MACD Chebyshev (CMACD)Introducing the Advanced MACD Chebyshev Indicator
Enhanced Convergence Divergence with Gate Compressor for Improved Trading Signals
Introduction
We are excited to introduce a new, advanced Moving Average Convergence Divergence (MACD) indicator that we've developed, called the MACD Chebyshev (CMACD). This innovative indicator uses the dominant period to determine the frequency of the band pass and employs a delayed version of the signal for better convergence divergence. To further enhance the quality of the signals, we've incorporated a gate compressor in the histogram. In this blog post, we will provide an extensive overview of the CMACD indicator, detailing its features and explaining how it works.
The MACD Chebyshev Indicator
The CMACD indicator is based on the well-known MACD indicator, which is a popular technical analysis tool for identifying potential trend reversals in financial markets. The MACD indicator calculates the difference between two Exponential Moving Averages (EMAs) and plots a histogram to represent the convergence and divergence between these EMAs. The CMACD indicator builds on this concept by using the Chebyshev Type I and Type II Moving Averages, which offer superior smoothing and reduced lag compared to traditional EMAs.
The main components of the CMACD indicator are:
1. Signal Line (Blue Line)
2. Delay Line (Orange Line)
3. Histogram (Green and Red bars)
4. Zero Line (Gray Line)
The indicator calculates the difference between the two Chebyshev Moving Averages and plots the histogram based on this difference. The histogram bars change color depending on whether they are above or below the zero line and whether they are growing or falling.
Custom Functions and Features
The CMACD indicator includes several custom functions and features that set it apart from the standard MACD indicator:
1. Dominant Period: The CMACD indicator uses the dominant period to determine the frequency of the band pass. This ensures that the indicator is more responsive to the current market conditions, as it adapts to the dominant cycle in the price data.
2. Delayed Signal: The CMACD indicator employs a delayed version of the signal to provide better convergence divergence. This helps to reduce false signals and improve the accuracy of the indicator.
3. Ripple: The Ripple parameter allows users to adjust the smoothing factor of the Chebyshev Moving Averages. This can be customized to suit individual trading preferences and strategies.
4. Gate Compressor: The CMACD indicator incorporates a gate compressor in the histogram. This unique feature allows users to specify a Percent Rank for the gate signal level, a Gate Ratio, and a Knee Type (either "hard" or "soft"). The gate compressor works by reducing the amplitude of the histogram bars when their absolute value is below the specified threshold. This helps to filter out noise and improve the clarity of the signals generated by the indicator.
Color Scheme
The CMACD indicator features an intuitive color scheme for easy interpretation of the histogram:
1. Green Bars (Above Zero Line): The histogram bars are green when they are above the zero line. The darker green color indicates a growing bar, while the lighter green color represents a falling bar.
2. Red Bars (Below Zero Line): The histogram bars are red when they are below the zero line. The darker red color indicates a growing bar, while the lighter red color represents a falling bar.
Conclusion
The MACD Chebyshev (CMACD) indicator is an innovative and powerful tool for technical analysis, offering superior performance compared to the standard MACD indicator. With its advanced features, such as the dominant period, delayed signal, ripple adjustment, and gate compressor, the CMACD indicator provides more accurate and reliable trading signals. Incorporate the CMACD indicator into your trading strategy today and experience the enhanced convergence divergence for better trading decisions.
在腳本中搜尋"averages"
peacefulIndicatorsWe are delighted to present the PeacefulIndicators library, a modest yet powerful collection of custom technical indicators created to enhance your trading analysis. The library features an array of practical tools, including MACD with Dynamic Length, Stochastic RSI with ATR Stop Loss, Bollinger Bands with RSI Divergence, and more.
The PeacefulIndicators library offers the following functions:
macdDynamicLength: An adaptive version of the classic MACD indicator, which adjusts the lengths of the moving averages based on the dominant cycle period, providing a more responsive signal.
rsiDivergence: A unique implementation of RSI Divergence detection that identifies potential bullish and bearish divergences using a combination of RSI and linear regression.
trendReversalDetection: A helpful tool for detecting trend reversals using the Rate of Change (ROC) and Moving Averages, offering valuable insights into possible market shifts.
volume_flow_oscillator: A custom oscillator that combines price movement strength and volume to provide a unique perspective on market dynamics.
weighted_volatility_oscillator: Another custom oscillator that factors in price volatility and volume to deliver a comprehensive view of market fluctuations.
rvo: The Relative Volume Oscillator highlights changes in volume relative to historical averages, helping to identify potential breakouts or reversals.
acb: The Adaptive Channel Breakout indicator combines a moving average with an adjustable volatility multiplier to create dynamic channels, useful for identifying potential trend shifts.
We hope this library proves to be a valuable addition to your trading toolbox.
Library "peacefulIndicators"
A custom library of technical indicators for trading analysis, including MACD with Dynamic Length, Stochastic RSI with ATR Stop Loss, Bollinger Bands with RSI Divergence, and more.
macdDynamicLength(src, shortLen, longLen, signalLen, dynLow, dynHigh)
Moving Average Convergence Divergence with Dynamic Length
Parameters:
src (float) : Series to use
shortLen (int) : Shorter moving average length
longLen (int) : Longer moving average length
signalLen (int) : Signal line length
dynLow (int) : Lower bound for the dynamic length
dynHigh (int) : Upper bound for the dynamic length
Returns: tuple of MACD line and Signal line
Computes MACD using lengths adapted based on the dominant cycle period
rsiDivergence(src, rsiLen, divThreshold, linRegLength)
RSI Divergence Detection
Parameters:
src (float) : Series to use
rsiLen (simple int) : Length for RSI calculation
divThreshold (float) : Divergence threshold for RSI
linRegLength (int) : Length for linear regression calculation
Returns: tuple of RSI Divergence (positive, negative)
Computes RSI Divergence detection that identifies bullish (positive) and bearish (negative) divergences
trendReversalDetection(src, rocLength, maLength, maType)
Trend Reversal Detection (TRD)
Parameters:
src (float) : Series to use
rocLength (int) : Length for Rate of Change calculation
maLength (int) : Length for Moving Average calculation
maType (string) : Type of Moving Average to use (default: "sma")
Returns: A tuple containing trend reversal direction and the reversal point
Detects trend reversals using the Rate of Change (ROC) and Moving Averages.
volume_flow_oscillator(src, length)
Volume Flow Oscillator
Parameters:
src (float) : Series to use
length (int) : Period for the calculation
Returns: Custom Oscillator value
Computes the custom oscillator based on price movement strength and volume
weighted_volatility_oscillator(src, length)
Weighted Volatility Oscillator
Parameters:
src (float) : Series to use
length (int) : Period for the calculation
Returns: Custom Oscillator value
Computes the custom oscillator based on price volatility and volume
rvo(length)
Relative Volume Oscillator
Parameters:
length (int) : Period for the calculation
Returns: Custom Oscillator value
Computes the custom oscillator based on relative volume
acb(price_series, ma_length, vol_length, multiplier)
Adaptive Channel Breakout
Parameters:
price_series (float) : Price series to use
ma_length (int) : Period for the moving average calculation
vol_length (int) : Period for the volatility calculation
multiplier (float) : Multiplier for the volatility
Returns: Tuple containing the ACB upper and lower values and the trend direction (1 for uptrend, -1 for downtrend)
Supply and Demand Visible Range [LuxAlgo]The Supply and Demand Visible Range indicator displays areas & levels on the user's chart for the visible range using a novel volume-based method. The script also makes use of intra-bar data to create precise Supply & Demand zones.
🔶 SETTINGS
Threshold %: Percentage of the total visible range volume used as a threshold to set supply/demand areas. Higher values return wider areas.
Resolution: Determines the number of bins used to find each area. Higher values will return more precise results.
