TASC 2022.09 LRAdj EMA█ OVERVIEW
TASC's September 2022 edition of Traders' Tips includes an article by Vitali Apirine titled "The Linear Regression-Adjusted Exponential Moving Average". This script implements the titular indicator presented in this article.
█ CONCEPT
The Linear Regression-Adjusted Exponential Moving Average (LRAdj EMA) is a new tool that combines a linear regression indicator with exponential moving averages . First, the indicator accounts for the linear regression deviation, that is, the distance between the price and the linear regression indicator. Subsequently, an exponential moving average (EMA) smooths the price data and and provides an indication of the current direction.
As part of a trading system, LRAdj EMA can be used in conjunction with an exponential moving average of the same length to identify the overall trend. Alternatively, using LRAdj EMAs of different lengths together can help identify turning points.
█ CALCULATION
The script uses the following input parameters:
EMA Length
LR Lookback Period
Multiplier
The calculation of LRAdj EMA is carried out as follows:
Current LRAdj EMA = Prior LRAdj EMA + MLTP × (1+ LRAdj × Multiplier ) × ( Price − Prior LRAdj EMA ),
where MLTP is a weighting multiplier defined as MLTP = 2 ⁄ ( EMA Length + 1), and LRAdj is the linear regression adjustment (LRAdj) multiplier:
LRAdj = (Abs( Current LR Dist )−Abs( Minimum LR Dist )) ⁄ (Abs( Maximum LR Dist )−Abs( Minimum LR Dist ))
When calculating the LRAdj multiplier, the absolute values of the following quantities are used:
Current LR Dist is the distance between the current close and the linear regression indicator with a length determined by the LR Lookback Period parameter,
Minimum LR Dist is the minimum distance between the close and the linear regression indicator for the LR lookback period ,
Maximum LR Dist is the maximum distance between the close and the linear regression indicator for the LR lookback period .
Cerca negli script per "Exponential Moving Average"
Nyquist Moving Average (NMA) MACD [Loxx]Nyquist Moving Average (NMA) MACD is a MACD indicator using Nyquist Moving Average for its calculation.
What is the Nyquist Moving Average?
A moving average outlined originally developed by Dr . Manfred G. Dürschner in his paper "Gleitende Durchschnitte 3.0".
In signal processing theory, the application of a MA to itself can be seen as a Sampling procedure. The sampled signal is the MA (referred to as MA.) and the sampling signal is the MA as well (referred to as MA). If additional periodic cycles which are not included in the price series are to be avoided sampling must obey the Nyquist Criterion.
It can be concluded that the Moving Averages 3.0 on the basis of the Nyquist Criterion bring about a significant improvement compared with the Moving Averages 2.0 and 1.0. Additionally, the efficiency of the Moving Averages 3.0 can be proven in the result of a trading system with NWMA as basis.
What is the MACD?
Moving average convergence divergence (MACD) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average (EMA) from the 12-period EMA.
The result of that calculation is the MACD line. A nine-day EMA of the MACD called the "signal line," is then plotted on top of the MACD line, which can function as a trigger for buy and sell signals. Traders may buy the security when the MACD crosses above its signal line and sell—or short—the security when the MACD crosses below the signal line. Moving average convergence divergence (MACD) indicators can be interpreted in several ways, but the more common methods are crossovers, divergences, and rapid rises/falls.
Included
Bar coloring
2 types of signal output options
Alerts
Loxx's Expanded Source Types
Fukuiz Octa-EMA + Ichimoku (Strategy)This strategy is based EMA of 8 different period and Ichimoku Cloud which works better in 1hr 4hr and daily time frame.
#A brief introduction to Ichimoku #
The Ichimoku Cloud is a collection of technical indicators that show support and resistance levels, as well as momentum and trend direction. It does this by taking multiple averages and plotting them on a chart. It also uses these figures to compute a “cloud” that attempts to forecast where the price may find support or resistance in the future.
#A brief introduction to EMA#
An exponential moving average ( EMA ) is a type of moving average (MA) that places a greater weight and significance on the most recent data points. The exponential moving average is also referred to as the exponentially weighted moving average . An exponentially weighted moving average reacts more significantly to recent price changes than a simple moving average ( SMA ), which applies an equal weight to all observations in the period.
#How to use#
The strategy will give entry points itself, you can monitor and take profit manually(recommended), or you can use the exit setup.
EMA (Color) = Bullish trend
EMA (Gray) = Bearish trend
#Condition#
Buy = All Ema (color) above the cloud.
SELL= All Ema turn to gray color.
EMA/Session/ATR/LotSizeSeveral indicators combined
1. 6 Exponential Moving Averages - Identifying the trend direction or using EMAs as a dynamic support/resistance.
2. Session on Chart - Highlighting session for day trading. London, New York, Tokyo, and Sydney.
3. Average True Range - display the Average True Range on recent price to calculate the volatility.
4. Lot Size Calculator - to calculate lot size based on account balance, risk per trade, atr stop-loss, and art multiplier.
5. ATRX - ATRX is an indicator that gives the value of the (close price - EMA 27)/ATR (14)
It tells how strong the trend is compared to its volatility
According to AJ. BANK FTMO Trader Thailand, if the value of ATRX is between 2X-3X or -2X-3X, you should consider trading using climax zone on timeframe H1.
If the ATRX is more than 3X or less than -3X but does not exceed 4X or -4X, you should consider trading using timeframe M15 in the climax zone.
However, if the ATRX exceeds 4X or -4X, use M5 instead.
