Multi Moving Average with CustomizationCore Functionality
The indicator allows you to display up to 5 different moving averages on your chart simultaneously.
Each moving average can be fully customized with its own settings.
You can choose between
1. Simple Moving Average (SMA),
2. Exponential Moving Average (EMA)
3. Weighted Moving Average (WMA) types
Multi-Timeframe Support
One standout feature is the ability to display higher timeframe moving averages on lower timeframe charts.
For example, you can show a 200 EMA from the daily chart while viewing a 15-minute chart.
Advanced Visualization Features
The indicator includes several visualization enhancements:
1. MA Cloud - Creates a filled area between any two selected moving averages. The cloud automatically changes color based on which MA is on top - typically green when the faster MA is above (bullish) and red when below (bearish).
2. Golden/Death Cross Detection - Automatically detects and marks important MA crossover events:
* Golden Cross: When a shorter-term MA crosses above a longer-term MA (bullish signal)
* Death Cross: When a shorter-term MA crosses below a longer-term MA (bearish signal)
3. Trend Background - Colors the entire chart background based on whether price is above or below a specified MA, giving a clear visual indicator of the overall trend.
Alert System
The indicator can generate alerts when price crosses above or below any selected moving average. This feature is useful for automated trading signals or notifications, and can be configured to trigger once per bar.
Flexible Architecture
The code uses several programming techniques to maximize flexibility:
* Switch statements for selecting MA types and cloud values
* Conditional logic throughout the code
* Function abstraction for calculating MAs and handling multi-timeframe display
* String identifiers to select which MAs to use for cloud visualization
Unique Technical Aspects
1. The multi-timeframe plotting function solves the common problem of higher timeframe MAs looking distorted on lower timeframe charts.
2. The cloud feature uses string identifiers to select which MAs to use, allowing for any combination.
3. The indicator employs smart conditional logic to handle complex decision trees efficiently.
4. Every visual aspect (colors, line widths, display conditions) is customizable through the settings.
This indicator combines multiple technical analysis tools into a single, highly configurable package that can adapt to different trading styles and timeframes.
Its ability to correctly display higher timeframe MAs on lower timeframe charts makes it particularly valuable for traders who analyze multiple timeframes simultaneously.
스크립트에서 "Exponential Moving Average"에 대해 찾기
MENTFX AVERAGES MULTI TIMEFRAMEThe MENTFX AVERAGES MULTIME TIMEFRAME indicator is designed to provide traders with the ability to visualize multiple moving averages (MAs) from higher timeframes on their current chart, regardless of the chart's timeframe. It combines the power of exponential moving averages (EMAs) to help traders identify trends, spot potential reversal points, and make more informed trading decisions.
Key Features:
Multi-Timeframe Moving Averages: This indicator plots moving averages from daily timeframes directly on your chart, helping you keep track of higher timeframe trends while trading in any timeframe.
Customizable Moving Averages: You can adjust the length and visibility of up to three EMAs (default settings are 5, 10, and 20-period EMAs) to suit your trading style.
Overlay on Price: The indicator is designed to be overlaid on your price chart, seamlessly integrating with your existing analysis.
Simple but Effective: By offering a clear visual guide to where price is trading relative to important higher timeframe levels, this indicator helps traders avoid trading against major trends.
Why It’s Unique:
Validation Timeframe Flexibility: Unlike traditional moving average indicators that only work within the same chart's timeframe, the MENTFX AVERAGES M indicator allows you to pull moving averages from higher timeframes (default: Daily) and overlay them on any chart you're currently viewing, whether it's intraday (minutes) or even weekly. This cross-timeframe visibility is critical in determining the true market trend, adding context to your trades.
Customizability: Although the default settings focus on daily EMAs (5, 10, and 20 periods), traders can modify the parameters, including the type of moving average (Simple, Weighted, etc.), making it adaptable for any strategy. Whether you want shorter-term or longer-term averages, this indicator covers your needs.
Trend Confirmation Tool: The use of multiple EMAs helps traders confirm trend direction and potential price breakouts or reversals. For example, when the shorter-term 5 EMA crosses above the 20 EMA, it can signal a potential bullish trend, while the opposite could indicate bearish pressure.
How This Indicator Helps:
Identify Key Support and Resistance Levels: Higher timeframe moving averages often act as dynamic support and resistance. This indicator helps you stay aware of those critical levels, even when trading lower timeframes.
Trend Identification: Knowing where the market is relative to the 5, 10, and 20 EMAs from a higher timeframe gives you a clearer picture of whether you're trading with or against the prevailing trend.
Improved Decision Making: By aligning your trades with the direction of higher timeframe trends, you can increase your confidence in trade entries and exits, avoiding low-probability setups.
Multi-Market Use: This indicator works well across various asset classes—stocks, forex, crypto, and commodities—making it versatile for any trader.
How to Use:
Intraday Trading: Use the daily EMAs as a guide to see if intraday price movements align with longer-term trends.
Swing Trading: Plot daily EMAs to track the strength of a larger trend, using pullbacks to the moving averages as potential entry points.
Trend Trading: Monitor crossovers between the moving averages to signal potential changes in trend direction.
Default Settings:
5 EMA (Daily) – Blue Line
10 EMA (Daily) – Black Line
20 EMA (Daily) – Red Line
These lines will plot on your chart with a subtle opacity (33%) to ensure they don’t obstruct price action, while still providing crucial visual guidance on market trends.
This indicator is perfect for traders who want to blend technical analysis with multi-timeframe insights, helping you stay in sync with broader market movements while executing trades on any timeframe.
Three Anchored Moving Averages (VWAP / SMA / EMA)
This indicator allows users to anchor three types of moving averages (Simple Moving Average (SMA), Exponential Moving Average (EMA), and Volume Weighted Average Price (VWAP)) to specific points in time (anchor points)
Key Features:
Select from three Moving Average Types:
Simple Moving Average (SMA): Averages the closing prices over a specified period.
Exponential Moving Average (EMA): Gives more weight to recent prices, making it more responsive to new information.
Volume Weighted Average Price (VWAP): Averages the price weighted by volume, useful for understanding the average price at which the asset has traded over a period.
Up to Three Anchor Points:
Users can set up to three different anchor points to calculate the moving averages from specific dates and times. This allows for analysis of price action starting from significant points or specific events. For example, you can anchor to the low and high of a move to identify key levels or to points where the price takes off from a previous anchored MA.
Customisable Sentiment Options:
Each anchor point can be associated with a sentiment input (Auto, Bull, Bear, None), which influences if the MAs are displayed as lines or zones/bands:
Auto: Automatically determines the sentiment based on whether anchor points are on pivot highs and lows. If anchored to a pivot high, the system will assume a bearish sentiment and display a red band or zone between the MA OHLC4 and High. Anchoring to a pivot low will display a green band (OHLC4 - Low).
Bull: Forces a bullish sentiment (Green Band - OHLC4 to Low)
Bear: Forces a bearish sentiment (Red Band - OHLC4 to High)
None: Ignores sentiment and displays a single line (OHLC4)
Chart Matching:
The indicator includes an option to display the moving averages only if the chart symbol matches a specified ticker. This feature ensures that the indicator is relevant to the specific asset being analysed.
How to Use the Indicator:
1. Set Anchor Points: When added to your chart, select three anchor points by point and click. If you only wish to anchor to a single point, click on that point three times and disable the other two in settings once the indicator is applied.
2. Select Moving Average Type: Choose between SMA, EMA, or VWAP using the dropdown menu. EMAs are the most responsive.
3. Enable/Disable Anchor Points: Use the checkboxes to enable or disable each anchor point.
4. Select Sentiment Type: Choose between Auto, Bull, Bear, or None.
5. Chart Matching: Optionally, specify a chart symbol to restrict the indicator's display to that particular asset.
6. Interpret the Plots: The indicator plots the high, mid, and low values of the selected moving average type from each anchor point. The fills between these plots help identify potential support and resistance zones. These should be used as points of interest for pullback reversals or potential continuation if the price breaks through.
Practical Applications:
Trend Analysis: Identify the overall trend direction from specific historical points.
Support and Resistance: Determine key dynamic support and resistance levels based on anchored moving averages.
Event-Based Analysis: Anchor the moving averages to significant events (e.g., earnings releases, economic data) to study their impact on price trends.
Multi Timeframe Analysis: Higher Timeframe Anchors can be used to identify longer term trend analysis. Switching to a lower timeframe for execution triggers at these points wont distort the MA levels as they are anchored to a specific point in time
Intraday or Swing Trading: trend analysis using anchor points can be used for any style of trading (Intraday / Swing / Invest). Use anchored levels as points of interest and wait for hints in price action to try and catch the next move.
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.
Scalping The Bull IndicatorName: Scalping The Bull Indicator
Category: Scalping, Trend Following, Mean Reversion.
Timeframe: 1M, 5M, 30M, 1D depending on the specific technique.
Technical Analysis: The indicator supports the operations of the trader named "Scalping The Bull" which uses price action and exponential moving averages.
Suggested usage: Altcoin showing strong trends for scalping and intra-day trades. Trigger points are used as entry and exit points and to be used to understand when a signal has more power.
It is possible to identify the following conformations:
Shimano: look at the price records of a consecutive series of closings between the EMA 60 and the EMA 223 when a certain threshold is reached. Use the trigger points as price structures to identify entry and exit zones (e.g. breakout of the yesterday high as for entry point) .
Bomb: look at the price registers a percentage variation in a single candle, greater than a threshold such as 2%, in particular on shorter timeframes and around the trigger points.
Viagra: look at there is a consecutive series of closes below the EMA 10.
Downward fake: look when, after a cross under (Death Cross), the price returns above the EMA 223 using the yesterday high as a trigger point.
Emergence: look at the EMA 60 is about to cross over the EMA 223.
Anti-crossing: look at, after an important price rise and a subsequent retracement, the EMA 60 is about to cross under the EMA 223 but a bullish impulse brings the price back above the EMAs.
For Sales: look at two types of situations: 1) when the price falls by more than 10% from the opening price and around the yesterday’s low or 2) when the price falls and then reaches, in the last 5 days, a bigger percentage and then breaks a trigger point.
Colour change: look at the opening price of the session - indicated as a trigger point.
Third touch of EMA 60: look for 3 touches below the EMA 60, and enter when there is a close above the EMA 60.
Third touch of EMA 223: look for 3 touches when there are 3 touches below the EMA 223, and enter when there is a close above the EMA 60.
Bud: look at price when it crosses upwards the average 10 and subsequently at least 2 "rest" candles are between the maximum and minimum of the breaking candle.
Fake on EMA 10: look for the open of a candle higher than the EMA 10, the minimum of the candle lower and the closing price returns above the EMA 10..
For Stop Loss and Profit Targets consider a proper R/R depending on Risk Management, using price structures such as the low of the entering candle and a quick Position Management moving quickly the Stop-Loss at Break-Even.
Configuration:
Market
EMA: The indicator automatically configure itself on market it knows (Binance, Piazza Affari and NASDAQ) otherwise it can be configured manually fo Crypto market (5/10/60/223) or Stock Market (5/10/50/200).
Additional Average: You can display an additional average, e.g. 20-period average.
Chart elements:
Session Separators: indicates the beginning of the current session (in blue)
Background: signals with the background in green an uptrend situation ( 60 > 223) and in red background a downtrend situation (60 < 223).
Trigger points:
Today's highs and lows: draw on the chart the opening price of the daily candle and the highs and lows of the day (high in purple, low in red and open in green)
Yesterday's highs and lows: draw on the chart the opening price of the daily candle, the highs and lows of the previous day (high in yellow, low in red).
Credits
Massimo : for refactoring and suggestions.
AMACD - All Moving Average Convergence DivergenceThis indicator displays the Moving Average Convergane and Divergence ( MACD ) of individually configured Fast, Slow and Signal Moving Averages. Buy and sell alerts can be set based on moving average crossovers, consecutive convergence/divergence of the moving averages, and directional changes in the histogram moving averages.
The Fast, Slow and Signal Moving Averages can be set to:
Exponential Moving Average ( EMA )
Volume-Weighted Moving Average ( VWMA )
Simple Moving Average ( SMA )
Weighted Moving Average ( WMA )
Hull Moving Average ( HMA )
Exponentially Weighted Moving Average (RMA) ( SMMA )
Symmetrically Weighted Moving Average ( SWMA )
Arnaud Legoux Moving Average ( ALMA )
Double EMA ( DEMA )
Double SMA (DSMA)
Double WMA (DWMA)
Double RMA ( DRMA )
Triple EMA ( TEMA )
Triple SMA (TSMA)
Triple WMA (TWMA)
Triple RMA (TRMA)
Linear regression curve Moving Average ( LSMA )
Variable Index Dynamic Average ( VIDYA )
Fractal Adaptive Moving Average ( FRAMA )
If you have a strategy that can buy based on External Indicators use 'Backtest Signal' which returns a 1 for a Buy and a 2 for a sell.
'Backtest Signal' is plotted to display.none, so change the Style Settings for the chart if you need to see it for testing.