Intra-bar TF: Timeframe used to obtain intra-bar data.
🔶 USAGE
The supply/demand areas and levels displayed by the script are aimed at providing potential supports/resistances for users. The script's behavior makes it recalculate each time the visible chart interval/range changes, as such this script is more suited as a descriptive tool.
Price reaching a supply (upper) area that might have been tested a few times might be indicative of a potential reversal down, while price reaching a demand (lower) area that might have been tested a few times could be indicative of a potential reversal up.
The width of each area can also indicate which areas are more liquid, with thinner areas indicating more significant liquidity.
The user can control the width of each area using the Threshold % setting, with a higher setting returning wider areas. The precision setting can also return wider supply/demand areas if very low values are used and has the benefit of improving the script execution time at the cost of precision.
The Supply and Demand Zones indicator returns various levels. The solid-colored levels display the average of each area, while dashed colored lines display the weighted averages of each area. These weighted averages can highlight more liquid price levels within the supply/demand areas.
Central solid/dashed lines display the average between the areas' averages and weighted averages.
🔶 DETAILS
Each supply/demand area is constructed from volume data. The calculation is done as follows:
The accumulated volume within the chart visible range is calculated.
The chart visible range is divided into N bins of equal width (where N is the resolution setting)
Calculation start from the highest visible range price value for the supply area, and lowest value for the demand area.
The volume within each bin after the starting calculation level is accumulated, once this accumulated volume is equal or exceed the threshold value ( p % of the total visible range volume) the area is set.
Each bin volume accumulation within an area is displayed on the left, this can help indicate how fast volume accumulates within an area.
🔶 LIMITATIONS
The script execution time is dependent on all of the script's settings, using more demanding settings might return errors so make sure to be aware of the potential scenarios that might make the script exceed the allowed execution time:
Having a chart's visible range including a high number of bars.
Using a high number of bins (high resolution value) will increase computation time, this can be worsened by using a high threshold %.
Using very low intra-bar timeframe can drastically increase computation time but can also simply throw an error if the chart timeframe is high.
Users facing issues can lower the resolution value or use the chart timeframe for intra-bar data.
Impulse Momentum MACD - Slow and FastImpulse Momentum MACD - Slow and Fast
The Momentum indicator is a technical indicator that measures the speed and strength of the price movement of a financial asset. This indicator is used to identify the underlying strength of a trend and predict potential changes in price direction, when the indicator crosses the zero line, it can signal a change of direction in the price trend.
On the other hand, the MACD is an indicator used to identify the trend and strength of the market and shows the difference between two exponential moving averages ( EMA ) of different periods. The MACD is commonly used to determine the direction of an asset's price trend.
COPOSITION AND USE OF THE INDICATOR
This script is an implementation of the Impulse Momentum MACD indicator with two variations: slow and fast. It uses a combination of the Momentum indicator and the Moving Average Convergence/Divergence (MACD) indicator to identify trend reversals and momentum changes in an asset's price.
The combination of both indicators can help traders identify market entry and exit opportunities. The Impulse Momentum MACD is a Modified MACD, it is formed by filtering the values in a range of Modifiable Moving Averages by calculating their high and low ranges,This indicator has two parts: a slow part and a fast part. The slow part uses input values for the lengths of the moving averages and the length of the signal for the MACD indicator. The fast part uses different input values for the lengths of the moving averages. Also, each part has its own set of line colors and histogram colors for easy visualization.
The script also includes inputs to choose the type of moving average to use (SMA, EMA, etc.), the lookback period, the colors for the histogram lines and bars, and a zero trend line (also known as a horizontal trend line). ).
* Highest performing custom settings for the zero trend line. For Operations of:
- One Minute: Trend Line Time Frame = Five Minutes.
- Three Minutes: Trend Line Time Frame = Fifteen Minutes.
- Five Minutes: Trend Line Time Frame = Thirty Minutes.
- Fifteen Minutes: Trend Line Time Frame = Sixty Minutes.
Rules For Trading
🔹 Bullish:
* The Zero Horizontal Trend Line should be in Green Color.
* The Slow Histogram Bar should be in Green Color.
* The Fast Histogram Bar must be in Blue or Black Color or No Bar Appears.
* The Momentum Line or Momentum Area must be in Green Color.
crosses:
- When the Impulse Momentum MACD Slow line crosses the Impulse Momentum MACD Slow signal line upwards.
- When the Impulse Momentum MACD Fast line crosses the Impulse Momentum MACD Fast signal line upwards.
- Note 1: A Position is Opened when the condition of any of the aforementioned crossovers is met.
- Note 2: If the two aforementioned crossings anticipate the condition of the Zero Horizontal Tendency Line because it is in Red; A position is only opened immediately when the Zero Horizontal Trend line turns Green.
🔹 Bearish:
* The Zero Horizontal Trend Line should be in Red Color.
* The Slow Histogram Bar should be in Red Color.
* The Fast Histogram Bar must be in Blue or Black Color or No Bar Appears.
* The Momentum Line or Momentum Area must be in Red Color.
crosses:
- When the Impulse Momentum MACD Slow line crosses the Impulse Momentum MACD Slow signal line downwards.
- When the Impulse Momentum MACD Fast line crosses the Impulse Momentum MACD Fast signal line downwards.
- Note 1: A Position is Opened when the condition of any of the aforementioned crossovers is met.
- Note 2: If the two aforementioned crossings anticipate the condition of the Zero Horizontal Tendency Line because it is Green, an immediate position is only opened when the Zero Horizontal Tendency line turns Red.
This script can be used in different markets such as forex, indices and cryptocurrencies for analysis and trading. However, it is important to note that no trading strategy is guaranteed to be profitable, and traders should always conduct their own research and risk management.
Stochastic MACD - Slow and FastStochastic MACD - Slow and Fast
The "Stochastic MACD - Slow and Fast" indicator combines two popular technical indicators, the Stochastic Oscillator and the Moving Average Convergence Divergence ( MACD ).
The Stochastic Oscillator is a momentum indicator that measures the current closing position of an asset relative to its recent price range. This indicator helps traders identify possible turning points in an asset's trend, it is used to identify if the market is overbought or oversold.
On the other hand, the MACD is an indicator used to identify the trend and strength of the market and shows the difference between two exponential moving averages ( EMA ) of different periods. The MACD is commonly used to determine the direction of an asset's price trend.
The combination of both indicators can help traders identify market entry and exit opportunities. This indicator has two parts: a slow part and a fast part. The slow part uses input values for the lengths of the moving averages and the length of the signal for the MACD indicator. The fast part uses different input values for the lengths of the moving averages. Also, each part has its own set of line colors and histogram colors for easy visualization.
In general, the "Stochastic MACD - Slow and Fast" indicator is used to identify possible turning points in the trend of an asset. Traders can use the indicator to determine when to enter or exit a position based on the signals generated by the indicator. The stochastic MACD is a variation of the regular MACD that incorporates a stochastic oscillator to provide additional signals.
In summary, this indicator can be useful for those looking for a combination of two popular indicators to help identify trading opportunities.
In addition, parameters were defined to activate or deactivate the graphic signal.
When the Stochastic MACD Slow Line Crosses the Stochastic MACD Slow Signal Line:
Long or Buy = ↑ // The Entry is more Effective if it is made when the signal is below the Zero Trend Line .
Short or Sell = ↓ // The Entry is more Effective if it is made when the signal is above the Zero Trend Line .
When the Fast Stochastic MACD Line Crosses the Slow Stochastic MACD Line:
Long or Buy = ▲ // The Entry is more Effective if it is made when the signal is below the Zero Trend Line .
Short or Sell = ▼ // The Entry is more Effective if it is made when the signal is above the Zero Trend Line .
Taking into account the above, alerts were also defined for possible Purchases or Sales or entries in Long or Short.