Logarithmic Bollinger BandsLogarithmic Bollinger Bands
Published by Eric Thies on January 14, 2022
Summary
In this script I have taken the standard Bollinger band pinescript and made efforts to eliminate the behavior experienced in periods of high volatility in which we see the bands disappear completely off the chart by adding exponential plotting and logarithmic sourcing to the tool.
This tool will also show periods of Bearish and Bullish Expansion for users to see when volatility is running high in the market.
More On Bollinger Bands
Bollinger Bands consist of a center line representing the moving average of a security’s price over a certain period, and two additional parallel lines (called the upper and lower trading bands) one of which is just the moving average plus k-times the standard deviation over the selected time frame, and the other being the moving average minus k-times the standard deviation over that same timeframe. This technique has been developed in the 1980’s by John Bollinger, who lately registered the terms “Bollinger Bands” as a U.S. trademark in 2011. Technical analysts typically use 20 periods and k = 2 as default settings to build Bollinger Bands, while they can choose a simple or exponential moving average. Bollinger Bands provide a relative definition of high and low prices of a security. When the security is trading within the upper band, the price is considered high, while it is considered low when the security is trading within the lower band.
There is no general consensus on the use of Bollinger Bands among traders. Some traders see a buy signal when the price hits the lower Bollinger Band and close their position when the price hits the moving average. Some others buy when the price crosses over the upper band and sell when the price crosses below the lower band. We can see here two opposing interpretations based on different rationales, depending whether we are in a reversal or continuation pattern. Another interesting feature of the Bollinger Bands is that they give an indication of the volatility levels; a widening gap between the upper and lower bands indicates an increasing volatility, while a narrowing band indicates a decreasing volatility. Moreover, when the bands have an almost flat slope (parallel to the x-axis) the price will generally oscillate between the bands as if trading through a channel.
// © 2022 KINGTHIES THIS SOURCE CODE IS SUBJECT TO TERMS OF MOZILLA PUBLIC LICENSE 2.0 (MOZILLA.ORG/MPL/2.0)
//@version=5
//## !<---------------- © KINGTHIES --------------------->
indicator('Logarithmic Bollinger Bands (kingthies)',shorttitle='LogBands_KT',overlay=true)
// { BBANDS
src = math.log(input(close,title="Source"))
lenX = input(20,title='lenX')
highlights = input(false,title="Highlight Bear and Bull Expansions?")
mult = 2
bbandBasis = ta.sma(src,lenX)
dev = 2 * ta.stdev(src, 20)
upperBB = bbandBasis + dev
lowerBB = bbandBasis - dev
bbw = (upperBB-lowerBB)/bbandBasis
bbr = (src - lowerBB)/(upperBB - lowerBB)
// }
// { BBAND EXPANSIONS
bullExp= ta.rising(upperBB,1) and ta.falling(lowerBB,1) and ta.rising(bbandBasis,1) and ta.rising(bbw,1) and ta.rising(bbr,1)
bearExp= ta.rising(upperBB,1) and ta.falling(lowerBB,1) and ta.falling(bbandBasis,1) and ta.rising(bbw,1) and ta.falling(bbr,1)
// }
// { COLORS
greenBG = color.rgb(9,121,105,75), redBG = color.rgb(136,8,8,75)
bullCol = highlights and bullExp ? greenBG : na, bearCol = highlights and bearExp ? redBG : na
// }
// { INDICATOR PLOTTING
lowBB=plot(math.exp(lowerBB),title='Low Band',color=color.aqua),plot(math.exp(bbandBasis),title='BBand Basis',color=color.red),
highBB=plot(math.exp(upperBB),title='High Band',color=color.aqua),fill(lowBB,highBB,title='Band Fill Color',color=color.rgb(0,128,128,75))
bgcolor(bullCol,title='Bullish Expansion Highlights'),bgcolor(bearCol,title='Bearish Expansion Highlights')
// }
Kelt + BBand Combination (kingthies) █ Overview
The Kelt-BBand Combo is a trading approach that I've used for multiple years now, and works on any timeframe, chart possible. There are various versions of this approach published by myself and others who find value in measuring the deviations of price and strategize market entries and exits. For an entry-level description of each component, I'll type them up below.
█ Using This Indicator
While there are various strategies to use this tool, I'll share the one that has yielded me the most success across traditional and cryptocurrency markets - first understand the different appearances of both....
IF the bbands are inside the kelts, the squeeze is on. In 90% of cases this is often a bullish leaning event
IF the bbands are pinching (regardless of slope or kelt behavior),these are your primary support and resistances, respectively
When trending up, HA candles will touch between the upper kelt and upper bband on every candle, across all timeframes
When trending down, HA candles will touch between the lower kelt and lower bband on every candle, across all timeframes
If one timeframe is not giving clear indicator of trend direction or s/r to follow, zoom out. the higher timeframe will always win and show you the true direction
█ Intro to Bollinger Bands
Bollinger Bands consists of a center line representing the moving average of a security’s price over a certain period, and two additional parallel lines (called the trading bands) one of which is just the moving average plus k-times the standard deviation over the selected time frame, and the other being the moving average minus k-times the standard deviation over that same timeframe. This technique has been developed in the 1980’s by John Bollinger, who lately registered the terms “Bollinger Bands” as a U.S. trademark in 2011. Technical analysts typically use 20 periods and k = 2 as default settings to build Bollinger Bands, while they can choose a simple or exponential moving average. Bollinger Bands provide a relative definition of high and low prices of a security. When the security is trading within the upper band, the price is considered high, while it is considered low when the security is trading within the lower band.
