average Type: This selects the type of moving average to be used in the calculations. Options include SMA, EMA, ALMA, DEMA, JMA, KAMA, SMMA, TMA, TSF, VMA, VAMA, VWMA, WMA, and ZLEMA.
Channel Multiplier: This adjusts the distance between the bands.
Channel Multiplier Step: This changes the step size of the channel multiplier. Each next market band will be multiplied by a previous one. You can potentially use values below 1, which will plot bands inside the first, main channel.
Use DPO instead of source data?: This setting uses the DPO for calculations instead of the source data. Basically, this is how you can add or eliminate trend from calculation of an average leg-up / leg-down move.
Fast: This adjusts the fast length of the DPO.
Slow: This adjusts the slow length of the DPO.
Zig-zag Period: This adjusts the period of the zig-zag pattern used in the DPO.
(!) For more information about DPO visit official TradingView description here: link
Also, I want to say thanks to @StockMarketCycles for initial idea of Detrended Rhythm Oscillator (DRO) that I use in this script.
The Adaptive Average Channel is a powerful and versatile indicator that combines the strengths of multiple technical analysis methods.
In summary, with the ALAC, you can:
1 - Dynamically adapt to any asset and price action with automatic calculation of dominant cycle lengths.
2 - Identify potential overbought and oversold conditions with the adaptive market bands.
3 - Customize your analysis with various settings, including moving average type and channel multiplier.
4 - Enhance your trading strategy by using the indicator in conjunction with other forms of analysis.
MMA mainpanelI stumbled on the MMA in the “Active Investing” course notes by Alan Hull (who invented the Hull Moving Average)
alanhull.com
He writes on page 13:
“Multiple moving averages, MMAs, are a sophisticated tool that can be used in a range of applications. MMAs are a series of lines that track and filter the weekly price movements. They consist of 2 sets of lines that allow Technical Analysts to observe and compare the immediate behavior of price activity with the long term behavior of the price activity. Exponential moving averages are used for this type of analysis. The price bars in the following chart have been switched off to improve readability of the MMA lines.”
“Once we have found a share that has an acceptable 'Rate of return' we must make a qualitative judgment of the trend. We are looking for a strong and consistent trend that is not likely to reverse shortly after we enter the market. The following points are critical;
- The long term group must be spreading apart or running parallel with each other.
- The long term group must be pointing upwards.
- The straighter the long term group of lines are; the less volatile the trend is.
- The short term group can pullback (ie. compress together) but if they cross into the long term group then the trend is weakening and may be about to break.
This type of qualitative analysis is only used when entering the market and the idea is to avoid volatility. We want to 'Buy and Hold' and not get bounced in and out of the market. Judging the quality of trends is the most subjective function we will have to perform.”
Because I tend to close positions too soon, I tried MMA. I found that it can help me to stay in position as long as the trend is going on. TradingView offers several scripts for MMA, this version differs from the others because I added color zones and linecolor changes to mark the trend according to Alan’s norms:
An uptrend is marked with a blue zone when the short term group is above the long term group and the long term group is sorted correctly and ema50 points up. The zone is purple when vice versa in downtrend. When there is no trend no zone is colored, but the lines are made gray.
Because of Alan’s idea to show MMA without price bars, I created both an overlay version for the main panel and a version for a sub panel.
EMA Angle Trend StrengthEATS is an innovative indicator that calculates the slope of the exponential moving average (EMA) over a defined number of candles, presenting this on a scale of 0 to 100.
Users can individually adjust the length of the EMA and the precision of slope calculation. For the EMA length, users can specify the number of candles used for the EMA calculation. In terms of precision, the user can define the number of candles over which the slope calculation takes place.
The EATS indicator uses a mathematical function to calculate the angle of slope of the EMA. The resulting slope is converted into degrees and then portrayed on a scale of 0 to 100 using the "eats" function.
This indicator can be a useful tool for traders looking to evaluate a market's momentum and identify potential trend shifts. It allows you to visualize the strength a trend based on the angle of the EMA slope, offering a complementary perspective to traditional price and volume indicators.
Please note that as with all indicators, the EATS indicator should not be used as a standalone trading tool. It should always be used in combination with other technical analyses and/or fundamental analyses to make the most informed trading decisions.