COPOSITION AND USE OF THE INDICATOR
This script is an implementation of the Stochastic MACD indicator with two variations - Slow and Fast. It uses a combination of the Stochastic Oscillator and the Moving Average Convergence Divergence (MACD) indicator to identify trend reversals and momentum shifts in the price of an asset.
The Slow version of the Stochastic MACD is built using three inputs - fastLength, slowLength, and signalLength. The fastLength and slowLength are used to calculate two exponential moving averages (EMAs), while the signalLength is used to calculate a signal line as an EMA of the difference between the two EMAs. The Stochastic Oscillator is then applied to the difference between the two EMAs, and the resulting values are plotted on the chart.
The Fast version of the Stochastic MACD is built using the same inputs as the Slow version, but with different values. It uses a shorter fastLength value and a longer slowLength value to generate the two EMAs, and the resulting values are plotted on the chart.
The script also includes inputs for choosing the type of moving average to use (SMA, EMA, etc.), the source of price data (open, close, etc.), the lookback period, and the colors for the lines and histogram bars.
This script can be used in different markets such as forex, indices, and cryptocurrencies for analysis and trading. However, it is important to note that no trading strategy is guaranteed to be profitable, and traders should always conduct their own research and risk management.
ROC (Rate of Change) Refurbished▮ Introduction
The Rate of Change indicator (ROC) is a momentum oscillator.
It was first introduced in the early 1970s by the American technical analyst Welles Wilder.
It calculates the percentage change in price between periods.
ROC takes the current price and compares it to a price 'n' periods (user defined) ago.
The calculated value is then plotted and fluctuates above and below a Zero Line.
A technical analyst may use ROC for:
- trend identification;
- identifying overbought and oversold conditions.
Even though ROC is an oscillator, it is not bounded to a set range.
The reason for this is that there is no limit to how far a security can advance in price but of course there is a limit to how far it can decline.
If price goes to $0, then it obviously will not decline any further.
Because of this, ROC can sometimes appear to be unbalanced.
(TradingView)
▮ Improvements
The following features were added:
1. Eight moving averages for the indicator;
2. Dynamic Zones;
3. Rules for coloring bars/candles.
▮ Motivation
Averages have been added to improve trend identification.
For finer tuning, you can choose the type of averages.
You can hide them if you don't need them.
The Dynamic Zones has been added to make it easier to identify overbought/oversold regions.
Unlike other oscillators like the RSI for example, the ROC does not have a predetermined range of oscillations.
Therefore, a fixed line that defines an overbought/oversold range becomes unfeasible.
It is in this matter that the Dynamic Zone helps.
It dynamically adjusts as the indicator oscillates.
▮ About Dynamic Zones
'Most indicators use a fixed zone for buy and sell signals.
Here's a concept based on zones that are responsive to the past levels of the indicator.'
The concept of Dynamic Zones was described by Leo Zamansky (Ph.D.) and David Stendahl, in the magazine of Stocks & Commodities V15:7 (306-310).
Basically, a statistical calculation is made to define the extreme levels, delimiting a possible overbought/oversold region.
Given user-defined probabilities, the percentile is calculated using the method of Nearest Rank.
It is calculated by taking the difference between the data point and the number of data points below it, then dividing by the total number of data points in the set.
The result is expressed as a percentage.
This provides a measure of how a particular value compares to other values in a data set, identifying outliers or values that are significantly higher or lower than the rest of the data.
▮ Thanks and Credits
- TradingView: for ROC and Moving Averages
- allanster: for Dynamic Zones
Historical AverageHistorical Average is a script written in the Pine Script language and is used to calculate various types of moving averages. Moving averages are statistical measures that smooth out data over time, making it easier to identify trends and patterns. This script allows the user to select from several different types of moving averages, including Simple Moving Average (SMA), Linear Weighted Moving Average (LWMA), Exponential Moving Average (EMA), Double Exponential Moving Average (DEMA), Triple Exponential Moving Average (TEMA), and Quadruple Exponential Moving Average (QEMA). The script also allows the user to specify a data source for the moving averages to be calculated from.
To use this script, the user simply needs to specify the data source and select the desired moving average type from the list. The script will then calculate and plot the selected moving average on the chart. This can be useful for traders and investors who want to gain a better understanding of the trends and patterns in the data they are analyzing.
Smoothed RSI Heikin Ashi Oscillator w/ Expanded Types [Loxx]Smoothed RSI Heikin-Ashi Oscillator w/ Expanded Types is a spin on Heikin Ashi RSI Oscillator by @JayRogers. The purpose of this modification is to reduce noise in the original version thereby increasing suitability of the signal output. This indicator is tuned for Forex markets.
Differences:
35+ Smoothing Options for RSI
35+ Smoothing Options for HA Candles
Heiken-Ashi Better Expanded Source input. This source input is use for the RSI calculation only.
Signals
Alerts
What are Heiken-Ashi "better" candles?
The "better formula" was proposed in an article/memo by BNP-Paribas (In Warrants & Zertifikate, No. 8, August 2004 (a monthly German magazine published by BNP Paribas, Frankfurt), there is an article by Sebastian Schmidt about further development (smoothing) of Heikin-Ashi chart.)
They proposed to use the following :
(Open+Close)/2+(((Close-Open)/( High-Low ))*ABS((Close-Open)/2))
instead of using :
haClose = (O+H+L+C)/4
According to that document the HA representation using their proposed formula is better than the traditional formula.
What are traditional Heiken-Ashi candles?
The Heikin-Ashi technique averages price data to create a Japanese candlestick chart that filters out market noise.
Heikin-Ashi charts, developed by Munehisa Homma in the 1700s, share some characteristics with standard candlestick charts but differ based on the values used to create each candle. Instead of using the open, high, low, and close like standard candlestick charts, the Heikin-Ashi technique uses a modified formula based on two-period averages. This gives the chart a smoother appearance, making it easier to spots trends and reversals, but also obscures gaps and some price data.
Future updates
Expand signal options to include RSI-, Zero-, and color-crosses
Adaptive Oscillator constructor [lastguru]Adaptive Oscillators use the same principle as Adaptive Moving Averages. This is an experiment to separate length generation from oscillators, offering multiple alternatives to be combined. Some of the combinations are widely known, some are not. Note that all Oscillators here are normalized to -1..1 range. This indicator is based on my previously published public libraries and also serve as a usage demonstration for them. I will try to expand the collection (suggestions are welcome), however it is not meant as an encyclopaedic resource , so you are encouraged to experiment yourself: by looking on the source code of this indicator, I am sure you will see how trivial it is to use the provided libraries and expand them with your own ideas and combinations. I give no recommendation on what settings to use, but if you find some useful setting, combination or application ideas (or bugs in my code), I would be happy to read about them in the comments section.
The indicator works in three stages: Prefiltering, Length Adaptation and Oscillators.
Prefiltering is a fast smoothing to get rid of high-frequency (2, 3 or 4 bar) noise.
Adaptation algorithms are roughly subdivided in two categories: classic Length Adaptations and Cycle Estimators (they are also implemented in separate libraries), all are selected in Adaptation dropdown. Length Adaptation used in the Adaptive Moving Averages and the Adaptive Oscillators try to follow price movements and accelerate/decelerate accordingly (usually quite rapidly with a huge range). Cycle Estimators, on the other hand, try to measure the cycle period of the current market, which does not reflect price movement or the rate of change (the rate of change may also differ depending on the cycle phase, but the cycle period itself usually changes slowly).