There is no general consensus on the use of Bollinger Bands among traders. Some traders see a buy signal when the price hits the lower Bollinger Band and close their position when the price hits the moving average. Some others buy when the price crosses over the upper band and sell when the price crosses below the lower band. We can see here two opposing interpretations based on different rationales, depending whether we are in a reversal or continuation pattern. Another interesting feature of the Bollinger Bands is that they give an indication of the volatility levels; a widening gap between the upper and lower bands indicates an increasing volatility, while a narrowing band indicates a decreasing volatility. Moreover, when the bands have an almost flat slope (parallel to the x-axis) the price will generally oscillate between the bands as if trading through a channel.
█ Intro to Keltner Channels
Keltner Channels aka Kelts were first described by a Chicago grain trader called Chester W. Keltner in his 1960 book How to Make Money in Commodities. Though Keltner claimed no ownership of the original idea and simply called it the ten-day moving average trading rule, his name was applied by those who heard of this concept through his books.
Similarly to the Bollinger Bands, Keltner channel is a technical analysis tool based on three parallel lines. In fact, the Keltner indicator consists of a central moving average in addition to channel lines spread above and below it. The central line represents a 10-day simple moving average of what Chester W. Keltner called typical price. The typical price is defined as the average of the high, low and close. The distance between the central line and the upper, or lower line, is equivalent to the simple moving average of the preceding 10 days' trading ranges.
One way to interpret the Keltner Channel would be to consider the price breakouts outside of the channel. A trader would track price movement and consider any close above the upper line as a strong buy signal. Equivalently, any close below the lower line would be considered a strong sell signal. The trader would follow the trend emphasized by the indicator while complementing his analysis with the use of other indicators as well. However, the breakout method only works well when the market moves from a range-bound setting to an established trend. In a trend-less configuration, the Keltner Channel is better used as an overbought/oversold indicator. Thus, as the price breaks out below the lower band, a trader waits for the next close inside the Keltner Channel and considers this price behavior as an oversold situation indicating a potential buy signal. Similarly, as the price breaks out above the upper band, the trader waits for the next close inside the Keltner Channel and considers this price movement as an overbought situation indicating a potential sell signal. By waiting for the price to close within the Channel, the trader avoids getting caught in a real upside or downside breakout.
Happy Trading!
Combo Backtest 123 Reversal & Moving Average Envelopes This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
Moving Average Envelopes are percentage-based envelopes set above and
below a moving average. The moving average, which forms the base for
this indicator, can be a simple or exponential moving average. Each
envelope is then set the same percentage above or below the moving average.
This creates parallel bands that follow price action. With a moving average
as the base, Moving Average Envelopes can be used as a trend following indicator.
However, this indicator is not limited to just trend following. The envelopes
can also be used to identify overbought and oversold levels when the trend is
relatively flat.
WARNING:
- For purpose educate only
- This script to change bars colors.
Adjustable Moving AveragesAdjustable Moving Averages
This script has fixed simple moving averages and fixed exponential moving averages function.
And script has 2 lines
1. Simpe Moving Average Line
2. Exponential Moving Average Line
You can change this 2 lines length and also you can change periods aswell.
With this; you can use any length of sma and ema with different periods without changing period.
For example this chart on 1 day period
And you can see 2 lines
Red Line: SMA100 and 4H perioıd
Yellow Line : EMA100 and 4H period
Multiple Time Frames Moving Averages (x3)This indicator is a set of 3 moving averages for which you can configure the type of the moving averages , their length , and of course the time frame . The moving averages you can choose from are:
- Simple Moving Average ( SMA )
- Exponential Moving Average ( EMA )
- Weighted Moving Average ( WMA )
- Running Moving Average (RMA)
- Hull Moving Average ( HMA )
- Volume Weighted Moving Average ( VWMA )
- Arnaud Legoux Moving Average ( ALMA )
The time-frames you can choose from - minutes (1, 3, 5, 15, 45), hours (1, 2, 3, 4, 12), days (1, 3), weekly or monthly .
Overall, it is a minimalistic indicator. No major improvements or trading logic like some of my other indicators, but I did make it slightly easier to use and visually appealing. The MAs' colors change from light to dark green/blue/red depending on the trend - bullish or bearish respectively. Initially, those were changing from green to red (based on direction) but it became a bit confusing when they started crossing each other. Anyway, feel free to change those colors to whatever you like.
If you have suggestions on how to improve this indicator or ideas about new ones, please drop me a line. Thanks.
Show EMA and SMA's at the same timeYou can now add both exponential and simple moving averages at the same time. ie a 7 day Simple Moving Average and a 21 day Exponential Moving Average.
Advanced MACDThis is a more advanced version of the standard moving average convergence/divergence indicator (MACD). It allows you to change the type of all moving averages (Simple, Exponential, Weighted, Volume-weighted, Triple EMA or a moving average that uses RSI). By for example setting the period to 3/10/16 and use simple moving averages instead of exponential moving averages you can turn it into the modified version of the MACD oscillator (mMACD) described in detail in Appendix B in the book "The Art and Science of Technical Analysis: Market Structure, Price Action and Trading Strategies" by Adam Grimes.
The indicator also allows you to volume weight the indicator (turned on by default), which will turn it into a Volume-Weighted Moving Average Convergence Divergence (VW-MACD) first used by Buff Pelz Dormeier in 2002 and described in detail in his book "Investing with Volume Analysis: Identify, Follow, and Profit from Trends". If you want to weight the oscillator against the true range instead of volume this is also possible. By default, this will be done automatically for assets that do not support volume.
MASelect Crossover StratBasic Crossover Strategy for backtesting purposes, to use with the study+alert script.