Buy/Sell EMA CandleThis indicator is designed to display various technical indicators, candle patterns, and trend directions on a price chart. Let's break down the code and explain its different sections:
Exponential Moving Averages (EMA):
The code calculates and plots five EMAs of different lengths (13, 21, 55, 90, and 200) on the price chart. These EMAs are used to identify trends and potential crossovers.
Engulfing Candle Patterns:
The code identifies and highlights potential bullish and bearish engulfing candle patterns. It checks if the current candle's body size is larger than the combined body sizes of the previous and subsequent four candles. If this condition is met, it marks the pattern on the chart.
s3.tradingview.com
EMA Crossovers:
The code identifies and highlights points where the shorter EMA (ema1) crosses above or below the longer EMA (ema2). It plots circles to indicate these crossover points.
Candle Direction and RSI Trend:
The code determines the trend direction of the last candle based on whether it closed higher or lower than its open price. It also calculates the RSI (Relative Strength Index) and determines its trend direction (overbought, oversold, or neutral) based on predefined thresholds.
s3.tradingview.com
Table Display:
The code creates a table displaying trend directions for different timeframes (monthly, weekly, daily, 4-hour, and 1-hour) for candle direction and RSI trends. The trends are labeled with "L" for long, "S" for short, and "N/A" for not applicable.
High Volume Bars (HVB):
The code identifies and colors bars with above-average volume as either bullish or bearish based on whether the price closed higher or lower than it opened. The color and conditions for high volume bars can be customized.
s3.tradingview.com
Doji Candle Pattern:
The code identifies and marks doji candle patterns, where the open and close prices are very close to each other within a certain percentage of the candle's high-low range.
RSI-Based Candle Coloring:
The code adjusts the color of the candles based on the RSI value. If the RSI value is above the overbought threshold or below the oversold threshold, the candles are colored yellow.
Usage and Interpretation:
Traders can use this indicator to identify potential trend changes based on EMA crossovers and candle patterns like engulfing and doji.
The RSI trend direction can provide additional insight into potential overbought or oversold conditions.
High volume bars can indicate potential price reversals or continuation patterns.
The table provides an overview of trend directions on different timeframes for both candle direction and RSI trends.
Keep in mind that this is a complex indicator with multiple features. Users should carefully evaluate its performance and consider combining it with other indicators and analysis methods for more accurate trading decisions.
The table is designed to provide a consolidated view of trend directions and other indicators across multiple timeframes. It is displayed on the chart and organized into rows and columns. Each row corresponds to a specific aspect of analysis, and each column corresponds to a different timeframe.
Here's a breakdown of the components of the table:
Row 1: Separation.
Row 2 (Header Row): This row contains the headers for the columns. The headers represent the different timeframes being analyzed, such as Monthly (M), Weekly (W), Daily (D), 4-hour (4h), and 1-hour (1h).
Row 3 (Content Row): This row contains labels indicating the types of information being displayed in the columns. The labels include "T" for Trend, "C" for Current Candle, and "R" for RSI Trend.
Row 4 and Onwards: These rows display the actual data for each aspect of analysis across different timeframes.
For each aspect of analysis (Trend, Current Candle, RSI Trend), the corresponding rows display the following information:
Monthly (M): The trend direction for the given aspect on the monthly timeframe.
Weekly (W): The trend direction for the given aspect on the weekly timeframe.
Daily (D): The trend direction for the given aspect on the daily timeframe.
4-hour (4h): The trend direction for the given aspect on the 4-hour timeframe.
1-hour (1h): The trend direction for the given aspect on the 1-hour timeframe.
The trend directions are represented by labels such as "L" for Long, "S" for Short, or "N/A" for Not Applicable.
The table's purpose is to provide a quick overview of trend directions and related information across multiple timeframes, aiding traders in making informed decisions based on the analysis of trend changes and other indicators.
Average Range LinesThis Average Range Lines indicator identifies high and low price levels based on a chosen time period (day, week, month, etc.) and then uses a simple moving average over the length of the lookback period chosen to project support and resistance levels, otherwise referred to as average range. The calculation of these levels are slightly different than Average True Range and I have found this to be more accurate for intraday price bounces.
Lines are plotted and labeled on the chart based on the following methodology:
+3.0: 3x the average high over the chosen timeframe and lookback period.
+2.5: 2.5x the average high over the chosen timeframe and lookback period.
+2.0: 2x the average high over the chosen timeframe and lookback period.
+1.5: 1.5x the average high over the chosen timeframe and lookback period.
+1.0: The average high over the chosen timeframe and lookback period.