Chande (Price) - based on Chande's Dynamic Momentum Index (CDMI or DYMOI), which is dynamic RSI with this length
Chande (Volume) - a variant of Chande's algorithm, where volume is used instead of price
VIDYA - based on VIDYA algorithm. The period oscillates from the Lower Bound up (slow)
VIDYA-RS - based on Vitali Apirine's modification of VIDYA algorithm (he calls it Relative Strength Moving Average). The period oscillates from the Upper Bound down (fast)
Kaufman Efficiency Scaling - based on Efficiency Ratio calculation originally used in KAMA
Deviation Scaling - based on DSSS by John F. Ehlers
Median Average - based on Median Average Adaptive Filter by John F. Ehlers
Fractal Adaptation - based on FRAMA by John F. Ehlers
MESA MAMA Alpha - based on MESA Adaptive Moving Average by John F. Ehlers
MESA MAMA Cycle - based on MESA Adaptive Moving Average by John F. Ehlers , but unlike Alpha calculation, this adaptation estimates cycle period
Pearson Autocorrelation* - based on Pearson Autocorrelation Periodogram by John F. Ehlers
DFT Cycle* - based on Discrete Fourier Transform Spectrum estimator by John F. Ehlers
Phase Accumulation* - based on Dominant Cycle from Phase Accumulation by John F. Ehlers
Length Adaptation usually take two parameters: Bound From (lower bound) and To (upper bound). These are the limits for Adaptation values. Note that the Cycle Estimators marked with asterisks(*) are very computationally intensive, so the bounds should not be set much higher than 50, otherwise you may receive a timeout error (also, it does not seem to be a useful thing to do, but you may correct me if I'm wrong).
The Cycle Estimators marked with asterisks(*) also have 3 checkboxes: HP (Highpass Filter), SS (Super Smoother) and HW (Hann Window). These enable or disable their internal prefilters, which are recommended by their author - John F. Ehlers . I do not know, which combination works best, so you can experiment.
Chande's Adaptations also have 3 additional parameters: SD Length (lookback length of Standard deviation), Smooth (smoothing length of Standard deviation) and Power ( exponent of the length adaptation - lower is smaller variation). These are internal tweaks for the calculation.
Oscillators section offer you a choice of Oscillator algorithms:
Stochastic - Stochastic
Super Smooth Stochastic - Super Smooth Stochastic (part of MESA Stochastic) by John F. Ehlers
CMO - Chande Momentum Oscillator
RSI - Relative Strength Index
Volume-scaled RSI - my own version of RSI. It scales price movements by the proportion of RMS of volume
Momentum RSI - RSI of price momentum
Rocket RSI - inspired by RocketRSI by John F. Ehlers (not an exact implementation)
MFI - Money Flow Index
LRSI - Laguerre RSI by John F. Ehlers
LRSI with Fractal Energy - a combo oscillator that uses Fractal Energy to tune LRSI gamma
Fractal Energy - Fractal Energy or Choppiness Index by E. W. Dreiss
Efficiency ratio - based on Kaufman Adaptive Moving Average calculation
DMI - Directional Movement Index (only ADX is drawn)
Fast DMI - same as DMI, but without secondary smoothing
If no Adaptation is selected (None option), you can set Length directly. If an Adaptation is selected, then Cycle multiplier can be set.
Before an Oscillator, a High Pass filter may be executed to remove cyclic components longer than the provided Highpass Length (no High Pass filter, if Highpass Length = 0). Both before and after the Oscillator a Moving Average can be applied. The following Moving Averages are included: SMA, RMA, EMA, HMA , VWMA, 2-pole Super Smoother, 3-pole Super Smoother, Filt11, Triangle Window, Hamming Window, Hann Window, Lowpass, DSSS. For more details on these Moving Averages, you can check my other Adaptive Constructor indicator:
The Oscillator output may be renormalized and postprocessed with the following Normalization algorithms:
Stochastic - Stochastic
Super Smooth Stochastic - Super Smooth Stochastic (part of MESA Stochastic) by John F. Ehlers
Inverse Fisher Transform - Inverse Fisher Transform
Noise Elimination Technology - a simplified Kendall correlation algorithm "Noise Elimination Technology" by John F. Ehlers
Except for Inverse Fisher Transform, all Normalization algorithms can have Length parameter. If it is not specified (set to 0), then the calculated Oscillator length is used.
More information on the algorithms is given in the code for the libraries used. I am also very grateful to other TradingView community members (they are also mentioned in the library code) without whom this script would not have been possible.
Adaptive MA constructor [lastguru]Adaptive Moving Averages are nothing new, however most of them use EMA as their MA of choice once the preferred smoothing length is determined. I have decided to make an experiment and separate length generation from smoothing, offering multiple alternatives to be combined. Some of the combinations are widely known, some are not. This indicator is based on my previously published public libraries and also serve as a usage demonstration for them. I will try to expand the collection (suggestions are welcome), however it is not meant as an encyclopaedic resource, so you are encouraged to experiment yourself: by looking on the source code of this indicator, I am sure you will see how trivial it is to use the provided libraries and expand them with your own ideas and combinations. I give no recommendation on what settings to use, but if you find some useful setting, combination or application ideas (or bugs in my code), I would be happy to read about them in the comments section.
The indicator works in three stages: Prefiltering, Length Adaptation and Moving Averages.
Prefiltering is a fast smoothing to get rid of high-frequency (2, 3 or 4 bar) noise.
Adaptation algorithms are roughly subdivided in two categories: classic Length Adaptations and Cycle Estimators (they are also implemented in separate libraries), all are selected in Adaptation dropdown. Length Adaptation used in the Adaptive Moving Averages and the Adaptive Oscillators try to follow price movements and accelerate/decelerate accordingly (usually quite rapidly with a huge range). Cycle Estimators, on the other hand, try to measure the cycle period of the current market, which does not reflect price movement or the rate of change (the rate of change may also differ depending on the cycle phase, but the cycle period itself usually changes slowly).
Chande (Price) - based on Chande's Dynamic Momentum Index (CDMI or DYMOI), which is dynamic RSI with this length
Chande (Volume) - a variant of Chande's algorithm, where volume is used instead of price
VIDYA - based on VIDYA algorithm. The period oscillates from the Lower Bound up (slow)
VIDYA-RS - based on Vitali Apirine's modification of VIDYA algorithm (he calls it Relative Strength Moving Average). The period oscillates from the Upper Bound down (fast)
Kaufman Efficiency Scaling - based on Efficiency Ratio calculation originally used in KAMA
Deviation Scaling - based on DSSS by John F. Ehlers
Median Average - based on Median Average Adaptive Filter by John F. Ehlers
Fractal Adaptation - based on FRAMA by John F. Ehlers
MESA MAMA Alpha - based on MESA Adaptive Moving Average by John F. Ehlers
MESA MAMA Cycle - based on MESA Adaptive Moving Average by John F. Ehlers, but unlike Alpha calculation, this adaptation estimates cycle period
Pearson Autocorrelation* - based on Pearson Autocorrelation Periodogram by John F. Ehlers
DFT Cycle* - based on Discrete Fourier Transform Spectrum estimator by John F. Ehlers
Phase Accumulation* - based on Dominant Cycle from Phase Accumulation by John F. Ehlers
Length Adaptation usually take two parameters: Bound From (lower bound) and To (upper bound). These are the limits for Adaptation values. Note that the Cycle Estimators marked with asterisks(*) are very computationally intensive, so the bounds should not be set much higher than 50, otherwise you may receive a timeout error (also, it does not seem to be a useful thing to do, but you may correct me if I'm wrong).
The Cycle Estimators marked with asterisks(*) also have 3 checkboxes: HP (Highpass Filter), SS (Super Smoother) and HW (Hann Window). These enable or disable their internal prefilters, which are recommended by their author - John F. Ehlers. I do not know, which combination works best, so you can experiment.
Chande's Adaptations also have 3 additional parameters: SD Length (lookback length of Standard deviation), Smooth (smoothing length of Standard deviation) and Power (exponent of the length adaptation - lower is smaller variation). These are internal tweaks for the calculation.