Use "Format" to change your settings. Both Moving Averages can be changed individually to swap between EMA (Exponential Moving Average), SMA (Simple Moving Average), WMA (Weighted Moving Average), DEMA (Double Exponential Moving Average) and VWMA (Volume Weighted Moving Average).
"Active Length" should be shorter than "Base Length". As usual with crossover strategies, candle resolution will affect results greatly. Longer=better.
Strategy options are "Long+Short" or "Long Only".
Entries/Exits are based on crossovers/crossunders only, but I encourage you to add further exit conditions and play around with the code.
I made this for beginners on Autoview discord to have something to play with, and added some unnecessary visual changes just to give code examples (changing things like background color, candle color, line color, plotting shapes, different plot styles).
Play around combining different types of Moving Averages of different lengths.
Moving Average Envelopes Backtest Moving Average Envelopes are percentage-based envelopes set above and
below a moving average. The moving average, which forms the base for
this indicator, can be a simple or exponential moving average. Each
envelope is then set the same percentage above or below the moving average.
This creates parallel bands that follow price action. With a moving average
as the base, Moving Average Envelopes can be used as a trend following indicator.
However, this indicator is not limited to just trend following. The envelopes
can also be used to identify overbought and oversold levels when the trend is
relatively flat.
You can change long to short in the Input Settings
WARNING:
- For purpose educate only
- This script to change bars colors.
Moving Average Envelopes Moving Average Envelopes are percentage-based envelopes set above and
below a moving average. The moving average, which forms the base for
this indicator, can be a simple or exponential moving average. Each
envelope is then set the same percentage above or below the moving average.
This creates parallel bands that follow price action. With a moving average
as the base, Moving Average Envelopes can be used as a trend following indicator.
However, this indicator is not limited to just trend following. The envelopes
can also be used to identify overbought and oversold levels when the trend is
relatively flat.
WARNING:
- This script to change bars colors.
Moving Average Envelopes Moving Average Envelopes are percentage-based envelopes set above and
below a moving average. The moving average, which forms the base for
this indicator, can be a simple or exponential moving average. Each
envelope is then set the same percentage above or below the moving average.
This creates parallel bands that follow price action. With a moving average
as the base, Moving Average Envelopes can be used as a trend following indicator.
However, this indicator is not limited to just trend following. The envelopes
can also be used to identify overbought and oversold levels when the trend is
relatively flat.
Money Flow Indicator (Chaikin Oscillator) Strategy Indicator plots Money Flow Indicator (Chaikin). This indicator looks
to improve on Larry William's Accumulation Distribution formula that
compared the closing price with the opening price. In the early 1970's,
opening prices for stocks stopped being transmitted by the exchanges.
This made it difficult to calculate Williams' formula. The Chaikin
Oscillator uses the average price of the bar calculated as follows
(High + Low) /2 instead of the Open.
The indicator subtracts a 10 period exponential moving average of the
AccumDist function from a 3 period exponential moving average of the
AccumDist function.
WARNING:
This script to change bars colors.
Multi Movings Averages
This tool can plot a maximum of 10 movings averages that are easily adaptable and configurable.
You can also use a exponential moving average instead of the simple moving average.
hope you enjoy :)
EMAs Bullish/Bearish Confluence [Trend Bias]EMA Confluence Zones
This indicator is designed to simplify trend identification by visually highlighting "Confluence Zones" —areas where short-term, medium-term, and long-term momentum are fully aligned.
While traders can manually add three Moving Averages to a chart, identifying the exact moment all three align (the "Perfect Stack") can be visually difficult during live trading. This script automates that process, converting complex line crosses into simple background color zones and providing actionable alerts for the exact moment a trend alignment begins.
🛠 How It Works
The script utilizes three customizable Exponential Moving Averages (EMAs) to detect the market bias:
Short EMA: Represents immediate price action/momentum.
Medium EMA: Represents the intermediate trend.
Long EMA: Represents the major trend baseline.
Calculations & Logic
The indicator checks for a specific hierarchical alignment (Stacking) of these averages:
1. 🟢 Bullish Confluence (Buy Zone):** Returns true when `Short > Medium` AND `Medium >Long`. This confirms that momentum is rising across all three monitored timeframes.
2. 🔴 Bearish Confluence (Sell Zone):** Returns true when `Short < Medium` AND `Medium < Long`. This confirms that momentum is falling across all three monitored timeframes.
3. ⚪ Neutral (No Color): Any other state indicates a choppy or consolidating market where the EMAs are intertwined.
---
🚀 Key Features
*Visual Bias Confirmation: The background highlights Green (Bullish) or Red (Bearish) only when the "Perfect Stack" conditions are met.
Trend Start Alerts: Unlike standard EMA cross alerts, this script includes custom alert conditions that trigger only on the first bar where the confluence becomes valid. This prevents spam alerts during a prolonged trend.
Full Customization: Users can adjust the lengths of all three EMAs to fit specific strategies (e.g., Scalping vs. Swing Trading).
Clean Chart Mode: Includes options to hide the EMA lines entirely and rely solely on the background color for a minimalist "Naked Trading" setup.
🎯 How to Use
1. Trend Filter: Use the background color to determine your directional bias. If the background is Green, look only for Long setups on lower timeframes. If Red, look only for Short setups.
2. Breakout Confirmation: If price breaks a key level, wait for the background color to flip. This confirms that the Moving Averages have caught up to the move, validating the breakout strength.
3. Exit Signal: If you are in a trend trade and the background color disappears (turns transparent), it indicates the trend momentum is fading and the EMAs are beginning to cross/compress.
⚙️ Settings
EMA Lengths: Default is 20, 50, 100. These can be changed to common combinations like (9, 21, 55) or (50, 100, 200).