3 EMA/SMA + Colored Candles[C2Trends]// Indicator Features:
// 1) 3 Exponential Moving Averages and 3 Simple Moving Averages.
// 2) Additional EMA input for colored candles(EMA is hidden from chart, input used for coloring of candles only)
// 3) Turn colored candles on/off from main input tab of indicator settings.
// 4) Turn SMA's and EMA's on/off from main input tab of indicator settings.
// 5) Select single color or 2 color EMA and SMA lines from main input tab of indicator settings.
// Indicator Notes:
// 1) 'Candle EMA' input is the trend lookback period for the price candle colors. When price is above desired Candle EMA, price candles will color green. When price is below the Candle EMA, price candles will color fuchsia.
// 2) If you are using another indicator that colors the price candles it may overlap the candle colors applied by this indicator. Trying hiding or removing other indicators to troubleshoot if having candle color issues.
// 3) Using 2-color price moving averages: when price is above an average the average will color green, when price is below an average the average will color fuchsia.
Indicators Combination Framework v3 IND [DTU]Hello All,
This script is a framework to analyze and see the results by combine selected indicators for (long, short, longexit, shortexit) conditions.
I was designed this for beginners and users to facilitate to see effects of the technical indicators combinations on the chart WITH NO CODE
You can improve your strategies according the results of this system by connecting the framework to a strategy framework/template such as Pinecoder, Benson, daveatt or custom.
This is enhanced version of my previous indicator "Indicators & Conditions Test Framework "
Currently there are 93 indicators (23 newly added) connected over library. You can also import an External Indicator or add Custom indicator (In the source)
It is possible to change it from Indicator to strategy (simple one) by just remarking strategy parts in the source code and see real time profit of your combinations
Feel free to change or use it in your source
Special thanks goes to Pine wizards: Trading view (built-in Indicators), @Rodrigo, @midtownsk8rguy, @Lazybear, @Daveatt and others for their open source codes and contributions
SIMPLE USAGE
1. SETTING: Show Alerts= True (To see your entries and Exists)
2. Define your Indicators (ex: INDICATOR1: ema(close,14), INDICATOR2: ema(close,21), INDICATOR3: ema(close,200)
3. Define Your Combinations for long & Short Conditions
a. For Long: (INDICATOR1 crossover INDICATOR2) AND (INDICATOR3 < close)
b. For Short: (INDICATOR1 crossunder INDICATOR2) AND (INDICATOR3 > close)
4. Select Strategy/template (Import strategy to chart) that you export your signals from the list
5. Analyze the best profit by changing Indicators values
SOME INDICATORS DETAILS
Each Indicator includes:
- Factorization : Converting the selected indicator to Double, triple Quadruple such as EMA to DEMA, TEMA QEMA
- Log : Simple or log10 can be used for calculation on function entries
- Plot Type : You can overlay the indicator on the chart (such ema) or you can use stochastic/Percentrank approach to display in the variable hlines range
- Extended Parametes : You can use default parameters or you can use extended (P1,P2) parameters regarding to indicator type and your choice
- Color : You can define indicator color and line properties
- Smooth : you can enable swma smooth
- indicators : you can select one of the 93 function like ema(),rsi().. to define your indicator
- Source : you can select from already defined indicators (IND1-4), External Indicator (EXT), Custom Indicator (CUST), and other sources (close, open...)
CONDITION DETAILS
- There are are 4 type of conditions, long entry, short entry, long exit, short exit.
- Each condition are built up from 4 combinations that joined with "AND" & "OR" operators
- You can see the results by enabling show alerts check box
- If you only wants to enter long entry and long exit, just fill these conditions
- If "close on opposite" checkbox selected on settings, long entry will be closed on short entry and vice versa
COMBINATIONS DETAILS
- There are 4 combinations that joined with "AND" & "OR" operators for each condition
- combinations are built up from compare 1st entry with 2nd one by using operator
- 1st and 2nd entries includes already defined indicators (IND1-5), External Indicator (EXT), Custom Indicator (CUST), and other sources (close, open...)
- Operators are comparison values such as >,<, crossover,...
- 2nd entry include "VALUE" parameter that will use to compare 1st indicator with value area
- If 2nd indicator selected different than "VALUE", value are will mean previous value of the selection. (ex: value area= 2, 2nd entry=close, means close )
- Selecting "NONE" for the 1st entry will disable calculation of current and following combinations
JOINS DETAILS
- Each combination will join wiht the following one with the JOIN (AND, OR) operator (if the following one is not equal "NONE")
CUSTOM INDICATOR
- Custom Indicator defines harcoded in the source code.
- You can call it with "CUST" in the Indicator definition source or combination entries source
- You can change or implement your custom indicator by updating the source code
EXTERNAL INDICATOR
- You can import an external indicator by selecting it from the ext source.
- External Indicator should be already imported to the chart and it have an plot function to output its signal
EXPORTING SIGNAL
- You can export your result to an already defined strategy template such as Pine coders, Benson, Daveatt Strategy templates
- Or you can define your custom export for other future strategy templates
ALERTS
- By enabling show alerts checkbox, you can see long entry exits on the bottom, and short entry exits aon the top of the chart
ADDITIONAL INFO
- You can see all off the inputs descriptions in the tooltips. (You can also see the previous version for details)
- Availability to set start, end dates
- Minimize repainting by using security function options (Secure, Semi Secure, Repaint)
- Availability of use timeframes
-
Version 3 INDICATORS LIST (More to be added):
▼▼▼ OVERLAY INDICATORS ▼▼▼
alma(src,len,offset=0.85,sigma=6).-------Arnaud Legoux Moving Average
ama(src,len,fast=14,slow=100).-----------Adjusted Moving Average
accdist().-------------------------------Accumulation/distribution index.
cma(src,len).----------------------------Corrective Moving average
dema(src,len).---------------------------Double EMA (Same as EMA with 2 factor)
ema(src,len).----------------------------Exponential Moving Average
gmma(src,len).---------------------------Geometric Mean Moving Average
highest(src,len).------------------------Highest value for a given number of bars back.
hl2ma(src,len).--------------------------higest lowest moving average
hma(src,len).----------------------------Hull Moving Average.
lagAdapt(src,len,perclen=5,fperc=50).----Ehlers Adaptive Laguerre filter
lagAdaptV(src,len,perclen=5,fperc=50).---Ehlers Adaptive Laguerre filter variation
laguerre(src,len).-----------------------Ehlers Laguerre filter
lesrcp(src,len).-------------------------lowest exponential esrcpanding moving line
lexp(src,len).---------------------------lowest exponential expanding moving line
linreg(src,len,loffset=1).---------------Linear regression
lowest(src,len).-------------------------Lovest value for a given number of bars back.
mcginley(src, len.-----------------------McGinley Dynamic adjusts for market speed shifts, which sets it apart from other moving averages, in addition to providing clear moving average lines
percntl(src,len).------------------------percentile nearest rank. Calculates percentile using method of Nearest Rank.
percntli(src,len).-----------------------percentile linear interpolation. Calculates percentile using method of linear interpolation between the two nearest ranks.
previous(src,len).-----------------------Previous n (len) value of the source
pivothigh(src,BarsLeft=len,BarsRight=2).-Previous pivot high. src=src, BarsLeft=len, BarsRight=p1=2
pivotlow(src,BarsLeft=len,BarsRight=2).--Previous pivot low. src=src, BarsLeft=len, BarsRight=p1=2
rema(src,len).---------------------------Range EMA (REMA)
rma(src,len).----------------------------Moving average used in RSI. It is the exponentially weighted moving average with alpha = 1 / length.
sar(start=len, inc=0.02, max=0.02).------Parabolic SAR (parabolic stop and reverse) is a method to find potential reversals in the market price direction of traded goods.start=len, inc=p1, max=p2. ex: sar(0.02, 0.02, 0.02)
sma(src,len).----------------------------Smoothed Moving Average
smma(src,len).---------------------------Smoothed Moving Average
super2(src,len).-------------------------Ehlers super smoother, 2 pole
super3(src,len).-------------------------Ehlers super smoother, 3 pole
supertrend(src,len,period=3).------------Supertrend indicator
swma(src,len).---------------------------Sine-Weighted Moving Average
tema(src,len).---------------------------Triple EMA (Same as EMA with 3 factor)
tma(src,len).----------------------------Triangular Moving Average
vida(src,len).---------------------------Variable Index Dynamic Average
vwma(src,len).---------------------------Volume Weigted Moving Average
volstop(src,len,atrfactor=2).------------Volatility Stop is a technical indicator that is used by traders to help place effective stop-losses. atrfactor=p1
wma(src,len).----------------------------Weigted Moving Average
vwap(src_).------------------------------Volume Weighted Average Price (VWAP) is used to measure the average price weighted by volume
▼▼▼ NON OVERLAY INDICATORS ▼▼
adx(dilen=len, adxlen=14, adxtype=0).----adx. The Average Directional Index (ADX) is a used to determine the strength of a trend. len=>dilen, p1=adxlen (default=14), p2=adxtype 0:ADX, 1:+DI, 2:-DI (def:0)
angle(src,len).--------------------------angle of the series (Use its Input as another indicator output)
aroon(len,dir=0).------------------------aroon indicator. Aroons major function is to identify new trends as they happen.p1 = dir: 0=mid (default), 1=upper, 2=lower
atr(src,len).----------------------------average true range. RMA of true range.
awesome(fast=len=5,slow=34,type=0).------Awesome Oscilator is an indicator used to measure market momentum. defaults : fast=len= 5, p1=slow=34, p2=type: 0=Awesome, 1=difference
bbr(src,len,mult=1).---------------------bollinger %%
bbw(src,len,mult=2).---------------------Bollinger Bands Width. The Bollinger Band Width is the difference between the upper and the lower Bollinger Bands divided by the middle band.
cci(src,len).----------------------------commodity channel index
cctbbo(src,len).-------------------------CCT Bollinger Band Oscilator
change(src,len).-------------------------A.K.A. Momentum. Difference between current value and previous, source - source . is most commonly referred to as a rate and measures the acceleration of the price and/or volume of a security
cmf(len=20).-----------------------------Chaikin Money Flow Indicator used to measure Money Flow Volume over a set period of time. Default use is len=20
cmo(src,len).----------------------------Chande Momentum Oscillator. Calculates the difference between the sum of recent gains and the sum of recent losses and then divides the result by the sum of all price movement over the same period.
cog(src,len).----------------------------The cog (center of gravity) is an indicator based on statistics and the Fibonacci golden ratio.
copcurve(src,len).-----------------------Coppock Curve. was originally developed by Edwin Sedge Coppock (Barrons Magazine, October 1962).
correl(src,len).-------------------------Correlation coefficient. Describes the degree to which two series tend to deviate from their ta.sma values.
count(src,len).--------------------------green avg - red avg
cti(src,len).----------------------------Ehler s Correlation Trend Indicator by
dev(src,len).----------------------------ta.dev() Measure of difference between the series and its ta.sma
dpo(len).--------------------------------Detrended Price OScilator is used to remove trend from price.
efi(len).--------------------------------Elders Force Index (EFI) measures the power behind a price movement using price and volume.
eom(len=14,div=10000).-------------------Ease of Movement.It is designed to measure the relationship between price and volume.p1 = div: 10000= (default)
falling(src,len).------------------------ta.falling() Test if the `source` series is now falling for `length` bars long. (Use its Input as another indicator output)
fisher(len).-----------------------------Fisher Transform is a technical indicator that converts price to Gaussian normal distribution and signals when prices move significantly by referencing recent price data
histvol(len).----------------------------Historical volatility is a statistical measure used to analyze the general dispersion of security or market index returns for a specified period of time.
kcr(src,len,mult=2).---------------------Keltner Channels Range
kcw(src,len,mult=2).---------------------ta.kcw(). Keltner Channels Width. The Keltner Channels Width is the difference between the upper and the lower Keltner Channels divided by the middle channel.
klinger(type=len).-----------------------Klinger oscillator aims to identify money flow’s long-term trend. type=len: 0:Oscilator 1:signal
macd(src,len).---------------------------MACD (Moving Average Convergence/Divergence)
mfi(src,len).----------------------------Money Flow Index s a tool used for measuring buying and selling pressure
msi(len=10).-----------------------------Mass Index (def=10) is used to examine the differences between high and low stock prices over a specific period of time
nvi().-----------------------------------Negative Volume Index
obv().-----------------------------------On Balance Volume
pvi().-----------------------------------Positive Volume Index
pvt().-----------------------------------Price Volume Trend
ranges(src,upper=len, lower=-5).---------ranges of the source. src=src, upper=len, v1:lower=upper . returns: -1 source=upper otherwise 0
rising(src,len).-------------------------ta.rising() Test if the `source` series is now rising for `length` bars long. (Use its Input as another indicator output)
roc(src,len).----------------------------Rate of Change
rsi(src,len).----------------------------Relative strength Index
rvi(src,len).----------------------------The Relative Volatility Index (RVI) is calculated much like the RSI, although it uses high and low price standard deviation instead of the RSI’s method of absolute change in price.
smi_osc(src,len,fast=5, slow=34).--------smi Oscillator
smi_sig(src,len,fast=5, slow=34).--------smi Signal
stc(src,len,fast=23,slow=50).------------Schaff Trend Cycle (STC) detects up and down trends long before the MACD. Code imported from
stdev(src,len).--------------------------Standart deviation
trix(src,len) .--------------------------the rate of change of a triple exponentially smoothed moving average.
tsi(src,len).----------------------------The True Strength Index indicator is a momentum oscillator designed to detect, confirm or visualize the strength of a trend.
ultimateOsc(len.-------------------------Ultimate Oscillator indicator (UO) indicator is a technical analysis tool used to measure momentum across three varying timeframes
variance(src,len).-----------------------ta.variance(). Variance is the expectation of the squared deviation of a series from its mean (ta.sma), and it informally measures how far a set of numbers are spread out from their mean.
willprc(src,len).------------------------Williams %R
wad().-----------------------------------Williams Accumulation/Distribution.
wvad().----------------------------------Williams Variable Accumulation/Distribution.