Length Adaptaton section offer you a choice of Moving Average algorithms. Most of the Adaptations are originally used with EMA, so this is a good starting point for exploration.
SMA - Simple Moving Average
RMA - Running Moving Average
EMA - Exponential Moving Average
HMA - Hull Moving Average
VWMA - Volume Weighted Moving Average
2-pole Super Smoother - 2-pole Super Smoother by John F. Ehlers
3-pole Super Smoother - 3-pole Super Smoother by John F. Ehlers
Filt11 -a variant of 2-pole Super Smoother with error averaging for zero-lag response by John F. Ehlers
Triangle Window - Triangle Window Filter by John F. Ehlers
Hamming Window - Hamming Window Filter by John F. Ehlers
Hann Window - Hann Window Filter by John F. Ehlers
Lowpass - removes cyclic components shorter than length (Price - Highpass)
DSSS - Derivation Scaled Super Smoother by John F. Ehlers
There are two Moving Averages that are drown on the chart, so length for both needs to be selected. If no Adaptation is selected ( None option), you can set Fast Length and Slow Length directly. If an Adaptation is selected, then Cycle multiplier can be selected for Fast and Slow MA.
More information on the algorithms is given in the code for the libraries used. I am also very grateful to other TradingView community members (they are also mentioned in the library code) without whom this script would not have been possible.
Adaptive Ehlers Deviation Scaled Moving Average (AEDSMA)AEDSMA INTRODUCTION
This indicator is a functional enhancement to “Ehlers Deviation Scaled Moving Average (EDSMA / DSMA)”. I’ve used Volume Breakout and Volatility for dynamic length adaption and further Slope too for trend evaluation.
EDSMA was originally developed by John F. Ehlers (Stocks & Commodities V. 36:8: The Deviation-Scaled Moving Average).
IDEA PLACEMENT
I’ve traded almost every kind of market with different volatility conditions using Moving Averages. It was too much of a hassle to select and use different MA length depending upon market trend. So, the journey started with adapting Moving Averages with another parameter and that’s how “MZ SAMA ” came into being where Slope was used to adapt Adaptive Moving Average with trend change. The problem was still pretty much the same as SAMA might not be effective on every market condition. Hence, I worked on Volume to adapt Moving Averages accordingly. I cane up with “MZ RVSI ” which I used in “MZ DVAMA ” to adapt dynamic length in Adaptive Moving Average and also used “MZ RVSI " alongside Slope as confirmation of trend changes.
Meanwhile, I started using DVAMA methodology on different types on Moving Averages that allow dynamic length for example Hull Moving Average, Linear Regression Curve, SMA, WMA, TMA and many more. All of my tested Mas showed too much flexibility because of volume based Adaptive length.
I came across a script of “Adaptive Hull Moving Average” which pretty much used the similar methodology as DVAMA but when I looked into its depth, its volume oscillator wasn’t working at all and only volatility based dynamic length was used. It was an interesting idea so, I decided to use Volume and Volatility alongside for better results but was nearly impossible to achieve what I wanted using only Hull Moving Average.
I had been using EDSMA in “MA MTF Cross Strategy” and “MZ SRSI Strategy V1.0” previously. It was the perfect choice when comparing to usage of slope on it. DSMA works perfectly as support and resistance as its Deviation Scaled. So, I tried using it to adapt dynamic length based on Volume and Volatility and I wasn’t disappointed. It worked like a charm when I adapted dynamic length between 50 and 255.
DYNAMIC LENGTH BENEFITS
Dynamic length adaption methodology works in a way of adapting Relatively Lower Length leading toward overfitting if trend is supported by Volume and Volatility . Similarly, adapting Relatively Higher Length leading toward underfitting if trend isn’t supported by Volume and Volatility .
Dynamic length adaption makes Moving Average to work better for both Bull and Bear-runs avoiding almost every fake break-in and breakouts. Hence, adaptive MA becomes more reliable for breakout trading.
MA would be more useful as it would adapt almost every chart based on its Volume and Volatility data.
DYNAMIC COLORS AND TREND CORRELATION
I’ve used dynamic coloring to identify trends with more detail which are as follows:
Lime Color: Strong Uptrend supported by Volume and Volatility or whatever you’ve chosen from both of them.
Fuchsia Color: Weak uptrend only supported by Slope or whatever you’ve selected.
Red Color: Strong Downtrend supported by Volume and Volatility or whatever you’ve chosen from both of them.
Grey Color: Weak Downtrend only supported by Slope or whatever you’ve selected.
Yellow Color: Possible reversal indication by Slope if enabled. Market is either sideways, consolidating or showing choppiness during that period.
SIGNALS
Green Circle: Market good for long with support of Volume and Volatility or whatever you’ve chosen from both of them.
Red Circle: Market good to short with support from Volume and Volatility or whatever you’ve chosen from both of them.
Yellow Cross: Market either touched top or bottom ATR band and can act as good TP or SL.
EDSMA EVELOPE/BANDS: I’ve included ATR based bands to the Adaptive EDSMA which act as good support/resistance despite from main Adaptive EDSMA Curve.
DEFAULT SETTINGS
I’ve set default Minimum length to 50 and Maximum length to 255 which I’ve found works best for almost all timeframes but you can change this delta to adapt your timeframe accordingly with more precision.
Dynamic length adoption is enabled based on both Volume and Volatility but only one or none of them can also be selected.
Trend signals are enabled based on Slope and Volume but Volatility can be enabled for more precise confirmations.
In “ RVSI ” settings TFS Volume Oscillator is set to default but others work good too especially Volume Zone Oscillator. For more details about Volume Breakout you can check “MZ RVSI Indicator".
ATR breakout is set to be positive if period 14 exceeds period 46 but can be changed if more adaption with volatility is required.
EDSMA super smoother filter length is set to 20 which can be increased to 50 or more for better smoothing but this will also change slope results accordingly.
EDSMA super smoother filter poles are set to 2 because found better results with 2 instead of 3.
FURTHER ENHANCEMENTS
So far, I’ve seen better results with Volume Breakout and Volatility but other parameters such as Linear Slope of Particular MA, MACD, “MZ SRSI ”, a Conditional Uptrend MA or simply KDJ can also be used for dynamic length adaption.
I haven't yet gotten used to pine script arrays so, defining and using conditional operators is pretty much lazy programming for me. Would be great redefining everything through truth matrix instead of using if-else conditions.
Configurable Multi MA Crossover Voting SystemThis strategy goes long when all fast moving averages that you have defined are above their counterpart slow moving averages.
Long position is closed when profit or loss target is hit and at least one of the fast moving averages is below its counterpart slow moving average.
The format of the config is simple. The format is : FASTxSLOW,FASTxSLOW,...
Example : If you want 2 moving averages fast=9,slow=14 and fast=20,slow=50 you define it like this : 9x14,20x50
Another example : 5x10,10x15,15x20 => means 3 moving average setups : first wih fast=5/slow=10, second with fast=10/slow=15, last with fast=15/slow=20
You can chose the type of moving average : SMA, WMA, VWMA (i got issues with EMA/RMA so i removed them)
You can chose the source of the moving average : high, close, hl2 etc.
You can chose the period on which ATR is calculated and ATR profit/loss factors.
Profit is calculated like : buy_price + atr_factor*atr
Loss is calculated like : buy_price - atr_factor*atr
Performance in backtest is variable depending on the timeframe, the options and the market.
Performance in backtest suggests it works better for higher timeframes like 1d, 4h etc.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
Moving Average MultitoolI made this script as a personal tool while backtesting multiple moving averages. It allows you to easily access and switch between different types of moving averages, without having to continuously add and remove different moving averages from your chart.