Visuals: Toggle lines or background colors on/off and adjust transparency to keep your chart readable.
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Disclaimer: This script is for informational purposes only. Past performance of a trend following method does not guarantee future results. Always use proper risk management.
Flux-Tensor Singularity [FTS]Flux-Tensor Singularity - Multi-Factor Market Pressure Indicator
The Flux-Tensor Singularity (FTS) is an advanced multi-factor oscillator that combines volume analysis, momentum tracking, and volatility-weighted normalization to identify critical market inflection points. Unlike traditional single-factor indicators, FTS synthesizes price velocity, volume mass, and volatility context into a unified framework that adapts to changing market regimes.
This indicator identifies extreme market conditions (termed "singularities") where multiple confirming factors converge, then uses a sophisticated scoring system to determine directional bias. It is designed for traders seeking high-probability setups with built-in confluence requirements.
THEORETICAL FOUNDATION
The indicator is built on the premise that market time is not constant - different market conditions contain varying levels of information density. A 1-minute bar during a major news event contains far more actionable information than a 1-minute bar during overnight low-volume trading. Traditional indicators treat all bars equally; FTS does not.
The theoretical framework draws conceptual parallels to physics (purely as a mental model, not literal physics):
Volume as Mass: Large volume represents significant market participation and "weight" behind price moves. Just as massive objects have stronger gravitational effects, high-volume moves carry more significance.
Price Change as Velocity: The rate of price movement through price space represents momentum and directional force.
Volatility as Time Dilation: When volatility is high relative to its historical norm, the "information density" of each bar increases. The indicator weights these periods more heavily, similar to how time dilates near massive objects in physics.
This is a pedagogical metaphor to create a coherent mental model - the underlying mathematics are standard financial calculations combined in a novel way.
MATHEMATICAL FRAMEWORK
The indicator calculates a composite singularity value through four distinct steps:
Step 1: Raw Singularity Calculation
S_raw = (ΔP × V) × γ²
Where:
ΔP = Price Velocity = close - close
V = Volume Mass = log(volume + 1)
γ² = Time Dilation Factor = (ATR_local / ATR_global)²
Volume Transformation: Volume is log-transformed because raw volume can have extreme outliers (10x-100x normal). The logarithm compresses these spikes while preserving their significance. This is standard practice in volume analysis.
Volatility Weighting: The ratio of short-term ATR (5 periods) to long-term ATR (user-defined lookback) is squared to create a volatility amplification factor. When local volatility exceeds global volatility, this ratio increases, amplifying the raw singularity value. This makes the indicator regime-aware.
Step 2: Normalization
The raw singularity values are normalized to a 0-100 scale using a stochastic-style calculation:
S_normalized = ((S_raw - S_min) / (S_max - S_min)) × 100
Where S_min and S_max are the lowest and highest raw singularity values over the lookback period.
Step 3: Epsilon Compression
S_compressed = 50 + ((S_normalized - 50) / ε)
This is the critical innovation that makes the sensitivity control functional. By applying compression AFTER normalization, the epsilon parameter actually affects the final output:
ε < 1.0: Expands range (more signals)
ε = 1.0: No change (default)
ε > 1.0: Compresses toward 50 (fewer, higher-quality signals)
For example, with ε = 2.0, a normalized value of 90 becomes 70, making threshold breaches rarer and more significant.
Step 4: Smoothing
S_final = EMA(S_compressed, smoothing_period)
An exponential moving average removes high-frequency noise while preserving trend.
SIGNAL GENERATION LOGIC
When the tensor crosses above the upper threshold (default 90) or below the lower threshold (default 10), an extreme event is detected. However, the indicator does NOT immediately generate a buy or sell signal. Instead, it analyzes market context through a multi-factor scoring system:
Scoring Components:
Price Structure (+1 point): Current bar bullish/bearish
Momentum (+1 point): Price higher/lower than N bars ago
Trend Context (+2 points): Fast EMA above/below slow EMA (weighted heavier)
Acceleration (+1 point): Rate of change increasing/decreasing
Volume Multiplier (×1.5): If volume > average, multiply score
The highest score (bullish vs bearish) determines signal direction. This prevents the common indicator failure mode of "overbought can stay overbought" by requiring directional confirmation.
Signal Conditions:
A BUY signal requires:
Extreme event detection (tensor crosses threshold)
Bullish score > Bearish score
Price confirmation: Bullish candle (optional, user-controlled)
Volume confirmation: Volume > average (optional, user-controlled)
Momentum confirmation: Positive momentum (optional, user-controlled)
A SELL signal requires the inverse conditions.
INPUTS EXPLAINED - Core Parameters:
Global Horizon (Context): Default 20. Lookback period for normalization and volatility comparison. Higher values = smoother but less responsive. Lower values = more signals but potentially more noise.
Tensor Smoothing: Default 3. EMA period applied to final output. Removes "quantum foam" (high-frequency noise). Range 1-20.
Singularity Threshold: Default 90. Values above this (or below 100-threshold) trigger extreme event detection. Higher = rarer, stronger signals.
Signal Sensitivity (Epsilon): Default 1.0. Post-normalization compression factor. This is the key innovation - it actually works because it's applied AFTER normalization. Range 0.1-5.0.
Signal Interpreter Toggles:
Require Price Confirmation: Default ON. Only generates buy signals on bullish candles, sell signals on bearish candles. Reduces false signals but may delay entry.
Require Volume Confirmation: Default ON. Only signals when volume > average. Critical for stocks/crypto, less important for forex (unreliable volume data).