+0.5: One-half the average high over the chosen timeframe and lookback period.
Open: Opening price for the chosen time period.
-0.5: One-half the average low over the chosen timeframe and lookback period.
-1.0: The average low over the chosen timeframe and lookback period.
-1.5: 1.5x the average low over the chosen timeframe and lookback period.
-2.0: 2x the average low over the chosen timeframe and lookback period.
-2.5: 2.5x the average low over the chosen timeframe and lookback period.
-3.0: 3x the average low over the chosen timeframe and lookback period.
Look for price to find support or resistance at these levels for either entries or to take profit. When price crosses the +/- 2.0 or beyond, the likelihood of a reversal is very high, especially if set to weekly and monthly levels.
This indicator can be used/viewed on any timeframe. For intraday trading and viewing on a 15 minute or less timeframe, I recommend using the 4 hour, 1 day, and/or 1 week levels. For swing trading and viewing on a 30 minute or higher timeframe, I recommend using the 1 week, 1 month, or longer timeframes. I don’t believe this would be useful on a 1 hour or less timeframe, but let me know if the comments if you find otherwise.
Based on my testing, recommended lookback periods by timeframe include:
Timeframe: 4 hour; Lookback period: 60 (recommend viewing on a 5 minute or less timeframe)
Timeframe: 1 day; Lookback period: 10 (also check out 25 if your chart doesn’t show good support/resistance at 10 days lookback – I have found 25 to be useful on charts like SPX)
Timeframe: 1 week; Lookback period: 14
Timeframe: 1 month; Lookback period: 10
The line style and colors are all editable. You can apply a global coloring scheme in the event you want to add this indicator to your chart multiple times with different time frames like I do for the weekly and monthly.
I appreciate your comments/feedback on this indicator to improve. Also let me know if you find this useful, and what settings/ticker you find it works best with!
Also check out my profile for more indicators!
Normalized Adaptive Trend Lines [MAMA and FAMA]These indicators was originally developed by John F. Ehlers (Stocks & Commodities V. 19:10: MESA Adaptive Moving Averages). Everget wrote the initial functions for these in pine script. I have simply normalized the indicators and chosen to use the Laplace transformation instead of the hilbert transformation
How the Indicator Works:
The indicator employs a series of complex calculations, but we'll break it down into key steps to understand its functionality:
LaplaceTransform: Calculates the Laplace distribution for the given src input. The Laplace distribution is a continuous probability distribution, also known as the double exponential distribution. I use this because of the assymetrical return profile
MESA Period: The indicator calculates a MESA period, which represents the dominant cycle length in the price data. This period is continuously adjusted to adapt to market changes.
InPhase and Quadrature Components: The InPhase and Quadrature components are derived from the Hilbert Transform output. These components represent different aspects of the price's cyclical behavior.
Homodyne Discriminator: The Homodyne Discriminator is a phase-sensitive technique used to determine the phase and amplitude of a signal. It helps in detecting trend changes.
Alpha Calculation: Alpha represents the adaptive factor that adjusts the sensitivity of the indicator. It is based on the MESA period and the phase of the InPhase component. Alpha helps in dynamically adjusting the indicator's responsiveness to changes in market conditions.
MAMA and FAMA Calculation: The MAMA and FAMA values are calculated using the adaptive factor (alpha) and the input price data. These values are essentially adaptive moving averages that aim to capture the current trend more effectively than traditional moving averages.
But Omar, why would anyone want to use this?
The MAMA and FAMA lines offer benefits:
The indicator offers a distinct advantage over conventional moving averages due to its adaptive nature, which allows it to adjust to changing market conditions. This adaptability ensures that investors can stay on the right side of the trend, as the indicator becomes more responsive during trending periods and less sensitive in choppy or sideways markets.
One of the key strengths of this indicator lies in its ability to identify trends effectively by combining the MESA and MAMA techniques. By doing so, it efficiently filters out market noise, making it highly valuable for trend-following strategies. Investors can rely on this feature to gain clearer insights into the prevailing trends and make well-informed trading decisions.
This indicator is primarily suppoest to be used on the big timeframes to see which trend is prevailing, however I am not against someone using it on a timeframe below the 1D, just be careful if you are using this for modern portfolio theory, this is not suppoest to be a mid-term component, but rather a long term component that works well with proper use of detrended fluctuation analysis.
Dont hesitate to ask me if you have any questions
Again, I want to give credit to Everget and ChartPrime!