It also has the option to show the a 14 period average distance between the closing price of an asset and the selected moving average, as a multiple of ATR. This number can be shown by enabling the "Show ATR Between MA and Close" setting. The intention of this value is to quantify and compare the speed of different moving averages across any instrument and any timeframe. The higher the value, the slower the moving average. The lower the value, the faster the moving average.
MACD PlusMoving Average Convergence Divergence – MACD
The MACD is an extremely popular indicator used in technical analysis. It can be used to identify aspects of a security's overall trend. Most notably these aspects are momentum, as well as trend direction and duration. What makes the MACD so informative is that it is actually the combination of two different types of indicators. First, the MACD employs two Moving Averages of varying lengths (which are lagging indicators) to identify trend direction and duration. Then, it takes the difference in values between those two Moving Averages (MACD Line) and an EMA of those Moving Averages (Signal Line) and plots that difference between the two lines as a histogram which oscillates above and below a center Zero Line. The histogram is used as a good indication of a security's momentum.
Added Color Plots to Settings Pane.
Switched MTF Logic to turn ON/OFF automatically w/ TradingView's Built in Feature.
Added Ability to Turn ON/OFF Show MacD & Signal Line.
Added Ability to Turn ON/OFF Show Histogram.
Added Ability to Change MACD Line Colors Based on Trend.
Added Ability to Highlight Price Bars Based on Trend.
Added Alerts to Settings Pane.
Customized Alerts to Show Symbol, TimeFrame, Closing Price, MACD Crosses Up & MACD Crosses Down Signals in Alert.
Alerts are Pre-Set to only Alert on Bar Close.
Added ability to show Dots when MACD Crosses.
Added Ability to Change Plot Widths in Settings Pane.
Added in Alert Feature where Cross Up if above 0 or cross down if below 0 (OFF By Default).
Squeeze Pro
Traditionally, John Carter's version uses 20 period SMAs as the basis lines on both the BB and the KC.
In this version, I've given the freedom to change this and try out different types of moving averages.
The original squeeze indicator had only one Squeeze setting, though this new one has three.
The gray dot Squeeze, call it a "low squeeze" or an "early squeeze" - this is the easiest Squeeze to form based on its settings.
The orange dot Squeeze is the original from the first Squeeze indicator.
And finally, the yellow dot squeeze, call it a "high squeeze" or "power squeeze" - is the most difficult to form and suggests price is under extreme levels of compression.
Colored Directional Movement Index (CDMI) , a custom interpretation of J. Welles Wilder’s Directional Movement Index (DMI), where :
DMI is a collection of three separate indicators ( ADX , +DI , -DI ) combined into one and measures the trend’s strength as well as its direction
CDMI is a custom interpretation of DMI which presents ( ADX , +DI , -DI ) with a color scale - representing the trend’s strength, color density - representing momentum/slope of the trend’s strength, and triangle up/down shapes - representing the trend’s direction. CDMI provides all the information in a single line with colored triangle shapes plotted on the bottom. DMI can provide quality information and even trading signals but it is not an easy indicator to master, whereus CDMI simplifies its usage. The CDMI adds additional insight of verifying/confirming the trend as well as its strength
Label :
Displaying the trend strength and direction
Displaying adx and di+/di- values
Displaying adx's momentum (growing or falling)
Where tooltip label describes "howto read colored dmi line"
Ability to display historical values of DMI readings displayed in the label.
Added "Expert Trend Locator - XTL"
The XTL was developed by Tom Joseph (in his book Applying Technical Analysis ) to identify major trends, similar to Elliott Wave 3 type swings.
Blue bars are bullish and indicate a potential upwards impulse.
Red bars are bearish and indicate a potential downwards impulse.
White bars indicate no trend is detected at the moment.
Added "Williams Vix Fix" signal. The Vix is one of the most reliable indicators in history for finding market bottoms. The Williams Vix Fix is simply a code from Larry Williams creating almost identical results for creating the same ability the Vix has to all assets.
The VIX has always been much better at signaling bottoms than tops. Simple reason is when market falls retail traders panic and increase volatility , and professionals come in and capitalize on the situation. At market tops there is no one panicking... just liquidity drying up.
The FE green triangles are "Filtered Entries"
The AE green triangles are "Aggressive Filtered Entries"
3SMA + Ichimoku 2leadlineThis indicator simultaneously displays two lines, which are the leading spans of the Ichimoku Kinko Hyo, and three simple moving averages.
To make it easier to distinguish between the simple moving average line and the line of the Ichimoku Kinko Hyo, the simple moving average line is set to level 2 thickness by default.
Also, the color of Reading Span 1 in the Ichimoku Kinko Hyo has been changed from green to lime to improve color visibility.
I (author of this indicator) use this indicator especially as a simple perspective on the cryptocurrency BTC / USD(USDT).
If this indicator is a problem, moderators don't know about tradingview beginners.
" Visibility " should be a high-priority item not only for indicators but also for graph requirements.
Visibility is one of the most important factors for investors who have to make instant decisions in one minute and one second.
The purpose of this indicator is to display two leading spans that are easily noticed in the Ichimoku cloud and three simple moving averages whose set values can be changed.
This is because chart analysis often uses a combination of a simple moving average of three periods and two lead spans of the Ichimoku cloud.
Also, in chart analysis, green is often displayed with the same thickness on both the moving average line and the Ichimoku cloud.
Therefore, if the moving average line and the Ichimoku cloud often use the same green color, the visibility will drop. Therefore, the green color of Ichimoku cloud was changed to lime color by default.
Tradingview beginners often refer only to the two lines of the leading span of Ichimoku Cloud. Therefore, we decided not to draw lines that are difficult to use.
Many Tradingview beginners don't know that you can change the thickness of the indicator .
Therefore, this indicator shows by DEFAULT the three commonly used simple moving averages that are thickened by one step at the same time.
Also, since the same green color is often used for the Ichimoku cloud and the moving average line, the green color of the preceding span of the Ichimoku cloud is changed to lime color by default.
The originality of this indicator is that it enhances " visibility " so that novice tradingview users will not be confused on the chart screen.
The lines other than the preceding span of the Ichimoku cloud are not displayed, and the moving average line is level 2 thick so that the user can easily see it.
This indicator not only combines a simple moving average and Ichimoku cloud, but also improves "visibility" by not incorporating lines that are difficult to see from the beginning and making it only the minimum display, making it easy for beginners to understand. The purpose is to do.
If any of the other TradingView indicators already meet the following, acknowledge that this indicator is not original.
・Display 3 simple moving averages at the same time
・For visibility, the thickness of the simple moving average line is set to level 2 from the beginning.
・A setting that does not dare to draw lines other than the lead span of Ichimoku cloud.
・Make the moving average line and the Ichimoku cloud line different colors and thicknesses from the beginning.
On Balance Volume FieldsThe On Balance Volume (OBV) indicator was developed by Joseph E. Granville and published first in his book "New key to stock market profits" in 1963. It uses volume to determine momentum of an asset. The base concept of OBV is - in simple terms - you take a running total of the volume and either add or subtract the current timeframe volume if the market goes up or down. The simplest use cases only use the line build that way to confirm direction of price, but the possibilities and applications of OBV go far beyond that and are (at least to my knowledge) not found in existing indicators available on this platform.
If you are interested to get a deeper understanding of OBV, I recommend the lecture of the above mentioned book by Granville. All the features described below are taken directly from the book or are inspired by it (deviations will be marked accordingly). If you have no prior experience with OBV, I recommend to start simple and read an easy introduction (e.g. On-Balance Volume (OBV) Definition from Investopedia) and start applying the basic concepts first before heading into the more advanced analysis of OBV fields and trends.
Markets and Timeframes
As the OBV is "just" a momentum indicator, it should be applicable to any market and timeframe.