HISTORY
v3.01
ADD: 23 new indicators added to indicators list from the library. Current Total number of Indicators are 93. (to be continued to adding)
ADD: 2 more Parameters (P1,P2) for indicator calculation added. Par:(Use Defaults) uses only indicator(Source, Length) with library's default parameters. Par:(Use Extra Parameters P1,P2) use indicator(Source,Length,p1,p2) with additional parameters if indicator needs.
ADD: log calculation (simple, log10) option added on indicator function entries
ADD: New Output Signals added for compatibility on exporting condition signals to different Strategy templates.
ADD: Alerts Added according to conditions results
UPD: Indicator source inputs now display with indicators descriptions
UPD: Most off the source code rearranged and some functions moved to the new library. Now system work like a little bit frontend/backend
UPD: Performance improvement made on factorization and other source code
UPD: Input GUI rearranged
UPD: Tooltips corrected
REM: Extended indicators removed
UPD: IND1-IND4 added to indicator data source. Now it is possible to create new indicators with the previously defined indicators value. ex: IND1=ema(close,14) and IND2=rsi(IND1,20) means IND2=rsi(ema(close,14),20)
UPD: Custom Indicator (CUST) added to indicator data source and Combination Indicator source.
UPD: Volume added to indicator data source and Combination Indicator source.
REM: Custom indicators removed and only one custom indicator left
REM: Plot Type "Org. Range (-1,1)" removed
UPD: angle, rising, falling type operators moved to indicator library
lib_Indicators_v2_DTULibrary "lib_Indicators_v2_DTU"
This library functions returns included Moving averages, indicators with factorization, functions candles, function heikinashi and more.
Created it to feed as backend of my indicator/strategy "Indicators & Combinations Framework Advanced v2 " that will be released ASAP.
This is replacement of my previous indicator (lib_indicators_DT)
I will add an indicator example which will use this indicator named as "lib_indicators_v2_DTU example" to help the usage of this library
Additionally library will be updated with more indicators in the future
NOTES:
Indicator functions returns only one series :-(
plotcandle function returns candle series
INDICATOR LIST:
hide = 'DONT DISPLAY', //Dont display & calculate the indicator. (For my framework usage)
alma = 'alma(src,len,offset=0.85,sigma=6)', //Arnaud Legoux Moving Average
ama = 'ama(src,len,fast=14,slow=100)', //Adjusted Moving Average
acdst = 'accdist()', //Accumulation/distribution index.
cma = 'cma(src,len)', //Corrective Moving average
dema = 'dema(src,len)', //Double EMA (Same as EMA with 2 factor)
ema = 'ema(src,len)', //Exponential Moving Average
gmma = 'gmma(src,len)', //Geometric Mean Moving Average
hghst = 'highest(src,len)', //Highest value for a given number of bars back.
hl2ma = 'hl2ma(src,len)', //higest lowest moving average
hma = 'hma(src,len)', //Hull Moving Average.
lgAdt = 'lagAdapt(src,len,perclen=5,fperc=50)', //Ehler's Adaptive Laguerre filter
lgAdV = 'lagAdaptV(src,len,perclen=5,fperc=50)', //Ehler's Adaptive Laguerre filter variation
lguer = 'laguerre(src,len)', //Ehler's Laguerre filter
lsrcp = 'lesrcp(src,len)', //lowest exponential esrcpanding moving line
lexp = 'lexp(src,len)', //lowest exponential expanding moving line
linrg = 'linreg(src,len,loffset=1)', //Linear regression
lowst = 'lowest(src,len)', //Lovest value for a given number of bars back.
pcnl = 'percntl(src,len)', //percentile nearest rank. Calculates percentile using method of Nearest Rank.
pcnli = 'percntli(src,len)', //percentile linear interpolation. Calculates percentile using method of linear interpolation between the two nearest ranks.
rema = 'rema(src,len)', //Range EMA (REMA)
rma = 'rma(src,len)', //Moving average used in RSI. It is the exponentially weighted moving average with alpha = 1 / length.
sma = 'sma(src,len)', //Smoothed Moving Average
smma = 'smma(src,len)', //Smoothed Moving Average
supr2 = 'super2(src,len)', //Ehler's super smoother, 2 pole
supr3 = 'super3(src,len)', //Ehler's super smoother, 3 pole
strnd = 'supertrend(src,len,period=3)', //Supertrend indicator
swma = 'swma(src,len)', //Sine-Weighted Moving Average
tema = 'tema(src,len)', //Triple EMA (Same as EMA with 3 factor)
tma = 'tma(src,len)', //Triangular Moving Average
vida = 'vida(src,len)', //Variable Index Dynamic Average
vwma = 'vwma(src,len)', //Volume Weigted Moving Average
wma = 'wma(src,len)', //Weigted Moving Average
angle = 'angle(src,len)', //angle of the series (Use its Input as another indicator output)
atr = 'atr(src,len)', //average true range. RMA of true range.
bbr = 'bbr(src,len,mult=1)', //bollinger %%
bbw = 'bbw(src,len,mult=2)', //Bollinger Bands Width. The Bollinger Band Width is the difference between the upper and the lower Bollinger Bands divided by the middle band.
cci = 'cci(src,len)', //commodity channel index
cctbb = 'cctbbo(src,len)', //CCT Bollinger Band Oscilator
chng = 'change(src,len)', //Difference between current value and previous, source - source .
cmo = 'cmo(src,len)', //Chande Momentum Oscillator. Calculates the difference between the sum of recent gains and the sum of recent losses and then divides the result by the sum of all price movement over the same period.
cog = 'cog(src,len)', //The cog (center of gravity) is an indicator based on statistics and the Fibonacci golden ratio.
cpcrv = 'copcurve(src,len)', //Coppock Curve. was originally developed by Edwin "Sedge" Coppock (Barron's Magazine, October 1962).
corrl = 'correl(src,len)', //Correlation coefficient. Describes the degree to which two series tend to deviate from their ta.sma values.
count = 'count(src,len)', //green avg - red avg
dev = 'dev(src,len)', //ta.dev() Measure of difference between the series and it's ta.sma
fall = 'falling(src,len)', //ta.falling() Test if the `source` series is now falling for `length` bars long. (Use its Input as another indicator output)
kcr = 'kcr(src,len,mult=2)', //Keltner Channels Range
kcw = 'kcw(src,len,mult=2)', //ta.kcw(). Keltner Channels Width. The Keltner Channels Width is the difference between the upper and the lower Keltner Channels divided by the middle channel.
macd = 'macd(src,len)', //macd
mfi = 'mfi(src,len)', //Money Flow Index
nvi = 'nvi()', //Negative Volume Index
obv = 'obv()', //On Balance Volume
pvi = 'pvi()', //Positive Volume Index
pvt = 'pvt()', //Price Volume Trend
rise = 'rising(src,len)', //ta.rising() Test if the `source` series is now rising for `length` bars long. (Use its Input as another indicator output)
roc = 'roc(src,len)', //Rate of Change
rsi = 'rsi(src,len)', //Relative strength Index
smosc = 'smi_osc(src,len,fast=5, slow=34)', //smi Oscillator
smsig = 'smi_sig(src,len,fast=5, slow=34)', //smi Signal
stdev = 'stdev(src,len)', //Standart deviation
trix = 'trix(src,len)' , //the rate of change of a triple exponentially smoothed moving average.
tsi = 'tsi(src,len)', //True Strength Index
vari = 'variance(src,len)', //ta.variance(). Variance is the expectation of the squared deviation of a series from its mean (ta.sma), and it informally measures how far a set of numbers are spread out from their mean.
wilpc = 'willprc(src,len)', //Williams %R
wad = 'wad()', //Williams Accumulation/Distribution.
wvad = 'wvad()' //Williams Variable Accumulation/Distribution.
}
f_func(string, float, simple, float, float, float, simple) f_func Return selected indicator value with different parameters. New version. Use extra parameters for available indicators
Parameters:
string : FuncType_ indicator from the indicator list
float : src_ close, open, high, low,hl2, hlc3, ohlc4 or any
simple : int length_ indicator length
float : p1 extra parameter-1. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p2 extra parameter-2. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p3 extra parameter-3. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
simple : int version_ indicator version for backward compatibility. V1:dont use extra parameters p1,p2,p3 and use default values. V2: use extra parameters for available indicators
Returns: float Return calculated indicator value
fn_heikin(float, float, float, float) fn_heikin Return given src data (open, high,low,close) as heikin ashi candle values
Parameters:
float : o_ open value
float : h_ high value
float : l_ low value
float : c_ close value
Returns: float heikin ashi open, high,low,close vlues that will be used with plotcandle
fn_plotFunction(float, string, simple, bool) fn_plotFunction Return input src data with different plotting options
Parameters:
float : src_ indicator src_data or any other series.....
string : plotingType Ploting type of the function on the screen
simple : int stochlen_ length for plotingType for stochastic and PercentRank options
bool : plotSWMA Use SWMA for smoothing Ploting
Returns: float
fn_funcPlotV2(string, float, simple, float, float, float, simple, string, simple, bool, bool) fn_funcPlotV2 Return selected indicator value with different parameters. New version. Use extra parameters fora available indicators
Parameters:
string : FuncType_ indicator from the indicator list
float : src_data_ close, open, high, low,hl2, hlc3, ohlc4 or any
simple : int length_ indicator length
float : p1 extra parameter-1. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p2 extra parameter-2. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p3 extra parameter-3. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
simple : int version_ indicator version for backward compatibility. V1:dont use extra parameters p1,p2,p3 and use default values. V2: use extra parameters for available indicators
string : plotingType Ploting type of the function on the screen
simple : int stochlen_ length for plotingType for stochastic and PercentRank options
bool : plotSWMA Use SWMA for smoothing Ploting
bool : log_ Use log on function entries
Returns: float Return calculated indicator value
fn_factor(string, float, simple, float, float, float, simple, simple, string, simple, bool, bool) fn_factor Return selected indicator's factorization with given arguments
Parameters:
string : FuncType_ indicator from the indicator list
float : src_data_ close, open, high, low,hl2, hlc3, ohlc4 or any
simple : int length_ indicator length
float : p1 parameter-1. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p2 parameter-2. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p3 parameter-3. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
simple : int version_ indicator version for backward compatibility. V1:dont use extra parameters p1,p2,p3 and use default values. V2: use extra parameters for available indicators
simple : int fact_ Add double triple, Quatr factor to selected indicator (like converting EMA to 2-DEMA, 3-TEMA, 4-QEMA...)
string : plotingType Ploting type of the function on the screen
simple : int stochlen_ length for plotingType for stochastic and PercentRank options
bool : plotSWMA Use SWMA for smoothing Ploting
bool : log_ Use log on function entries
Returns: float Return result of the function
fn_plotCandles(string, simple, float, float, float, simple, string, simple, bool, bool, bool) fn_plotCandles Return selected indicator's candle values with different parameters also heikinashi is available
Parameters:
string : FuncType_ indicator from the indicator list
simple : int length_ indicator length
float : p1 parameter-1. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p2 parameter-2. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
float : p3 parameter-3. active on Version 2 for defining multi arguments indicator input value. ex: lagAdapt(src_, length_,LAPercLen_=p1,FPerc_=p2)
simple : int version_ indicator version for backward compatibility. V1:dont use extra parameters p1,p2,p3 and use default values. V2: use extra parameters for available indicators
string : plotingType Ploting type of the function on the screen
simple : int stochlen_ length for plotingType for stochastic and PercentRank options
bool : plotSWMA Use SWMA for smoothing Ploting
bool : log_ Use log on function entries
bool : plotheikin_ Use Heikin Ashi on Plot
Returns: float
MACD-X, More Than MACD by DGTMoving Average Convergence Divergence – MACD
The most popular indicator used in technical analysis, the moving average convergence divergence (MACD), created by Gerald Appel. MACD is a trend-following momentum indicator, designed to reveal changes in the strength, direction, momentum, and duration of a trend in a financial instrument’s price
Historical evolution of MACD,
- Gerald Appel created the MACD line,
- Thomas Aspray added the histogram feature to MACD
- Giorgos E. Siligardos created a leader of MACD
MACD employs two Moving Averages of varying lengths (which are lagging indicators) to identify trend direction and duration. Then, MACD 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.