Use Momentum Filter: Default ON. Requires momentum agreement with signal direction. Prevents counter-trend signals.
Momentum Lookback: Default 5. Number of bars for momentum calculation. Shorter = more responsive, longer = trend-following bias.
Visual Controls:
Colors: Customizable colors for bullish flux, bearish flux, background, and event horizon.
Visual Transparency: Default 85. Master control for all visual elements (accretion disk, field lines, particles, etc.). Range 50-99. Signals and dashboard have separate controls.
Visibility Toggles: Individual on/off switches for:
Gravitational field lines (trend EMAs)
Field reversals (trend crossovers)
Accretion disk (background gradient)
Singularity diamonds (neutral extreme events)
Energy particles (volume bursts)
Event horizon flash (extreme event background)
Signal background flash
Signal Size: Tiny/Small/Normal triangle size
Signal Offsets: Separate controls for buy and sell signal vertical positioning (percentage of price)
Dashboard Settings:
Show Dashboard: Toggle on/off
Position: 9 placement options (all corners, centers, middles)
Text Size: Tiny/Small/Normal/Large
Background Transparency: 0-50, separate from visual transparency
VISUAL ELEMENTS EXPLAINED
1. Accretion Disk (Background Gradient):
A three-layer gradient background that intensifies as the tensor approaches extremes. The outer disk appears at any non-neutral reading, the inner disk activates above 70 or below 30, and the core layer appears above 85 or below 15. Color indicates direction (cyan = bullish, red = bearish). This provides instant visual feedback on market pressure intensity.
2. Gravitational Field Lines (EMAs):
Two trend-following EMAs (10 and 30 period) visualized as colored lines. These represent the "curvature" of market trend - when they diverge, trend is strong; when they converge, trend is weakening. Crossovers mark potential trend reversals.
3. Field Reversals (Circles):
Small circles appear when the fast EMA crosses the slow EMA, indicating a potential trend change. These are distinct from extreme events and appear at normal market structure shifts.
4. Singularity Diamonds:
Small diamond shapes appear when the tensor reaches extreme levels (>90 or <10) but doesn't meet the full signal criteria. These are "watch" events - extreme pressure exists but directional confirmation is lacking.
5. Energy Particles (Dots):
Tiny dots appear when volume exceeds 2× average, indicating significant participation. Color matches bar direction. These highlight genuine high-conviction moves versus low-volume drifts.
6. Event Horizon Flash:
A golden background flash appears the instant any extreme threshold is breached, before directional analysis. This alerts you to pay attention.
7. Signal Background Flash:
When a full buy/sell signal is confirmed, the background flashes cyan (buy) or red (sell). This is your primary alert that all conditions are met.
8. Signal Triangles:
The actual buy (▲) and sell (▼) markers. These only appear when ALL selected confirmation criteria are satisfied. Position is offset from bars to avoid overlap with other indicators.
DASHBOARD METRICS EXPLAINED
The dashboard displays real-time calculated values:
Event Density: Current tensor value (0-100). Above 90 or below 10 = critical. Icon changes: 🔥 (extreme high), ❄️ (extreme low), ○ (neutral).
Time Dilation (γ): Current volatility ratio squared. Values >2.0 indicate extreme volatility environments. >1.5 = elevated, >1.0 = above average. Icon: ⚡ (extreme), ⚠ (elevated), ○ (normal).
Mass (Vol): Log-transformed volume value. Compared to volume ratio (current/average). Icon: ● (>2× avg), ◐ (>1× avg), ○ (below avg).
Velocity (ΔP): Raw price change. Direction arrow indicates momentum direction. Shows the actual price delta value.
Bullish Flux: Current bullish context score. Displayed as both a bar chart (visual) and numeric value. Brighter when bullish score dominates.
Bearish Flux: Current bearish context score. Same visualization as bullish flux. These scores compete - the winner determines signal direction.
Field: Trend direction based on EMA relationship. "Repulsive" (uptrend), "Attractive" (downtrend), "Neutral" (ranging). Icon: ⬆⬇↔
State: Current market condition:
🚀 EJECTION: Buy signal active
💥 COLLAPSE: Sell signal active
⚠ CRITICAL: Extreme event, no directional confirmation
● STABLE: Normal market conditions
HOW TO USE THE INDICATOR
1. Wait for Extreme Events:
The indicator is designed to be selective. Don't trade every fluctuation - wait for tensor to reach >90 or <10. This alone is not a signal.
2. Check Context Scores:
Look at the Bullish Flux vs Bearish Flux in the dashboard. If scores are close (within 1-2 points), the market is indecisive - skip the trade.
3. Confirm with Signals:
Only act when a full triangle signal appears (▲ or ▼). This means ALL your selected confirmation criteria have been met.
4. Use with Price Structure:
Combine with support/resistance levels. A buy signal AT support is higher probability than a buy signal in the middle of nowhere.
5. Respect the Dashboard State:
When State shows "CRITICAL" (⚠), it means extreme pressure exists but direction is unclear. These are the most dangerous moments - wait for resolution.
6. Volume Matters:
Energy particles (dots) and the Mass metric tell you if institutions are participating. Signals without volume confirmation are lower probability.
MARKET AND TIMEFRAME RECOMMENDATIONS
Scalping (1m-5m):
Lookback: 10-14
Smoothing: 5-7
Threshold: 85
Epsilon: 0.5-0.7
Note: Expect more noise. Confirm with Level 2 data. Best on highly liquid instruments.
Intraday (15m-1h):
Lookback: 20-30 (default settings work well)
Smoothing: 3-5
Threshold: 90
Epsilon: 1.0
Note: Sweet spot for the indicator. High win rate on liquid stocks, forex majors, and crypto.