As a long term investor, my experience is limited to the longer timeframes (primarily daily), which is also how Granville applies it. But that is most likely due to the time it was developed and the lack of lower timeframe data at that point in time. I don't see why it wouldn't be applicable to any timeframe, but cannot speak from experience here so do your own research and let me know. Likewise, I invest in the crypto markets almost exclusively and hence this is where my experience with this indicator comes from.
Feature List
As a general note before starting into the description of the individual features: I use the colors and values of the default settings of the indicator to describe it. The general look and feel obviously can be customized (and I highly recommend doing so, as this is a very visual representation of volume, and it should suit your way of looking at a chart) and I also tried to make the individual features as customizable as possible.
Also, all additions to the OBV itself can be turned off so that you're left with just the OBV line (although if that's what you want, I recommend a version of the indicator with less overhead).
Fields
Fields are defined as successive UPs or DOWNs on the OBV. An UP is any OBV reading above the last high pivot and subsequently a DOWN is any reading below the last low pivot. An UP-field is the time from the first UP after a DOWN-field to the first DOWN (not including). The same goes for a DOWN field but vice versa.
The field serves the same purpose as the OBV itself. To indicate momentum direction. I haven't found much use for the fields themselves other than serving as a more smoothed view on the current momentum. The real power of the fields emerges when starting to determine larger trends of off them (as you will see soon).
Therefor the fields are displayed on the indicator as background colors (UP = green, DOWN = red), but only very faint to not distract too much from the other parts of the indicator.
Major Volume Trend
The major volume trend - from which Granville says, it's the one that tends to precede price - is determined as the succession of the highest highs and lowest lows of UP and DOWN fields. It is represented by the colors of the numbers printed on the highs and lows of the fields.
The trend to be "Rising" is defined as the highest high of an UP field being higher than the highest high of the last UP field and the lowest low of the last DOWN field being higher than the lowest low of the prior DOWN field. And vice versa for a "Falling" trend. If the trend does not have a rising or falling pattern, it is said to be "Doubtful". The colors are indicated as follows:
Rising = green
Falling = red
Doubtful = blue
ZigZag Swing count
The swing count is determined by counting the number of swings within a trend (as described above) and is represented by the numbers above the highs and lows of the fields. It determines the length and thus strength of a trend.
In general there are two ways to determine the count. The first one is by counting the swings between pivots and the second one by counting the swings between highs and lows of fields. This indicator represents the SECOND one as it represents the longer term trend (which I'm more interested in as it denotes a longer term perspective).
However, the ZigZag count has three applications on the OBV. The "simple ZigZag" is a count of three swings which mainly tells you that the shorter term momentum of the market has changed and the current trend is weakening. This doesn't mean it will reverse. A count of three downs is still healthy if it occurs on a strong uptrend (and vice versa) and it should primarily serve as a sign of caution. If the count increases beyond three, the last trend is weakening considerably, and you should probably take action.
The second count to look out for is five swings - the "compound ZigZag". If this goes hand in hand with breaking a major support/resistance on the OBV it can offer a buying/selling opportunity in the direction of the trend. Otherwise, there's a good chance that this is a reversal signal.
The third count is nine. To quote Granville directly: "there is a very strong tendency FOR MAJOR REVERSAL OF REND AFTER THE NINTH SWING" (emphasis by the author). This is something I look out for and get cautious about, although I have found signal to be weak in an overextended market. I have observed counts of 10 and even 12 which did not result in a major reversal and the market trended further after a short period of time. This is still a major sign of caution and should not be taken lightly.
Moving average
Although Granville talks only briefly about averages and the only mention of a specific one is the 10MA, I found moving averages to be a very valuable addition to my analysis of the OBV movements.
The indicator uses three Exponential Moving Averages. A long term one to determine the general direction and two short term ones to determine the momentum of the trend. Especially for the latter two, keep in mind that those are very indirect as they are indicators of an indicator anyway and I they should not necessarily be used as support or resistance (although that might sometimes be helpful). I recommend paying most attention to the longterm average as I've found it to be very accurate when determining the longterm trend of a market (even better than the same indicator on the price).
If the OBV is above the long term average, the space between OBV and average is filled green and filled red if below. The colors and defaults for the averages are:
long term, 144EMA, green
short term 1, 21EMA, blue
short term 2, 55EMA, red
Divergences
This is a very rudimentary adaption of the standard TradingView "Divergence Indicator". I find it helpful to have these on the radar, but do not actively use them (as in having a strategy based on OBV/price divergence). This is something that I would eventually pick up in a later version of the indicator if there is any demand for it, or I find the time to look into strategies based on this.
Comparison line
A small but very helpful addition to the indicator is a horizontal line that traces the current OBV value in real time, which makes it very easy to compare the current value of the OBV to historic values (which is a study I can highly recommend).
Tilson T3 and MavilimW Triple Combined StrategyInspired by truly greatful Kivanç Ozbilgic (www.tradingview.com).
The strategy tries to combined three different moving average strategies into one.
Strategies covered are:
1. Tillson T3 Moving Average Strategy
Developed by Tim Tillson, the T3 Moving Average is considered superior to traditional moving averages as it is smoother, more responsive and thus performs better in ranging market conditions as well. However, it bears the disadvantage of overshooting the price as it attempts to realign itself to current market conditions.
It incorporates a smoothing technique which allows it to plot curves more gradual than ordinary moving averages and with a smaller lag. Its smoothness is derived from the fact that it is a weighted sum of a single EMA, double EMA, triple EMA and so on. When a trend is formed, the price action will stay above or below the trend during most of its progression and will hardly be touched by any swings. Thus, a confirmed penetration of the T3 MA and the lack of a following reversal often indicates the end of a trend. Here is what the calculation looks like:
T3 = c1*e6 + c2*e5 + c3*e4 + c4*e3, where:
– e1 = EMA (Close, Period)
– e2 = EMA (e1, Period)
– e3 = EMA (e2, Period)
– e4 = EMA (e3, Period)
– e5 = EMA (e4, Period)
– e6 = EMA (e5, Period)
– a is the volume factor, default value is 0.7 but 0.618 can also be used
– c1 = – a^3
– c2 = 3*a^2 + 3*a^3
– c3 = – 6*a^2 – 3*a – 3*a^3
– c4 = 1 + 3*a + a^3 + 3*a^2
T3 MovingThe T3 Moving Average generally produces entry signals similar to other moving averages and thus is traded largely in the same manner.
Strategy for Tillson T3 is if the close crossovers T3 line and for at least five bars the close was under the T3
2. Tillson T3 Fibonacci Cross
Kivanc Ozbilgic added a second T3 line with a volume factor of 0.618 (Fibonacci Ratio) and length of 3 (fibonacci number) which can be added by selecting the T3 Fibonacci Strategy input box.
Strategy for Tillson T3 Fibo is when the Fibo Line crossover the T3 it gives long signal vice versa.
3. MavilimW
MavilimW is originally a support and resistance indicator based on fibonacci injected weighted moving averages.
Strategy for MavilimW is is if the close crossovers T3 line and for at least five bars the close was under the T3
Hope you enjoy
Pivot TrendHello Traders,
Another original idea is here with you. Actualy I can say that it's a breakout strategy that uses multiple Pivot Point's averages.
How it works?
- it finds the Pivot Points, you can set the length as you want
- it gets averages of Pivot Highs and Pivot Lows, you can set the number of Pivot Points to be included
- it compares the current closing price with averages of Pivot Highs and Pivot Lows
- if both are positive or negative then trend changes
You have two options:
- Pivot Point Period => is the length that is used to find Pivot Points. means it checks left/right bars if it's Pivot Point (4 by default)
- Number of PP to check => is the number of Pivot Points that the script finds and calculates the averages (3 by default)
An Example with the settings Pivot Point Period = 5 and Number of PP to check = 2
Play with settings as you wish. Comments are welcome, together we can improve it ;)
Enjoy!
eha MA CrossIn the study of time series, and specifically technical analysis of the stock market, a moving-average cross occurs when, the traces of plotting of two moving averages each based on different degrees of smoothing cross each other. Although it does not predict future direction but at least shows trends.