Mathematically expressed as;
macd = ma(source, fast_length) – ma(source, slow_length)
signal = ma(macd, signal_length)
histogram = macd – signal
where exponential moving average (ema) is in common use as a moving average (ma)
fast_length = 12
slow_length = 26
signal_length = 9
The MACD indicator is typically good for identifying three types of basic signals ;
Signal Line Crossovers
A Signal Line Crossover is the most common signal produced by the MACD. On the occasions where the MACD Line crosses above or below the Signal Line, that can signify a potentially strong move. The standard interpretation of such an event is a recommendation to buy if the MACD line crosses up through the Signal Line (a "bullish" crossover), or to sell if it crosses down through the Signal Line (a "bearish" crossover). These events are taken as indications that the trend in the financial instrument is about to accelerate in the direction of the crossover.
Zero Line Crossovers
Zero Line Crossovers occur when the MACD Line crossed the Zero Line and either becomes positive (above 0) or negative (below 0). A change from positive to negative MACD is interpreted as "bearish", and from negative to positive as "bullish". Zero crossovers provide evidence of a change in the direction of a trend but less confirmation of its momentum than a signal line crossover
Divergence
Divergence is another signal created by the MACD. Simply, divergence occurs when the MACD and actual price are not in agreement. A "positive divergence" or "bullish divergence" occurs when the price makes a new low but the MACD does not confirm with a new low of its own. A "negative divergence" or "bearish divergence" occurs when the price makes a new high but the MACD does not confirm with a new high of its own. A divergence with respect to price may occur on the MACD line and/or the MACD Histogram
Moving Average Crossovers , another hidden signal that MACD Indicator identifies
Many traders will watch for a short-term moving average to cross above a longer-term moving average and use this to signal increasing upward momentum. This bullish crossover suggests that the price has recently been rising at a faster rate than it has in the past, so it is a common technical buy sign. Conversely, a short-term moving average crossing below a longer-term average is used to illustrate that the asset's price has been moving downward at a faster rate and that it may be a good time to sell.
Moving Average Crossovers in reality is Zero Line Crossovers, the value of the MACD indicator is equal to zero each time the two moving averages cross over each other. For easy interpretation by trades, Zero Line Crossovers are simply described as positive or negative MACD
False signals
Like any forecasting algorithm, the MACD can generate false signals. A false positive, for example, would be a bullish crossover followed by a sudden decline in a financial instrument. A false negative would be a situation where there is bearish crossover, yet the financial instrument accelerated suddenly upwards
What is “MACD-X” and Why it is “More Than MACD”
In its simples form, MACD-X implements variety of different calculation techniques applied to obtain MACD Line, ability to use of variety of different sources , including Volume related sources, and can be plotted along with MACD in the same window and all those features are available and presented within a single indicator, MACD-X
Different calculation techniques lead to different values for MACD Line, as will further discuss below, and as a consequence the signal line and the histogram values will differentiate accordingly. Mathematical calculation of both signal line and the histogram remain the same.
Main features of MACD-X ;
1- Introduces different proven techniques applied on MACD calculation , such as MACD-Histogram, MACD-Leader and MACD-Source, besides the traditional MACD (MACD-TRADITIONAL)
• MACD-Traditional , by Gerald Appel
It is the MACD that we know, stated as traditional just to avoid confusion with other techniques used with this study
• MACD-Histogram , by Thomas Aspray
The MACD-Histogram measures the distance between MACD and its signal line (the 9-day EMA of MACD). Aspray developed the MACD-Histogram to anticipate signal line crossovers in MACD. Because MACD uses moving averages and moving averages lag price, signal line crossovers can come late and affect the reward-to-risk ratio of a trade. Bullish or bearish divergences in the MACD-Histogram can alert chartists to an imminent signal line crossover in MACD
The MACD-Histogram represents the difference between MACD and its 9-day EMA, the signal line. Mathematically,
macdx = macd - ma(macd, signal_length)
Aspray's contribution served as a way to anticipate (and therefore cut down on lag) possible MACD crossovers which are a fundamental part of the indicator.
Here come a question, what if repeat the same calculations once more (macdh2 = macdh - ma(macdh, signal_length), will it be even better, this question will remain to be tested
• MACD-Leader , by Giorgos E. Siligardos, PhD
MACD Leader has the ability to lead MACD at critical situations. Almost all smoothing methods encounter in technical analysis are based on a relative-weighted sum of past prices, and the Leader is no exception. The concealed weights of MACD Leader are such that more relative weight is used in the more recent prices than the respective weights used by the components of MACD. In effect, the Leader expresses more changes in average price dynamics for the recent price movement than MACD, thus eventually leading MACD, especially when significant trend changes are about to take place.
Siligardos creates two less-laggard moving averages indicators in its formula using the same periods as follows
Indicator1 = ma(source, fast_length) + ma(source - ma(source, fast_length), fast_length)
Indicator2 = ma(source, slow_length) + ma(source - ma(source, slow_length), slow_length)
and then take the difference:
Indicator1 - Indicator2
The result is a new MACD Leader indicator
macdx = macd + ma(source - fast_ma, fast_length) - ma(source - slow_ma, slow_length)
• MACD-Source , a custom experimental interpretation of mine ,
MACD Source, presents an application of MACD that evaluates Source/MA Ratio, relatively with less lag, as a basis for MACD Line, also can be expressed as source convergence/divergence to its moving average. Among the various techniques for removing the lag between price and moving average (MA) of the price, one in particular stands out: the addition to the moving average of a portion of the difference between the price and MA. MACD Source, is based on signal length mean of the difference between Source and average value of shot length and long length moving average of the source (Source/MA Ratio), where the source is actual value and hence no lag and relatively less lag with the average value of moving average of the source . Mathematically expressed as,
macdx = ma(source - avg( ma(source, fast_length), ma(source, slow_length) ), signal_length)
MACD Source provides relatively early crossovers comparing to MACD and better momentum direction indications, assuming the lengths are set to same values
For further details, you are invited to check the following two studies, where the first seeds were sown of the MACD-Source idea
Price Distance to its Moving Averages study, adapts the idea of “Prices high above the moving average (MA) or low below it are likely to be remedied in the future by a reverse price movement", presented in an article by Denis Alajbeg, Zoran Bubas and Dina Vasic published in International Journal of Economics, Commerce and Management
First MACD like interpretation comes with the second study named as “ P-MACD ”, where P stands for price, P-MACD study attempts to display relationship between Price and its 20 and 200-period moving average. Calculations with P-MACD were based on price distance (convergence/divergence) to its 200-period moving average, and moving average convergence/divergence of 20-period moving average to 200-period moving average of price.
Now as explained above, MACD Source is a one adapted with traditional MACD, where Source stands for Price, Volume Indicator etc, any source applicable with MACD concept
2- Allows usage of variety of different sources, including Volume related indicators
The most common usage of Source for MACD calculation is close value of the financial instruments price. As an experimental approach, this study will allow source to be selected as one of the following series;
• Current Close Price (close)
• Average of High, Low, and Close Price (hlc3)
• On Balance Volume (obv)
• Accumulation Distribution (accdist)
• Price Volume Trend (pvt)
Where,
-Current Close Price and Average of High, Low, and Close Price are price actions of the financial instrument
- Accumulation Distribution is a volume based indicator designed to measure underlying supply and demand
- On Balance Volume (OBV) , is a momentum indicator that measures positive and negative volume flow
- Price Volume Trend (PVT) is a momentum based indicator used to measure money flow
3- Can be plotted along with MACD in the same window using the same scaling
Default setting of MACD-X will display MACD-Source with Current Close Price as a source and traditional MACD can be plotted eighter as a companion of MACD-X or can be selected to be plotted alone.
Applying both will add ability to compare, or use as a confirmation of one other
In case, traditional MACD Is plotted along with MACD-X to avoid misinterpreting, the lines plotted, the area between MACD-X Line and Signal-X Line is highlighted automatically, even if the highlight option not selected. Otherwise highlight will be applied only if that option selected
4- 4C Histogram
Histogram is plotted with four colors to emphasize the momentum and direction
5- Customizable
Additional to ability of selecting Calculation Method, Source, plotting along with MACD, there are few other option that allows users to customize the MACD-X indicator
Lengths are configurable, default values are set as 12, 26, 9 respectively for fast, slow and smoothing length. Setting lengths to 8,21,5 respectively Is worth checking, slower length moving averages will lead to less lag and earlier reaction to price actions but yet requires a caution and back testing before applying
Highlight the area between MACD-X Line and Signal-X Line, with colors emphasising the direction
Label can be added to display Calculation Method, Source and Length settings, the aim of this label is to server only as a reminder to trades to be aware of settings while they are occupied with charts, analysis etc.
Here comes another question, which is of more importance having the reminder or having the indicators with multi timeframe feature? Build-in Multi Time Frame features of Pine is not supported when labels and lines introduced in the script, there are other methods but brings complexity. To be studied further, this version will be with labels for time being.
Epilogue
MACD-X is an alternative variant of MACD, the insight/signals provided by MACD are also applicable to MACD-X with early and clear warnings for the changes in the trend.
If MACD is essential to your analysis, then it is my guess that after using the MACD-X for a while and familiarizing yourself with its unique character and personality, you will make it an inseparable companion to other indicators in your charts.
The various signals generated by MACD/MACD-X are easily interpreted and very few indicators in technical analysis have proved to be more reliable than the MACD, and this relatively simple indicator can quickly be incorporated into any short-term trading strategy
Disclaimer : Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
The script is for informational and educational purposes only. Use of the script does not constitutes professional and/or financial advice. You alone the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
Forward Backward EMA [Repaint]Perform forward-backward filtering using exponential averaging, thus providing a zero-phase exponential moving average. The output repaint and cannot be used as input for other indicators.
Settings
Length : moving average period
Src : data input of the moving average
Plot Color : the color of the displayed plot
Line Width : width of the plotted line
Usages
The main usage of moving averages is to provide an estimate of the underlying trend in the price by removing higher term variations from it. Non-causal (repainting) indicators are limited to offline applications, as such, they are most useful for summary analyses, note that it is still possible to infer from the output of repainting indicators, however since past outputs are subject to changes, it is extremely difficult to track the effectiveness of such indicators, and in online applications they only track the price, making them equally useful for predictive applications than following the direction of an individual candle.
Non-causal filters can be useful in order to have a better view of symbols with a relatively uninformative evolution.
Details
Causal filters have lag, this is the cost of using past observations as inputs, the more past observations you use, the more lag you will obtain (assuming these past observations have non-zero weights). There are various solutions to reduce the lag of a moving average, the most simple one relying on giving higher weights to more recent observations, another one relies on introducing gain in the filter passband, that is amplifying certain variations in the input signal while attenuating/removing higher term ones, finally, we can use adaptive moving averages to avoid excessive lag.
All these previous solutions can be used causally, but they are far from being perfect, as the lag reduction is often done at the cost of smoothness, if we were to keep the original smoothness of the filter while having no lag we would need to use non-causal solutions. The most common solution is to directly use future values as inputs, such moving averages are called "two-sided" moving averages since they use past values as input (left side) as well as future input values (right side), this is equivalent to shifting the results of a moving average backward.
The advantages of two-sided moving averages is that they conserve the original amplitude response of the moving average, however, it won't be possible to compute the most recent values of the moving average (since we won't have access to future values at a certain point), an alternative method heavily used in digital signal processing is forward-backward filtering.
The method consists of applying a filter forward in time, then we apply it once again backward. In order for you to have an easier understanding of this process think about applying a moving average normally starting at time t = 0 , then apply that moving average once again using the previous results as input but start from t = N-1 , that is from the most recent point, and proceed backward, plotting the result from left to right until you get back to t = 0 .
From this, it follows that forward-backward filtering applies a filter twice, the resulting filter is thus a two-passes filter, this results in an even smoother output (more precisely the filter amplitude response is squared).
Forward-backward filtering can be done in Pinescript by using the function "line.new" inside a loop, an exponential moving average is applied forward first, then once again backward inside the loop, "line.new" is used to plot the results backward.
Notes
It is important to note that forward-backward filtering is a repainting process, all the results of the indicator you see on the chart are subject to change over time. Since the method make use of line.new you will have around only 54 visible observations, with the impossibility of using them as input for other indicators. If you see indicators in the future with the same characteristics be aware that they will repaint.
Never purchase/rent filters that appear as having no lag, they are either repainting or the results are coming from a lucky shot or from an overfitted model, it is impossible to make both zero-lag and causal moving averages with pinescript, if you have doubt don't test your luck, better safe than sorry.
Moving Average Compendium===========
Moving Average Compendium (16 MA Types)
===========
A selection of the most popular, widely used, interesting and most powerful Moving Averages we can think of. We've compiled 16 MA's into this script, and allowed full access to the source code so you can use what you need, as you need it.
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From very simple moving averages using built-in functions, all the way through to Fractal Adaptive Averages, we've tried to cover as much as we can think of! BUT, if you would like to make a suggestion or recommendation to be added to this compendium of MA's please let us know! Together we can get a complete list of many dozens of types of Moving Average.