Swing Trading (4h-1D):
Lookback: 30-50
Smoothing: 3
Threshold: 90-95
Epsilon: 1.5-2.0
Note: Signals are rare but high conviction. Combine with higher timeframe trend analysis.
Position Trading (1D-1W):
Lookback: 50-100
Smoothing: 5-7
Threshold: 95
Epsilon: 2.0-3.0
Note: Extremely rare signals. Only trade the most extreme events. Expect massive moves.
Market-Specific Settings:
Forex (EUR/USD, GBP/USD, etc.):
Volume data is unreliable (spot forex has no centralized volume)
Disable "Require Volume Confirmation"
Focus on momentum and trend filters
News events create extreme singularities
Best on 15m-1h timeframes
Stocks (High-Volume Equities):
Volume confirmation is CRITICAL - keep it ON
Works excellently on AAPL, TSLA, SPY, etc.
Morning session (9:30-11:00 ET) shows highest event density
Earnings announcements create guaranteed extreme events
Best on 5m-1h for day trading, 1D for swing trading
Crypto (BTC, ETH, major alts):
Reduce threshold to 85 (crypto has constant high volatility)
Volume spikes are THE primary signal - keep volume confirmation ON
Works exceptionally well due to 24/7 trading and high volatility
Epsilon can be reduced to 0.7-0.8 for more signals
Best on 15m-4h timeframes
Commodities (Gold, Oil, etc.):
Gold responds to macro events (Fed announcements, geopolitical events)
Oil responds to supply shocks
Use daily timeframe minimum
Increase lookback to 50+
These are slow-moving markets - be patient
Indices (SPX, NDX, etc.):
Institutional volume matters - keep volume confirmation ON
Opening hour (9:30-10:30 ET) = highest singularity probability
Strong correlation with VIX - high VIX = more extreme events
Best on 15m-1h for day trading
WHAT MAKES THIS INDICATOR UNIQUE
1. Post-Normalization Sensitivity Control:
Unlike most oscillators where sensitivity controls don't actually work (they're applied before normalization, which then rescales everything), FTS applies epsilon compression AFTER normalization. This means the sensitivity parameter genuinely affects signal frequency. This is a novel implementation not found in standard oscillators.
2. Multi-Factor Confluence Requirement:
The indicator doesn't just detect "overbought" or "oversold" - it detects extreme conditions AND THEN analyzes context through five separate factors (price structure, momentum, trend, acceleration, volume). Most indicators are single-factor; FTS requires confluence.
3. Volatility-Weighted Normalization:
By squaring the ATR ratio (local/global), the indicator adapts to changing market regimes. A 1% move in a low-volatility environment is treated differently than a 1% move in a high-volatility environment. Traditional indicators treat all moves equally regardless of context.
4. Volume Integration at the Core:
Volume isn't an afterthought or optional filter - it's baked into the fundamental equation as "mass." The log transformation handles outliers elegantly while preserving significance. Most price-based indicators completely ignore volume.
5. Adaptive Scoring System:
Rather than fixed buy/sell rules ("RSI >70 = sell"), FTS uses competitive scoring where bullish and bearish evidence compete. The winner determines direction. This solves the classic problem of "overbought markets can stay overbought during strong uptrends."
6. Comprehensive Visual Feedback:
The multi-layer visualization system (accretion disk, field lines, particles, flashes) provides instant intuitive feedback on market state without requiring dashboard reading. You can see pressure building before extreme thresholds are hit.
7. Separate Extreme Detection and Signal Generation:
"Singularity diamonds" show extreme events that don't meet full criteria, while "signal triangles" only appear when ALL conditions are met. This distinction helps traders understand when pressure exists versus when it's actionable.
COMPARISON TO EXISTING INDICATORS
vs. RSI/Stochastic:
These normalize price relative to recent range. FTS normalizes (price change × log volume × volatility ratio) - a composite metric, not just price position.
vs. Chaikin Money Flow:
CMF combines price and volume but lacks volatility context and doesn't use adaptive normalization or post-normalization compression.
vs. Bollinger Bands + Volume:
Bollinger Bands show volatility but don't integrate volume or create a unified oscillator. They're separate components, not synthesized.
vs. MACD:
MACD is pure momentum. FTS combines momentum with volume weighting and volatility context, plus provides a normalized 0-100 scale.
The specific combination of log-volume weighting, squared volatility amplification, post-normalization epsilon compression, and multi-factor directional scoring is unique to this indicator.
LIMITATIONS AND PROPER DISCLOSURE
Not a Holy Grail:
No indicator is perfect. This tool identifies high-probability setups but cannot predict the future. Losses will occur. Use proper risk management.
Requires Confirmation:
Best used in conjunction with price action analysis, support/resistance levels, and higher timeframe trend. Don't trade signals blindly.
Volume Data Dependency:
On forex (spot) and some low-volume instruments, volume data is unreliable or tick-volume only. Disable volume confirmation in these cases.
Lagging Components:
The EMA smoothing and trend filters are inherently lagging. In extremely fast moves, signals may appear after the initial thrust.
Extreme Event Rarity:
With conservative settings (high threshold, high epsilon), signals can be rare. This is by design - quality over quantity. If you need more frequent signals, reduce threshold to 85 and epsilon to 0.7.
Not Financial Advice:
This indicator is an analytical tool. All trading decisions and their consequences are solely your responsibility. Past performance does not guarantee future results.