This indicator uses two moving averages, a slower moving average and a faster-moving average. The faster moving average is a short term moving average. A short term moving average is faster because it only considers prices over a short period of time and is thus more reactive to daily price changes.
On the other hand, a long term moving average is deemed slower as it encapsulates prices over a longer period and is more passive. However, it tends to smooth out price noises which are often reflected in short term moving averages.
There are a bunch of parameters that you can set on this indicator based on your needs.
Moving Averages Algorithm
You can choose between three types provided of Algorithms
Simple Moving Average
Exponential Moving Average
Weighted Moving Average
I will update this study with more educational materials in the near future so be informed by following the study and let me know what you think about it.
Please hit the like button if this study is useful for you.
GMS: Moving Average IndicatorThis is a moving average indicator built the way I would want it. There are 3 moving averages with On/Off toggles. It makes it easier than having to add each one separately over and over. Now it's nice and easy all in one spot!
- The moving averages are SMA, EMA, WMA, VWMA and can select anyone for each of the 3 moving averages.
- You can also select the data used for the moving averages (OHLC etc.)
Source code should be open, so feel free to take a look and use it for you own project or ideas.
I hope this helps!
Andre
Supertrend0913This Pine Script (`@version=6`) combines **two Supertrend indicators** and a set of **moving averages (EMA & MA)** into one overlay chart tool for TradingView.
**Key features:**
* **Supertrend \ & \ :**
* Each has independent ATR period, multiplier, and ATR calculation method.
* Plots trend lines (green/red for \ , blue/yellow for \ ).
* Generates **buy/sell signals** when trend direction changes.
* Includes **alert conditions** for buy, sell, and trend reversals.
* **Moving Averages:**
* 6 EMAs (lengths 21, 55, 100, 200, 300, 400).
* 5 SMAs (lengths 11, 23, 25, 39, 200).
* Each plotted in different colors for trend visualization.
👉 In short: it’s a **combined trading tool** that overlays two configurable Supertrend systems with alerts plus multiple EMAs/SMAs to help identify trend direction, signals, and potential entry/exit points.
ZLEMA Trend Index 2.0ZTI — ZLEMA Trend Index 2.0 (0–1000)
Overview
Price Mapped ZTI v2.0 - Enhanced Zero-Lag Trend Index.
This indicator is a significant upgrade to the original ZTI v1.0, featuring enhanced resolution from 0-100 to 0-1000 levels for dramatically improved price action accuracy. The Price Mapped ZTI uses direct price-to-level mapping to eliminate statistical noise and provide true proportional representation of market movements.
Key Innovation: Instead of statistical normalization, this version maps current price position within a user-defined lookback period directly to the ZTI scale, ensuring perfect correlation with actual price movements. I believe this is the best way to capture trends instead of directly on the charts using a plethora of indicators which introduces bad signals resulting in drawdowns. The RSI-like ZTI overbought and oversold lines filter valid trends by slicing through the current trading zone. Unlike RSI that can introduce false signals, the ZTI levels 1 to 1000 is faithfully mapped to the lowest to highest price in the current trading zone (lookback period in days) which can be changed in the settings. The ZTI line will never go off the beyond the ZTI levels in case of extreme trend continuation as the trading zone is constantly updated to reflect only the most recent bars based on lookback days.
Core Features
✅ 10x Higher Resolution - 0-1000 scale provides granular movement detection
✅ Adjustable Trading Zone - Customizable lookback period from 1-50 days
✅ Price-Proportional Mapping - Direct correlation between price position and ZTI level
✅ Zero Statistical Lag - No rolling averages or standard deviation calculations
✅ Multi-Strategy Adaptability - Single parameter adjustment for different trading styles
Trading Zone Optimization
📊 Lookback Period Strategies
Short-term (1-3 days):
Ultra-responsive to recent price action
Perfect for scalping and day trading
Tight range produces more sensitive signals
Medium-term (7-14 days):
Balanced view of recent trading range
Ideal for swing trading
Captures meaningful support/resistance levels
Long-term (21-30 days):
Broader market context
Excellent for position trading
Smooths out short-term market noise
⚡ Market Condition Adaptation
Volatile Markets: Use shorter lookback (3-5 days) for tighter ranges
Trending Markets: Use longer lookback (14-21 days) for broader context
Ranging Markets: Use medium lookback (7-10 days) for clear boundaries
🎯 Timeframe Optimization
1-minute charts: 1-2 day lookback
5-minute charts: 2-5 day lookback
Hourly charts: 7-14 day lookback
Daily charts: 21-50 day lookback
Trading Applications
Scalping Setup (2-day lookback):
Super tight range for quick reversals
ZTI 800+ = immediate short opportunity
ZTI 200- = immediate long opportunity
Swing Trading Setup (10-day lookback):
Meaningful swing levels captured
ZTI extremes = high-probability reversal zones
More stable signals, reduced whipsaws
Advanced Usage
🔧 Real-Time Adaptability
Trending days: Increase to 14+ days for broader perspective
Range-bound days: Decrease to 3 days for tighter signals
High volatility: Shorter lookback for responsiveness
Low volatility: Longer lookback to avoid false signals
💡 Multi-Timeframe Approach
Entry signals: Use 7-day ZTI on main timeframe
Trend confirmation: Use 21-day ZTI on higher timeframe
Exit timing: Use 3-day ZTI for precise exits
🌐 Session Optimization
Asian session: Shorter lookback (3-5 days) for range-bound conditions
London/NY session: Longer lookback (7-14 days) for trending conditions
How It Works
The indicator maps the current price position within the specified lookback period directly to a 0-1000 scale and plots it using ZLEMA (Zero Lag Exponential Moving Average) which has the least lag of the available popular moving averages:
Price at recent high = ZTI at 1000
Price at recent low = ZTI at 1
Price at mid-range = ZTI at 500
This creates perfect proportional representation where every price movement translates directly to corresponding ZTI movement, eliminating the false signals common in traditional oscillators.
This single, versatile indicator adapts to any market condition, timeframe, or trading style through one simple parameter adjustment, making it an essential tool for traders at every level.
Credits
ZLEMA techniques widely attributed to John Ehlers.
Disclaimer
This tool is for educational purposes only and is not financial advice. Backtest and forward‑test before live use, and always manage risk.
Please note that I set this as closed source to prevent source code cloning by others, repackaging and republishing which results in multiple confusing choices of the same indicator.
BTC Evaluation IndicatorBTC Evaluation Indicator
The BTC Evaluation Indicator is a volatility-based tool designed to help traders evaluate Bitcoin’s price behavior relative to its moving average trend. It combines customizable moving averages with dynamic standard deviation bands to identify overbought and oversold conditions.
Key Features
Flexible Moving Averages: Choose between SMA, EMA, WMA, VWMA, HMA, or RMA for the baseline trend.
Dynamic Volatility Bands: Upper and lower bands are calculated using standard deviation, scaled by a user-defined multiplier.
Visual Clarity:
Orange line = central moving average (trend mean)
Green line = upper band (potential overbought zone)
Red line = lower band (potential oversold zone)
Shaded gray area = volatility range
Automatic Highlights: Background shading marks when price breaks above the upper band (overbought) or below the lower band (oversold).
How to Use
When price pushes above the upper band, it may indicate overextension or potential local overbought conditions.
When price falls below the lower band, it may signal undervaluation or potential oversold conditions.
The mean line acts as a dynamic equilibrium, often serving as short-term support/resistance.
This indicator is designed for Bitcoin evaluation, but it can be applied to any asset. By combining trend analysis with volatility context, it helps traders better understand when price may be stretched and when conditions are reverting to the mean.