Full List (so far)
---
SMA - Simple Moving Average
EMA - Exponential Moving Average
WMA - Weighted Moving Average
VWMA - Volume Weighted Moving Average
DEMA - Double Exponential Moving Average
TEMA - Triple Exponential Moving Average
SMMA - Smoothed Moving Average
HMA - Hull Moving Average
ZLEMA - Zero-Lag Exponential Moving Average
KAMA - Kaufman Adaptive Moving Average
JMA - Jurik Moving Average
SWMA - Sine-Weighted Moving Average
TriMA - Triangular Moving Average
MedMA - Moving Median Average
GeoMA - Geometric Mean Moving Average
FRAMA - Fractal Adaptive Moving Average
Line color changes from green (upward) to red (downward) - some of the MA types will "linger" without moving up or down and when they are in this state they should appear gray in color.
Thanks to all involved -
Good Luck and Happy Trading!
Moving Averages Linear CombinatorLinearly combining moving averages can provide relatively interesting results such as a low-lagging moving averages or moving averages able to produce more pertinent crosses with the price.
As a remainder, a linear combination is a mathematical expression that is based on the multiplication of two variables (or terms) with two coefficients (also called scalars when working with vectors) and adding the results, that is:
ax + by
This expression is a linear combination , with x/y as variables and a/b as coefficients. Lot of indicators are made from linear combinations of moving averages, some examples include the double/triple exponential moving average, least squares moving average and the hull moving average.
Today proposed indicator allow the user to combine many types of moving averages together in order to get different results, we will introduce each settings of the indicator as well as how they affect the final output.
Explaining The Effects Of Linear Combinations
There are various ways to explain why linear combination can produce low-lagging moving averages, lets take for example the linear combination of a fast SMA of period p/2 and slow simple moving average of period p , the linear combination of these two moving averages is described as follows:
MA = 2SMA(p/2) + -1SMA(p)
Which is equivalent to:
MA = 2SMA(p/2) - SMA(p) = SMA(p/2) + SMA(p/2) - SMA(p)
We can see the above linear combinations consist in adding a bandpass filter to the fast moving average, which of course allow to reduce the lag. It is important to note that lag is reduced when the first moving average term is more reactive than the second moving average term. In case we instead use:
MA = -2SMA(p/2) + 1SMA(p)
we would have a combination between a low-pass and band-reject filter.
The Indicator
The indicator is based on the following linear combination:
Coeff × LeadingMA(length) - (Coeff-1) × LaggingMA(length)
The length setting control both moving averages period, leading control the type of moving average used as leading MA, while lagging control the type of MA used as lagging moving average, in order to get low lag results the leading MA should be more reactive than the lagging MA. Coeff control the coefficients of the linear combination, with higher values of coeff amplifying the effects of the linear combination, negative values of coeff would make a low-lag moving average become a lagging moving average, coeff = 1 return the leading MA, coeff = -1 return the lagging MA. The leading period divisor allow to divide the period of the leading MA by the selected number.
The types of moving average available are: simple, exponentially weighted, triangular, least squares, hull and volume weighted. The lagging MA allow you to select another MA on the chart as input.
length = 100, leading period divisor = 2, coeff = 2, with both MA type = SMA. Using coeff = -2 instead would give:
You can select "Plot leading and lagging" in order to show the leading and lagging MA.
Conclusion
The proposed tool allow the user to create a custom moving averages by making use of linear combination. The script is not that useful when you think about it, and might maybe be one of my worst, as it is relatively impractical, not proud of it, but it still took time to make so i decided to post it anyway.
HEMA - A Fast And Efficient Estimate Of The Hull Moving AverageIntroduction
The Hull moving average (HMA) developed by Alan Hull is one of the many moving averages that aim to reduce lag while providing effective smoothing. The HMA make use of 3 linearly weighted (WMA) moving averages, with respective periods p/2 , p and √p , this involve three convolutions, which affect computation time, a more efficient version exist under the name of exponential Hull moving average (EHMA), this version make use of exponential moving averages instead of linearly weighted ones, which dramatically decrease the computation time, however the difference with the original version is clearly noticeable.
In this post an efficient and simple estimate is proposed, the estimation process will be fully described and some comparison with the original HMA will be presented.
This post and indicator is dedicated to LucF
Estimation Process
Estimating a moving average is easier when we look at its weights (represented by the impulse response), we basically want to find a similar set of weights via more efficient calculations, the estimation process is therefore based on fully understanding the weighting architecture of the moving average we want to estimate.
The impulse response of an HMA of period 20 is as follows :
We can see that the first weights increases a bit before decaying, the weights then decay, cross under 0 and increase again. More recent closing price values benefits of the highest weights, while the oldest values have negatives ones, negative weighting is what allow to drastically reduce the lag of the HMA. Based on this information we know that our estimate will be a linear combination of two moving averages with unknown coefficients :
a × MA1 + b × MA2
With a > 0 and b < 0 , the lag of MA1 is lower than the lag of MA2 . We first need to capture the general envelope of the weights, which has an overall non-linearly decaying shape, therefore the use of an exponential moving average might seem appropriate.
In orange the impulse response of an exponential moving average of period p/2 , that is 10. We can see that such impulse response is not a bad estimate of the overall shape of the HMA impulse response, based on this information we might perform our linear combination with a simple moving average :
2EMA(p/2) + -1SMA(p)
this gives the following impulse response :
As we can see there is a clear lack of accuracy, but because the impulse response of a simple moving is a constant we can't have the short increasing weights of the HMA, we therefore need a non-constant impulse response for our linear combination, a WMA might be appropriate. Therefore we will use :
2WMA(p/2) + -1EMA(p/2)
Note that the lag a WMA is inferior to the lag of an EMA of same period, this is why the period of the WMA is p/2 . We obtain :
The shape has improved, but the fit is poor, which mean we should change our coefficients, more precisely increasing the coefficient of the WMA (thus decreasing the one of the EMA). We will try :
3WMA(p/2) + -2EMA(p/2)
We then obtain :
This estimate seems to have a decent fit, and this linear combination is therefore used.
Comparison
HMA in blue and the estimate in fuchsia with both period 50, the difference can be noted, however the estimate is relatively accurate.
In the image above the period has been set to 200.
Conclusion
In this post an efficient estimate of the HMA has been proposed, we have seen that the HMA can be estimated via the linear combinations of a WMA and an EMA of each period p/2 , this isn't important for the EMA who is based on recursion but is however a big deal for the WMA who use recursion, and therefore p indicate the number of data points to be used in the convolution, knowing that we use only convolution and that this convolution use twice less data points then one of the WMA used in the HMA is a pretty great thing.
Subtle tweaking of the coefficients/moving averages length's might help have an even more accurate estimate, the fact that the WMA make use of a period of √p is certainly the most disturbing aspect when it comes to estimating the HMA. I also described more in depth the process of estimating a moving average.
I hope you learned something in this post, it took me quite a lot of time to prepare, maybe 2 hours, some pinescripters pass an enormous amount of time providing content and helping the community, one of them being LucF, without him i don't think you'll be seeing this indicator as well as many ones i previously posted, I encourage you to thank him and check his work for Pinecoders as well as following him.
Thanks for reading !
Volume Footprint Anomaly Scanner [PhenLabs]📊 PhenLabs - Volume Footprint Anomaly Scanner (VFAS)
Version: PineScript™ v6
📌 Description
The PhenLabs Volume Footprint Anomaly Scanner (VFAS) is an advanced Pine Script indicator designed to detect and highlight significant imbalances in buying and selling pressure within individual price bars. By analyzing a calculated "Delta" – the net difference between estimated buy and sell volume – and employing statistical Z-score analysis, VFAS pinpoints moments when buying or selling activity becomes unusually dominant. This script was created not in hopes of creating a "Buy and Sell" indicator but rather providing the user with a more in-depth insight into the intrabar volume delta and how it can fluctuate in unusual ways, leading to anomalies that can be capitalized on.
This indicator helps traders identify high-conviction points where strong market participants are active, signaling potential shifts in momentum or continuation of a trend. It aims to provide a clearer understanding of underlying market dynamics, allowing for more informed decision-making in various trading strategies, from identifying entry points to confirming trend strength.
🚀 Points of Innovation
● Z-Score for Delta Analysis : Utilizes statistical Z-scores to objectively identify statistically significant anomalies in buying/selling pressure, moving beyond simple, arbitrary thresholds.
● Dynamic Confidence Scoring : Assigns a multi-star confidence rating (1-4 stars) to each signal, factoring in high volume, trend alignment, and specific confirmation criteria, providing a nuanced view of signal strength.
● Integrated Trend Filtering : Offers an optional Exponential Moving Average (EMA)-based trend filter to ensure signals align with the broader market direction, reducing false positives in ranging markets.
● Strict Confirmation Logic : Implements specific confirmation criteria for higher-confidence signals, including price action and a time-based gap from previous signals, enhancing reliability.
● Intuitive Info Dashboard : Provides a real-time summary of market trend and the latest signal's direction and confidence directly on the chart, streamlining information access.
🔧 Core Components
● Core Delta Engine : Estimates the net buying/selling pressure (bar Delta) by analyzing price movement within each bar relative to volume. It also calculates average volume to identify bars with unusually high activity.
● Anomaly Detection (Z-Score) : Computes the Z-score for the current bar's Delta, indicating how many standard deviations it is from its recent average. This statistical measure is central to identifying significant anomalies.
● Trend Filter : Utilizes a dual Exponential Moving Average (EMA) cross-over system to define the prevailing market trend (uptrend, downtrend, or range), providing contextual awareness.
● Signal Processing & Confidence Algorithm : Evaluates anomaly conditions against trend filters and confirmation rules, then calculates a dynamic confidence score to produce actionable, contextualized signal information.
🔥 Key Features
● Advanced Delta Anomaly Detection : Pinpoints bars with exceptionally high buying or selling pressure, indicating potential institutional activity or strong market conviction.
● Multi-Factor Confidence Scoring : Each signal comes with a 1-4 star rating, clearly communicating its reliability based on high volume, trend alignment, and specific confirmation criteria.
● Optional Trend Alignment : Users can choose to filter signals, so only those aligned with the prevailing EMA-defined trend are displayed, enhancing signal quality.
● Interactive Signal Labels : Displays compact labels on the chart at anomaly points, offering detailed tooltips upon hover, including signal type, direction, confidence, and contextual information.
● Customizable Bar Colors : Visually highlights bars with Delta anomalies, providing an immediate visual cue for strong buying or selling activity.
● Real-time Info Dashboard : A clean, customizable dashboard shows the current market trend and details of the latest detected signal, keeping key information accessible at a glance.
● Configurable Alerts : Set up alerts for bullish or bearish Delta anomalies to receive real-time notifications when significant market pressure shifts occur.
🎨 Visualization
Signal Labels :
* Placed at the top/bottom of anomaly bars, showing a "📈" (bullish) or "📉" (bearish) icon.
* Tooltip: Hovering over a label reveals detailed information: Signal Type (e.g., "Delta Anomaly"), Direction, Confidence (e.g., "★★★☆"), and a descriptive explanation of the anomaly.
* Interpretation: Clearly marks actionable signals and provides deep insights without cluttering the chart, enabling quick assessment of signal strength and context.
● Info Dashboard :
* Located at the top-right of the chart, providing a clean summary.
* Displays: "PhenLabs - VFAS" header, "Market Trend" (Uptrend/Downtrend/Range with color-coded status), and "Direction | Conf." (showing the last signal's direction and star confidence).
* Optional "💡 Hover over signals for details" reminder.
* Interpretation: A concise, real-time summary of the market's pulse and the most recent high-conviction event, helping traders stay informed at a glance.
📖 Usage Guidelines
Setting Categories
⚙️ Core Delta & Volume Engine
● Minimum Volume Lookback (Bars)
○ Default: 9
○ Range: Integer (e.g., 5-50)
○ Description: Defines the number of preceding bars used to calculate the average volume and delta. Bars with volume below this average won't be considered for high-volume signals. A shorter lookback is more reactive to recent changes, while a longer one provides a smoother average.
📈 Anomaly Detection Settings
Delta Z-Score Anomaly Threshold
○ Default: 2.5
○ Range: Float (e.g., 1.0-5.0+)
○ Description: The number of standard deviations from the mean that a bar's delta must exceed to be considered a significant anomaly. A higher threshold means fewer, but potentially stronger, signals. A lower threshold will generate more signals, which might include less significant events. Experiment to find the optimal balance for your trading style.
🔬 Context Filters
Enable Trend Filter
○ Default: False
○ Range: Boolean (True/False)
○ Description: When enabled, signals will only be generated if they align with the current market trend as determined by the EMAs (e.g., only bullish signals in an uptrend, bearish in a downtrend). This helps to filter out counter-trend noise.
● Trend EMA Fast
○ Default: 50
○ Range: Integer (e.g., 10-100)
○ Description: The period for the faster Exponential Moving Average used in the trend filter. In combination with the slow EMA, it defines the trend direction.
● Trend EMA Slow
○ Default: 200
○ Range: Integer (e.g., 100-400)
○ Description: The period for the slower Exponential Moving Average used in the trend filter. The relationship between the fast and slow EMA determines if the market is in an uptrend (fast > slow) or downtrend (fast < slow).
🎨 Visual & UI Settings
● Show Info Dashboard
○ Default: True
○ Range: Boolean (True/False)
○ Description: Toggles the visibility of the dashboard on the chart, which provides a summary of market trend and the last detected signal.
● Show Dashboard Tooltip
○ Default: True
○ Range: Boolean (True/False)
○ Description: Toggles a reminder message in the dashboard to hover over signal labels for more detailed information.
● Show Delta Anomaly Bar Colors
○ Default: True
○ Range: Boolean (True/False)
○ Description: Enables or disables the coloring of bars based on their delta direction and whether they represent a significant anomaly.
● Show Signal Labels
○ Default: True
○ Range: Boolean (True/False)
○ Description: Controls the visibility of the “📈” or “📉” labels that appear on the chart when a delta anomaly signal is generated.
🔔 Alert Settings
Alert on Delta Anomaly
○ Default: True
○ Range: Boolean (True/False)
○ Description: When enabled, this setting allows you to set up alerts in TradingView that will trigger whenever a new bullish or bearish delta anomaly is detected.
✅ Best Use Cases
Early Trend Reversal / Continuation Detection: Identify strong surges of buying/selling pressure at key support/resistance levels that could indicate a reversal or the continuation of a strong move.
● Confirmation of Breakouts: Use high-confidence delta anomalies to confirm the validity of price breakouts, indicating strong conviction behind the move.
● Entry and Exit Points: Pinpoint precise entry opportunities when anomalies align with your trading strategy, or identify potential exhaustion signals for exiting trades.
● Scalping and Day Trading: The indicator’s sensitivity to intraday buying/selling imbalances makes it highly effective for short-term trading strategies.
● Market Sentiment Analysis: Gain a real-time understanding of underlying market sentiment by observing the prevalence and strength of bullish vs. bearish anomalies.
⚠️ Limitations
Estimated Delta: The script uses a simplified method to estimate delta based on bar close relative to its range, not actual order book or footprint data. While effective, it’s an approximation.
● Sensitivity to Z-Score Threshold: The effectiveness heavily relies on the `Delta Z-Score Anomaly Threshold`. Too low, and you’ll get many false positives; too high, and you might miss valid signals.
● Confirmation Criteria: The 4-star confidence level’s “confirmation” relies on specific subsequent bar conditions and previous confirmed signals, which might be too strict or specific for all contexts.
● Requires Context: While powerful, VFAS is best used in conjunction with other technical analysis tools and price action to form a comprehensive trading strategy. It is not a standalone “buy/sell” signal.
💡 What Makes This Unique
Statistical Rigor: The application of Z-score analysis to bar delta provides an objective, statistically-driven way to identify true anomalies, moving beyond arbitrary thresholds.
● Multi-Factor Confidence Scoring: The unique 1-4 star confidence system integrates multiple market dynamics (volume, trend alignment, specific follow-through) into a single, easy-to-interpret rating.
● User-Friendly Design: From the intuitive dashboard to the detailed signal tooltips, the indicator prioritizes clear and accessible information for traders of all experience levels.
🔬 How It Works
1. Bar Delta Calculation:
● The script first estimates the “buy volume” and “sell volume” for each bar. This is done by assuming that volume proportional to the distance from the low to the close represents buying, and volume proportional to the distance from the high to the close represents selling.
● How this contributes: This provides a proxy for the net buying or selling pressure (delta) within that specific price bar, even without access to actual footprint data.
2. Volume & Delta Z-Score Analysis:
● The average volume over a user-defined lookback period is calculated. Bars with volume less than twice this average are generally considered of lower interest.
● The Z-score for the calculated bar delta is computed. The Z-score measures how many standard deviations the current bar’s delta is from its average delta over the `Minimum Volume Lookback` period.
● How this contributes: A high positive Z-score indicates a bullish delta anomaly (significantly more buying than usual), while a high negative Z-score indicates a bearish delta anomaly (significantly more selling than usual). This identifies statistically unusual levels of pressure.
3. Trend Filtering (Optional):
● Two Exponential Moving Averages (Fast and Slow EMA) are used to determine the prevailing market trend. An uptrend is identified when the Fast EMA is above the Slow EMA, and a downtrend when the Fast EMA is below the Slow EMA.
● How this contributes: If enabled, the indicator will only display bullish delta anomalies during an uptrend and bearish delta anomalies during a downtrend, helping to confirm signals within the broader market context and avoid counter-trend signals.
4. Signal Generation & Confidence Scoring:
● When a delta Z-score exceeds the user-defined anomaly threshold, a signal is generated.
● This signal is then passed through a multi-factor confidence algorithm (`f_calculateConfidence`). It awards stars based on: high volume presence, alignment with the overall trend (if enabled), and a fourth star for very strong Z-scores (above 3.0) combined with specific follow-through candle patterns after a cooling-off period from a previous confirmed signal.
● How this contributes: Provides a qualitative rating (1-4 stars) for each anomaly, allowing traders to quickly assess the potential significance and reliability of the signal.
💡 Note:
The PhenLabs Volume Footprint Anomaly Scanner is a powerful analytical tool, but it’s crucial to understand that no indicator guarantees profit. Always backtest and forward-test the indicator settings on your chosen assets and timeframes. Consider integrating VFAS with your existing trading strategy, using its signals as confirmation for entries, exits, or trend bias. The Z-score threshold is highly customizable; lower values will yield more signals (including potential noise), while higher values will provide fewer but potentially higher-conviction signals. Adjust this parameter based on market volatility and your risk tolerance. Remember to combine statistical insights from VFAS with price action, support/resistance levels, and your overall market outlook for optimal results.
Vix_Fix Enhanced MTF [Cometreon]The VIX Fix Enhanced is designed to detect market bottoms and spikes in volatility, helping traders anticipate major reversals with precision. Unlike standard VIX Fix tools, this version allows you to control the standard deviation logic, switch between chart styles, customize visual outputs, and set up advanced alerts — all with no repainting.
🧠 Logic and Calculation
This indicator is based on Larry Williams' VIX Fix and integrates features derived from community requests/advice, such as inverse VIX logic.
It calculates volatility spikes using a customizable standard deviation of the lows and compares it to a moving high to identify potential reversal points.
All moving average logic is based on Cometreon's proprietary library, ensuring accurate and optimized calculations on all 15 moving average types.
🔷 New Features and Improvements
🟩 Custom Visual Styles
Choose how you want your VIX data displayed:
Line
Step Line
Histogram
Area
Column
You can also flip the orientation (bottom-up or top-down), change the source ticker, and tailor the display to match your charting preferences.
🟩 Multi-MA Standard Deviation Calculation
Customize the standard deviation formula by selecting from 15 different moving averages:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
RMA (Smoothed Moving Average)
HMA (Hull Moving Average)
JMA (Jurik Moving Average)
DEMA (Double Exponential Moving Average)
TEMA (Triple Exponential Moving Average)
LSMA (Least Squares Moving Average)
VWMA (Volume-Weighted Moving Average)
SMMA (Smoothed Moving Average)
KAMA (Kaufman’s Adaptive Moving Average)
ALMA (Arnaud Legoux Moving Average)
FRAMA (Fractal Adaptive Moving Average)
VIDYA (Variable Index Dynamic Average)
This gives you fine control over how volatility is measured and allows tuning the sensitivity for different market conditions.
🟩 Full Control Over Percentile and Deviation Conditions
You can enable or disable lines for standard deviation and percentile conditions, and define whether you want to trigger on over or under levels — adapting the indicator to your exact logic and style.
🟩 Chart Type Selection
You're no longer limited to candlestick charts! Now you can use Vix_Fix with different chart formats, including:
Candlestick
Heikin Ashi
Renko
Kagi
Line Break
Point & Figure
🟩 Multi-Timeframe Compatibility Without Repainting
Use a different timeframe from your chart with confidence. Signals remain stable and do not repaint. Perfect for spotting long-term reversal setups on lower timeframes.
🟩 Alert System Ready
Configure alerts directly from the indicator’s panel when conditions for over/under signals are met. Stay informed without needing to monitor the chart constantly.
🔷 Technical Details and Customizable Inputs
This indicator includes full control over the logic and appearance:
1️⃣ Length Deviation High - Adjusts the lookback period used to calculate the high deviation level of the VIX logic. Shorter values make it more reactive; longer values smooth out the signal.
2️⃣ Ticker - Choose a different chart type for the calculation, including Heikin Ashi, Renko, Kagi, Line Break, and Point & Figure.
3️⃣ Style VIX - Change the visual style (Line, Histogram, Column, etc.), adjust line width, and optionally invert the display (bottom-to-top).
📌 Fill zones for deviation and percentile are active only in Line and Step Line modes
4️⃣ Use Standard Deviation Up / Down - Enable the overbought and oversold zone logic based on upper and lower standard deviation bands.
5️⃣ Different Type MA (for StdDev) - Choose from 15 different moving averages to define the calculation method for standard deviation (SMA, EMA, HMA, JMA, etc.), with dedicated parameters like Phase, Sigma, and Offset for optimized responsiveness.
6️⃣ BB Length & Multiplier - Adjust the period and multiplier for the standard deviation bands, similar to how Bollinger Bands work.
7️⃣ Show StdDev Up / Down Line - Enable or disable the visibility of upper and lower standard deviation boundaries.
8️⃣ Use Percentile & Length High - Activate the percentile-based logic to detect extreme values in historical volatility using a customizable lookback length.
9️⃣ Highest % / Lowest % - Set the high and low percentile thresholds (e.g., 85 for high, 99 for low) that will be used to trigger over/under signals.
🔟 Show High / Low Percentile Line - Toggle the visual display of the percentile boundaries directly on the chart for clearer signal reference.
1️⃣1️⃣ Ticker Settings – Customize parameters for special chart types such as Renko, Heikin Ashi, Kagi, Line Break, and Point & Figure, adjusting reversal, number of lines, ATR length, etc.
1️⃣2️⃣ Timeframe – Enables using SuperTrend on a higher timeframe.
1️⃣3️⃣ Wait for Timeframe Closes -
✅ Enabled – Displays Vix_Fix smoothly with interruptions.
❌ Disabled – Displays Vix_Fix smoothly without interruptions.
☄️ If you find this indicator useful, leave a Boost to support its development!
Every feedback helps to continuously improve the tool, offering an even more effective trading experience. Share your thoughts in the comments! 🚀🔥
[blackcat] L2 BullBear OscillatorOVERVIEW
The " L2 BullBear Oscillator" is a custom trading indicator for TradingView that helps traders identify market trends, potential tops and bottoms, and the strength of trends using various moving averages and price relationships.
FEATURES
Calculates a base oscillator based on the close price relative to the highest and lowest prices over the past 60 periods.
Smoothes the oscillator using exponential moving averages (EMAs).
Determines market strength through relative strength indicators and moving averages.
Identifies potential tops and strong support levels based on specific conditions involving oscillators and price actions.
Plots several signals to help traders make informed decisions.
HOW TO USE
Install the script on your TradingView chart.
Customize the settings in the "Inputs" section:
Set the periods for the short-term and long-term EMAs.
Set the periods for the three SMAs used in calculations.
Interpret the plots:
BullBear Signal (Fuchsia Line): Indicates the overall market trend. Uptrends suggest buying opportunities, while downtrends suggest selling.
Decreasing BullBear Signal (Aqua Line): Highlights periods when the trend is weakening or turning bearish, signaling possible selling opportunities.
Potential Top Condition (Yellow Plot): Signals possible trend reversals from bullish to bearish, indicating times to consider taking profits or preparing for a downtrend.
High Price Condition (Yellow Plot): Indicates strong bullish momentum but also potentially overbought conditions, which might precede a correction.
Earning Condition (Red Line): Possibly signifies strong bullish signals, indicating good times to enter long positions.
Strong Support Condition (White Arrows): Signals potential bottoms or support levels, indicating buying opportunities.
Start Hiding Condition (Fuchsia Plot): Might indicate times to exit positions or reduce exposure due to unfavorable market conditions.
ALGORITHMS
Moving Averages:
Simple Moving Averages (SMAs): Used to calculate averages of price data over specified periods.
Exponential Moving Averages (EMAs): Used to give more weight to recent prices, making the moving averages more responsive to new data.
Oscillator Calculation:
The base oscillator is calculated based on the close price's position within the highest and lowest prices over 60 periods, normalized to a 0-100 scale.
This oscillator is then smoothed using EMAs to reduce noise and make trends more visible.
Relative Strength Indicator:
Calculated based on the close price's position within the highest and lowest prices over 20 periods, also normalized to a 0-100 scale.
This is smoothed using SMAs to get a more stable signal.
Condition Checks:
Various conditions are checked to identify potential tops, strong support, and other market states based on the relationships between these indicators and price actions.
LIMITATIONS
The script is based on historical data and does not guarantee future performance.
It is recommended to use the script in conjunction with other analysis tools.
The effectiveness of the strategy may vary depending on the market conditions and asset being traded.
NOTES
The script is designed for educational purposes and should not be considered financial advice.
Users are encouraged to backtest the strategy on a demo account before applying it to live trades.
THANKS
Special thanks to the TradingView community for their support and feedback.
EMA/RMA clouds by AlpachinoRE-UPLOAD
The indicator is designed for faster trend determination and also provides hints about whether the trend is strong, weaker, or if a range is expected.
It consists of an exponential moving average (EMA) and a slower smoothed moving average (RMA). I chose these because EMA is the fastest and is respected by the market, while I discovered through practice that the market often respects RMA, and in some cases, even more than EMA. Their combination is necessary because I want to take advantage of the best qualities of both averages. Displaying averages based solely on the close values creates a simple line that the market might respect. However, this is often not the case. Market makers know that many traders still believe in the theory that closing above/below an EMA signals a valid new trend. They commonly apply this belief to EMA200. Traders think that if the market closes below EMA, it signals a downtrend. That’s not necessarily true. This misconception often traps inexperienced traders.
For this reason, my indicator does not include a separate line.
I use what are called envelopes. In other words, for both EMA and RMA, the calculation uses the high and low of the selected period, which can be chosen as an input in the indicator.
Why did I choose high and low?
To stabilize price fluctuations as much as possible, especially to allow enough space for the price to react to the moving average. This reaction occurs precisely between the high and low.
Modes:
EMA Cloud – This is the most common envelope in terms of averages. It shows the best reactions with a period of 50.
What should you observe: the alignment of the envelope or its slope.
Usage:
Breakouts through the entire envelope tend to be strong, which signals that the trend may change. However, what interests you most is that the first test of the envelope after a breakout is the most successful entry point for trades in the breakout direction.
In an uptrend, the first support will be the high of the envelope, and the second (let’s call it the "ultimate support") will be the low of the envelope.
If, during an uptrend, the market closes below the low, be cautious, as the trend may reverse.
If the envelope is broken, trade the retest of the envelope.
In general, if the price is above the envelope, focus on long trades; if it’s below the envelope, focus on short trades.
Double Cloud – Since we already know that highs and lows are more relevant for price respect, I utilized this in the double cloud. Here, I use calculations for EMA and RMA highs and EMA and RMA lows.
The core idea is that since the price often reacts more to RMA than EMA, I wanted to eliminate attempts by market makers to lure you into incorrect directions. By creating more space for the price to react to the highs or lows, I made the cloud fill the area between EMA and RMA highs. This serves as the last zone where the price can hold. If the price breaks above this high cloud during a return, this doesn’t happen randomly—you should pay attention, as it’s likely signaling a range or a trend change.
The same applies to the low cloud for EMA and RMA.
The advantage of the double cloud is that you can see two clouds that may move sideways. This can resemble two walls—and they really act as such.
Usage:
Let’s say we have a downtrend. The market seems to be experiencing a downtrend exhaustion. Here's the behavior you might observe:
The price returns to the EMA/RMA low; the first reaction may still have some strength, but each subsequent return will move higher and higher into the cloud with increasingly smaller rejections downward. This indicates the absorption of selling pressure by bullish pressure. Eventually, the price may close above the cloud, significantly disrupting the downtrend and potentially signaling a reversal.
A confirmation of the reversal is usually seen with a retest of the cloud and a bounce upward into an uptrend.
The second scenario, which you’ll often see, involves sharp and significant moves through both envelopes. This kind of move is the strongest signal of a trend change. However, do not jump into trades immediately—wait for the first retest, which is usually successful. Additional tests may not work, as the breakout might not signify a trend change but rather a range.
When the clouds are far apart, it signals a weak trend or that the market is in a range. You will see that this is generally true. When the clouds cross or overlap, their initial point of contact signals the start of a stronger trend. The steeper the slope, the stronger the trend.
[blackcat] L1 Abnormal Volume Monitor█ OVERVIEW
The script is an indicator designed to monitor abnormal volume patterns in the market. It calculates and plots moving average volumes, identifies triple volume bars, and detects potential large order entries based on specific conditions.
█ FEATURES
• Input Parameters: The script defines parameters M1, M2, and lbk which control the calculation of moving averages and the lookback period for detecting abnormal volume.
• Calculations: The script calculates two moving averages of volume (MAVOL1 and MAVOL2), a smoothed price level (mm), and identifies conditions for triple volume bars and large order entries.
• Plotting: The script plots volume histograms for up and down bars, moving average volumes, and highlights triple volume bars with and without large order entries.
• Conditional Statements: The script uses conditional statements to determine when to plot certain data points and labels based on the calculated conditions.
█ LOGICAL FRAMEWORK
• xfl(cond, lbk): This function checks if a condition (cond) has been true within a specified lookback period (lbk). It returns true if the condition has been met and false otherwise.
• Parameters: cond (condition to check), lbk (lookback period).
• Return Value: outb (boolean indicating if the condition was met within the lookback period).
• abnormal_vol_monitor(close, open, high, low, volume, M1, M2, lbk): This function calculates moving average volumes, identifies triple volume bars, and detects large order entries.
• Parameters: close, open, high, low, volume (price and volume data), M1, M2 (periods for moving averages), lbk (lookback period).
• Return Value: A tuple containing MAVOL1, MAVOL2, xa (large order entry condition), and tripleVolume (triple volume condition).
█ KEY POINTS AND TECHNIQUES
• Moving Averages: The script uses simple moving averages (sma) and exponential moving averages (ema) to smooth volume data.
• Volume Analysis: The script identifies triple volume bars and large order entries based on specific conditions, such as volume doubling and price increases.
• Lookback Period: The xfl function uses a lookback period to ensure the accuracy of the detected conditions.
• Plotting Techniques: The script uses different plot styles and colors to distinguish between up bars, down bars, moving averages, and abnormal volume patterns.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
• Modifications: The script could be modified to include additional conditions for detecting other types of abnormal volume patterns or to adjust the sensitivity of the detection.
• Extensions: Similar techniques could be applied to other financial instruments or timeframes to identify unusual trading activity.
• Related Concepts: The script utilizes concepts such as moving averages, exponential moving averages, and conditional plotting, which are fundamental in Pine Script and technical analysis.
Volume Weighted Jurik Moving AverageThe Jurik Moving Average (JMA) is a smoothing indicator that is designed to improve upon traditional moving averages by reducing lag while enhancing responsiveness to price movements. It was created by Jurik Research and is often used to track trends with greater accuracy and minimal delay. The JMA is based on a combination of **exponential smoothing** and **phase adjustments**, making it more adaptable to varying market conditions compared to standard moving averages like SMA (Simple Moving Average) or EMA (Exponential Moving Average).
The core advantage of the JMA lies in its ability to adjust to price changes without excessively lagging, which is a common issue with traditional moving averages. It incorporates a **phase parameter** that can be adjusted to smooth out the signal further or make it more responsive to recent price action. This phase adjustment allows traders to fine-tune the JMA's sensitivity to the market, optimizing it for different timeframes and trading strategies.
How JMA Works and Benefits of Adding Volume Weight
The JMA works by applying a **smoothing process** to price data while allowing for adjustments through its phase and power parameters. These parameters help control the degree of smoothness and responsiveness. The result is a curve that follows price trends closely but with less lag than traditional moving averages.
Adding **volume weighting** to the JMA enhances its ability to reflect market activity more accurately. Just like the **Volume-Weighted Moving Average (VWMA)**, volume-weighting adjusts the moving average based on the strength of trading volume, meaning that price movements with higher volume will have a greater influence on the JMA. This can help traders identify trends that are supported by significant market participation, making the moving average more reliable.
The benefit of a volume-weighted JMA is that it responds more effectively to price movements that occur during periods of high trading volume, which are often considered more significant. This can help traders avoid false signals that may occur during low-volume periods when price changes may not reflect true market sentiment. By incorporating volume into the calculation, the JMA becomes more aligned with real market conditions, enhancing its effectiveness for trend identification and decision-making.
Multiple SMA, EMA, and VWAP CrossoversMultiple SMA, EMA, and VWAP Crossovers with Alerts
Overview : The "Multiple SMA, EMA, and VWAP Crossovers" script is designed for traders who want to monitor various simple moving averages (SMAs), exponential moving averages (EMAs), and the volume-weighted average price (VWAP) to identify potential buy and sell opportunities. This script allows you to visualize key moving averages on your chart and create custom alerts for specific crossover events.
Detail s: This script plots the following moving averages:
Simple Moving Averages (SMA): 5, 10, 20, 50, 100, 200, and 325 periods
Exponential Moving Average (EMA): 9 periods
Volume-Weighted Average Price (VWAP)
It includes options to display these moving averages and set alerts for their crossovers.
Available Crossovers:
20/50 SMA, 20/100 SMA, 20/200 SMA, 20/325 SMA
50/100 SMA, 50/200 SMA, 50/325 SMA
100/200 SMA, 100/325 SMA
200/325 SMA
VWAP/20 SMA, VWAP/50 SMA, VWAP/100 SMA, VWAP/200 SMA, VWAP/325 SMA
Optional Lines to Add to the Chart:
9 EMA, 5 SMA, 10 SMA, 20 SMA, 50 SMA, 100 SMA, 200 SMA, 325 SMA, VWAP
How to Use:
Enable Indicators: Use the input options to select which SMAs, EMA, and VWAP you want to display on your chart.
Set Alerts: Choose the specific crossover events you want to monitor. For example, you can set an alert for the 20/50 SMA crossover or the VWAP/100 SMA crossover.
Monitor the Chart: The script will plot the selected moving averages on your chart. When a selected crossover event occurs, an alert will be triggered, notifying you of the potential trade opportunity.
Usage Tips:
Trending Market: Use the buy and sell alerts in trending markets where the moving averages can help confirm the direction of the trend.
Key Support and Resistance Levels: Combine crossover alerts with key support and resistance levels for more reliable trading signals.
Volume Confirmation: Ensure there is sufficient volume to support the crossover signals, indicating stronger momentum behind the move.
When NOT to Use Buy and Sell Alerts:
Low Volume: Avoid using buy and sell alerts during periods of low trading volume, as the signals may be less reliable.
Market Noise: Be cautious in highly volatile markets where frequent crossovers might generate false signals.
Sideways Market: In a sideways or range-bound market, crossover signals can result in multiple whipsaws, leading to potential losses.
Why Use This Script? This script provides a comprehensive tool for traders to monitor multiple moving averages and VWAP crossovers efficiently. It allows you to customize alerts based on your trading strategy and helps you make informed decisions by visualizing key technical indicators on your chart.
Legal Disclaimer: The information provided by this script is for educational and informational purposes only and should not be considered financial advice. The developer of this script is not responsible for any financial losses incurred from using this script.
Bitcoin Macro Trend Map [Ox_kali]
## Introduction
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The “Bitcoin Macro Trend Map” script is designed to provide a comprehensive analysis of Bitcoin’s macroeconomic trends. By leveraging a unique combination of Bitcoin-specific macroeconomic indicators, this script helps traders identify potential market peaks and troughs with greater accuracy. It synthesizes data from multiple sources to offer a probabilistic view of market excesses, whether overbought or oversold conditions.
This script offers significant value for the following reasons:
1. Holistic Market Analysis : It integrates a diverse set of indicators that cover various aspects of the Bitcoin market, from investor sentiment and market liquidity to mining profitability and network health. This multi-faceted approach provides a more complete picture of the market than relying on a single indicator.
2. Customization and Flexibility : Users can customize the script to suit their specific trading strategies and preferences. The script offers configurable parameters for each indicator, allowing traders to adjust settings based on their analysis needs.
3. Visual Clarity : The script plots all indicators on a single chart with clear visual cues. This includes color-coded indicators and background changes based on market conditions, making it easy for traders to quickly interpret complex data.
4. Proven Indicators : The script utilizes well-established indicators like the EMA, NUPL, PUELL Multiple, and Hash Ribbons, which are widely recognized in the trading community for their effectiveness in predicting market movements.
5. A New Comprehensive Indicator : By integrating background color changes based on the aggregate signals of various indicators, this script essentially creates a new, comprehensive indicator tailored specifically for Bitcoin. This visual representation provides an immediate overview of market conditions, enhancing the ability to spot potential market reversals.
Optimal for use on timeframes ranging from 1 day to 1 week , the “Bitcoin Macro Trend Map” provides traders with actionable insights, enhancing their ability to make informed decisions in the highly volatile Bitcoin market. By combining these indicators, the script delivers a robust tool for identifying market extremes and potential reversal points.
## Key Indicators
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Macroeconomic Data: The script combines several relevant macroeconomic indicators for Bitcoin, such as the 10-month EMA, M2 money supply, CVDD, Pi Cycle, NUPL, PUELL, MRVR Z-Scores, and Hash Ribbons (Full description bellow).
Open Source Sources: Most of the scripts used are sourced from open-source projects that I have modified to meet the specific needs of this script.
Recommended Timeframes: For optimal performance, it is recommended to use this script on timeframes ranging from 1 day to 1 week.
Objective: The primary goal is to provide a probabilistic solution to identify market excesses, whether overbought or oversold points.
## Originality and Purpose
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This script stands out by integrating multiple macroeconomic indicators into a single comprehensive tool. Each indicator is carefully selected and customized to provide insights into different aspects of the Bitcoin market. By combining these indicators, the script offers a holistic view of market conditions, helping traders identify potential tops and bottoms with greater accuracy. This is the first version of the script, and additional macroeconomic indicators will be added in the future based on user feedback and other inputs.
## How It Works
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The script works by plotting each macroeconomic indicator on a single chart, allowing users to visualize and interpret the data easily. Here’s a detailed look at how each indicator contributes to the analysis:
EMA 10 Monthly: Uses an exponential moving average over 10 monthly periods to signal bullish and bearish trends. This indicator helps identify long-term trends in the Bitcoin market by smoothing out price fluctuations to reveal the underlying trend direction.Moving Averages w/ 18 day/week/month.
Credit to @ryanman0
M2 Money Supply: Analyzes the evolution of global money supply, indicating market liquidity conditions. This indicator tracks the changes in the total amount of money available in the economy, which can impact Bitcoin’s value as a hedge against inflation or economic instability.
Credit to @dylanleclair
CVDD (Cumulative Value Days Destroyed): An indicator based on the cumulative value of days destroyed, useful for identifying market turning points. This metric helps assess the Bitcoin market’s health by evaluating the age and value of coins that are moved, indicating potential shifts in market sentiment.
Credit to @Da_Prof
Pi Cycle: Uses simple and exponential moving averages to detect potential sell points. This indicator aims to identify cyclical peaks in Bitcoin’s price, providing signals for potential market tops.
Credit to @NoCreditsLeft
NUPL (Net Unrealized Profit/Loss): Measures investors’ unrealized profit or loss to signal extreme market levels. This indicator shows the net profit or loss of Bitcoin holders as a percentage of the market cap, helping to identify periods of significant market optimism or pessimism.
Credit to @Da_Prof
PUELL Multiple: Assesses mining profitability relative to historical averages to indicate buying or selling opportunities. This indicator compares the daily issuance value of Bitcoin to its yearly average, providing insights into when the market is overbought or oversold based on miner behavior.
Credit to @Da_Prof
MRVR Z-Scores: Compares market value to realized value to identify overbought or oversold conditions. This metric helps gauge the overall market sentiment by comparing Bitcoin’s market value to its realized value, identifying potential reversal points.
Credit to @Pinnacle_Investor
Hash Ribbons: Uses hash rate variations to signal buying opportunities based on miner capitulation and recovery. This indicator tracks the health of the Bitcoin network by analyzing hash rate trends, helping to identify periods of miner capitulation and subsequent recoveries as potential buying opportunities.
Credit to @ROBO_Trading
## Indicator Visualization and Interpretation
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For each horizontal line representing an indicator, a legend is displayed on the right side of the chart. If the conditions are positive for an indicator, it will turn green, indicating the end of a bearish trend. Conversely, if the conditions are negative, the indicator will turn red, signaling the end of a bullish trend.
The background color of the chart changes based on the average of green or red indicators. This parameter is configurable, allowing adjustment of the threshold at which the background color changes, providing a clear visual indication of overall market conditions.
## Script Parameters
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The script includes several configurable parameters to customize the display and behavior of the indicators:
Color Style:
Normal: Default colors.
Modern: Modern color style.
Monochrome: Monochrome style.
User: User-customized colors.
Custom color settings for up trends (Up Trend Color), down trends (Down Trend Color), and NaN (NaN Color)
Background Color Thresholds:
Thresholds: Settings to define the thresholds for background color change.
Low/High Red Threshold: Low and high thresholds for bearish trends.
Low/High Green Threshold: Low and high thresholds for bullish trends.
Indicator Display:
Options to show or hide specific indicators such as EMA 10 Monthly, CVDD, Pi Cycle, M2 Money, NUPL, PUELL, MRVR Z-Scores, and Hash Ribbons.
Specific Indicator Settings:
EMA 10 Monthly: Options to customize the period for the exponential moving average calculation.
M2 Money: Aggregation of global money supply data.
CVDD: Adjustments for value normalization.
Pi Cycle: Settings for simple and exponential moving averages.
NUPL: Thresholds for unrealized profit/loss values.
PUELL: Adjustments for mining profitability multiples.
MRVR Z-Scores: Settings for overbought/oversold values.
Hash Ribbons: Options for hash rate moving averages and capitulation/recovery signals.
## Conclusion
__________________________________________________________________________________
The “Bitcoin Macro Trend Map” by Ox_kali is a tool designed to analyze the Bitcoin market. By combining several macroeconomic indicators, this script helps identify market peaks and troughs. It is recommended to use it on timeframes from 1 day to 1 week for optimal trend analysis. The scripts used are sourced from open-source projects, modified to suit the specific needs of this analysis.
## Notes
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This is the first version of the script and it is still in development. More indicators will likely be added in the future. Feedback and comments are welcome to improve this tool.
## Disclaimer:
__________________________________________________________________________________
Please note that the Open Interest liquidation map is not a guarantee of future market performance and should be used in conjunction with proper risk management. Always ensure that you have a thorough understanding of the indicator’s methodology and its limitations before making any investment decisions. Additionally, past performance is not indicative of future results.
Temporary imbalances 2.0 This indicator attempts to calculate potential points of imbalance and equilibrium based on VWAPs and modified moving averages. The idea is to determine if there has been a change in volume and perform the calculation from that point It uses the standard deviation to determine the significant imbalance threshold. Candles with bullish imbalances are highlighted in green, while candles with bearish imbalances are highlighted in red.
"It also features a set of VWAPs and modified moving averages that you can enable or disable."
When you activate the 'Show Anchor VWAP' option, it will add five modified VWAPs.
Practical Significance:
The Anchored VWAP is a volume-weighted average price that serves as a dynamic reference to assess the average price during specific moments of market imbalance.
During a bullish imbalance, the anchor_vwap reflects the VWAP at that moment, emphasizing price behavior during that specific period.
Similarly, in a bearish imbalance, the anchor_vwap provides the associated VWAP for that condition, highlighting price movements during the imbalance phase.
How to Use:
The anchor_vwap can be employed to contextualize the volume-weighted average price during critical moments associated with significant changes in market imbalance.
By analyzing price behavior during and after periods of imbalance, the Anchored VWAP can help better understand market dynamics and identify potential areas of support or resistance.
Show VWAP Percent Imbalance"
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price multiplied by volume, with a focus on conditions where the percentage volume variation surpasses a predefined threshold.
Calculation: Utilizes the simple moving average weighted of the product of the volume-weighted average price and volume only when the percentage volume variation exceeds a specific threshold.
Interpretation: Provides insight into the volume-weighted price trend during conditions where the percentage volume variation exceeds a predefined limit.
The "showDeltaVWAP" is a toggleable setting that you can turn on or off. When activated, it displays special lines on the chart. Let's understand what these lines represent:
Delta Anchor VWAP:
A green line (Delta Anchor VWAP) represents a measure of market volume imbalance.
Delta2 Anchor VWAP:
A red line (Delta2 Anchor VWAP) shows another perspective of volume imbalance.
VWAP Delta Volume:
A light blue line (VWAP Delta Volume) displays a volume-weighted average of price.
VWAP Delta Volume2:
An orange line (VWAP Delta Volume2) shows another view of the volume-weighted average of price.
Delta3 Anchor VWAP:
A light blue line (Delta3 Anchor VWAP) represents a combination of the previous measures.
Delta4 Anchor VWAP:
A purple line (Delta4 Anchor VWAP) is another combination, providing an overall view.
These lines are based on different conditions and calculations related to trading volume. When you activate "showDeltaVWAP," these lines appear on the chart, aiding in better understanding market behavior.
"Show Faster Volatility" is an option that you can enable or disable. When activated (set to true), it displays special lines on the chart called "Faster Volatility VWAP," "Faster Volatility VWAP2," and "Faster Volatility VWAP3." Let's understand what these lines represent:
Faster Volatility VWAP:
A purple line (Faster Volatility VWAP) is a Volume Weighted Average Price (VWAP) that is calculated more quickly based on short-term price reversal patterns.
Faster Volatility VWAP2:
A light gray line (Faster Volatility VWAP2) is another Volume Weighted Average Price (VWAP) that is calculated even more quickly based on even shorter-term price reversal patterns.
Faster Volatility VWAP3:
A purple line (Faster Volatility VWAP3) is another Volume Weighted Average Price (VWAP) calculated rapidly based on even shorter-term price reversal patterns.
These lines are designed to indicate moments of possible exhaustion of volatility in the market, suggesting that there may be a subsequent increase in volatility. When you activate "Show Faster Volatility," these lines are displayed on the chart.
"Show Average VWAPs Imbalance" displays weighted averages of different Volume Weighted Average Prices (VWAPs) in relation to specific market conditions. Here's an explanation of each component:
Standard VWAP:
The blue line represents the standard VWAP, a volume-weighted average of asset prices over a specific period.
VWAP with Added Imbalance (avg_vwap2):
The pink line is a weighted average that adds an imbalance value to the standard VWAP. This component highlights periods of market imbalance.
VWAP with Balance (avg_vwap3):
The lilac line is a weighted average that adds balance based on the imbalance between uptrend and downtrend, reflecting changes in volume. This provides insights into supply and demand dynamics.
Overall Average of VWAPs (avg_vwaptl):
The violet line is a weighted average that incorporates both standard and adjusted VWAPs, offering an overview of market behavior under different considered conditions.
Visual Customization (Show Average VWAPs Imbalance):
Users have the option to show or hide these average lines on the chart, allowing for a clear visualization of market trends.
"Show Min Variation VWAP" is associated with the calculation and display of a smoothed version of the Volume Weighted Average Price (VWAP), taking into account the minimum price variation over a specific period.
"How Imbalance Anchor VWAP Calculated as the smoothed relationship between liquidity difference and maximum VWAP equilibrium" is associated with the calculation and display of a smoothed version of the Imbalance Anchor VWAP. Here is a detailed explanation:
Calculations and Smoothing:
The variable "smoothed_difference" represents the exponential moving average (EMA) of the difference between two variables related to liquidity.
"smoothed_difference2" is the division of "smoothed_difference" by the maximum variation of the VWAP Equilibrium.
"smoothed_difference3" involves additional manipulation of "smoothed_difference" and "vwap_delta3."
"smoothed_difference4" incorporates the previous results, adjusted by the value of the VWAP.
Visual Customization:
The user has the option to enable or disable the display on the chart.
The line is colored in a shade of green.
It provides a smoothed representation of the Imbalance Anchor VWAP.
The line is colored in a shade of blue, and the calculation involves the summation of moving averages (20, 50, 200). Afterward, there is division by 3. Additionally, there is the summation of moving averages (766, 866, 966), divided by 3. The final step is to add these results together and divide by 2. media name is Imbalance Value2
Show VWAP Equilibrium (Max Variation) Calculated as the difference between two VWAPs derived from the highest and lowest price changes
Show Equilibrium VWAP Calculated as the sum of VWAP and (sma200 - sma20)
calculate the difference between the media of 200 to 20
Show Equilibrium VWAP Calculated as the sum of VWAP and (766+866+966)/3 - (sma200 - sma20)
Show Equilibrium VWAP Standard Deviation Calculated as the Exponential Moving Average (EMA) of the Standard Deviation of SMA (sma200 + sma20 + sma8)/3
Show Equilibrium VWAP Delta Calculated as the ratio of the smoothed VWAP Delta Result componentes
Show Standard Deviation Equilibrium VWAP Delta: Calculated as the Standard Deviation between the Average of VWAP Delta Result Components and Their Smoothed Versions
This average attempts to calculate the equilibrium."
vwap_equilibrium:
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price (hl2) multiplied by volume, focusing on periods of volume equilibrium.
Calculation: Utilizes the simple moving average weighted (sma) of the product of the volume-weighted average price and volume only when there is no volume imbalance.
Interpretation: This indicator provides a view of the volume-weighted price trend during moments when the market is in equilibrium, meaning there is no noticeable imbalance in volume conditions. The calculation of VWAP is adjusted to reflect market characteristics during periods of stability.
vwap_percent_condition:
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price multiplied by volume, with a focus on conditions where the percentage volume variation surpasses a predefined threshold.
Calculation: Utilizes the simple moving average weighted of the product of the volume-weighted average price and volume only when the percentage volume variation exceeds a specific threshold.
Interpretation: Provides insight into the volume-weighted price trend during conditions where the percentage volume variation exceeds a predefined limit.
The objective of these two VWAPs is to calculate possible equilibrium points between buyers and sellers.
The indicator works for all timeframes This indicator can be adjusted according to the preferences and characteristics of the specific asset or market. It provides clear visual information and can be used as a complementary tool for technical analysis in trading strategies.
Interesting
Interesting
lookback period 7 , 12, 20,70,200, 500,766,866,966
imbalance threshold 2.4, 3.3 ,4.2
The objective of this indicator is to identify and highlight various points of imbalance and equilibrium.