BEST PRACTICES
Don't trade every singularity - wait for context confirmation
Higher timeframes = higher reliability
Combine with support/resistance for entry refinement
Volume confirmation is CRITICAL for stocks/crypto (toggle off only for forex)
During major news events, singularities are inevitable but direction may be uncertain - use wider stops
When bullish and bearish flux scores are close, skip the trade
Test settings on your specific instrument/timeframe before live trading
Use the dashboard actively - it contains critical diagnostic information
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
DEMA Flow [Alpha Extract]A sophisticated trend identification system that combines Double Exponential Moving Average methodology with advanced HL median filtering and ATR-based band detection for precise trend confirmation. Utilizing dual-layer smoothing architecture and volatility-adjusted breakout zones, this indicator delivers institutional-grade flow analysis with minimal lag while maintaining exceptional noise reduction. The system's intelligent band structure with asymmetric ATR multipliers provides clear trend state classification through price position analysis relative to dynamic threshold levels.
🔶 Advanced DEMA Calculation Engine
Implements double exponential moving average methodology using cascaded EMA calculations to significantly reduce lag compared to traditional moving averages. The system applies dual smoothing through sequential EMA processing, creating a responsive yet stable trend baseline that maintains sensitivity to genuine market structure changes while filtering short-term noise.
// Core DEMA Framework
dema(src, length) =>
EMA1 = ta.ema(src, length)
EMA2 = ta.ema(EMA1, length)
DEMA_Value = 2 * EMA1 - EMA2
DEMA_Value
// Primary Calculation
DEMA = dema(close, DEMA_Length)
2H
🔶 HL Median Filter Smoothing Architecture
Features sophisticated high-low median filtering using rolling window analysis to create ultra-smooth trend baselines with outlier resistance. The system constructs dynamic arrays of recent DEMA values, sorts them for median extraction, and handles both odd and even window lengths for optimal smoothing consistency across all market conditions.
// HL Median Filter Logic
hlMedian(src, length) =>
window = array.new_float()
for i = 0 to length - 1
array.push(window, src)
array.sort(window)
// Median Extraction
lenW = array.size(window)
median = lenW % 2 == 1 ?
array.get(window, lenW / 2) :
(array.get(window, lenW/2 - 1) + array.get(window, lenW/2)) / 2
// Smooth DEMA Calculation
Smooth_DEMA = hlMedian(DEMA_Value, HL_Filter_Length)
🔶 ATR Band Construction Framework
Implements volatility-adaptive band structure using Average True Range calculations with asymmetric multiplier configuration for optimal trend identification. The system creates upper and lower threshold bands around the smoothed DEMA baseline with configurable ATR multipliers, enabling precise trend state determination through price breakout analysis.
// ATR Band Calculation
atrBands(src, atr_length, upper_mult, lower_mult) =>
ATR = ta.atr(atr_length)
Upper_Band = src + upper_mult * ATR
Lower_Band = src - lower_mult * ATR
// Band Generation
= atrBands(Smooth_DEMA, ATR_Length, Upper_ATR_Mult, Lower_ATR_Mult)
15min
🔶 Intelligent Flow Signal Engine
Generates binary trend states through band breakout detection, transitioning to bullish flow when price exceeds upper band and bearish flow when price breaches lower band. The system maintains flow state persistence until opposing band breakout occurs, providing clear trend classification without whipsaw signals during normal volatility fluctuations.
🔶 Comprehensive Visual Architecture
Provides multi-dimensional flow visualization through color-coded DEMA line, trend-synchronized candle coloring, and bar color overlay for complete chart integration. The system uses institutional color scheme with neon green for bullish flow, neon red for bearish flow, and neutral gray for undefined states with configurable band visibility.
🔶 Asymmetric Band Configuration
Features intelligent asymmetric ATR multiplier system with default upper multiplier of 2.1 and lower multiplier of 1.5, optimizing for market dynamics where upside breakouts often require stronger momentum confirmation than downside breaks. This configuration reduces false signals while maintaining sensitivity to genuine flow changes.
🔶 Dual-Layer Smoothing Methodology
Combines DEMA's inherent lag reduction with HL median filtering to create exceptional smoothing without sacrificing responsiveness. The system first applies double exponential smoothing for initial noise reduction, then applies median filtering to eliminate outliers and create ultra-clean flow baseline suitable for high-frequency and institutional trading applications.
🔶 Alert Integration System
Features comprehensive alert framework for flow state transitions with customizable notifications for bullish and bearish flow confirmations. The system provides real-time alerts on crossover events with clear directional indicators and exchange/ticker integration for multi-symbol monitoring capabilities.
🔶 Performance Optimization Framework
Utilizes efficient array management with optimized median calculation algorithms and minimal variable overhead for smooth operation across all timeframes. The system includes intelligent bar indexing for median filter initialization and streamlined flow state tracking for consistent performance during extended analysis periods.
🔶 Why Choose DEMA Flow ?
This indicator delivers sophisticated flow identification through dual-layer smoothing architecture and volatility-adaptive band methodology. By combining DEMA's reduced-lag characteristics with HL median filtering and ATR-based breakout zones, it provides institutional-grade flow analysis with exceptional noise reduction and minimal false signals. The system's asymmetric band structure and comprehensive visual integration make it essential for traders seeking systematic trend-following approaches across cryptocurrency, forex, and equity markets with clear entry/exit signals and comprehensive alert capabilities for automated trading strategies.
X21The X21 Dynamic Trend Indicator is an adaptive moving average system that combines SMA, EMA, and TEMA to provide real-time trend identification with dynamic color coding. This indicator automatically adjusts its visual presentation based on market conditions, making trend recognition intuitive and immediate.
Key Components
1. TEMA21 (Triple Exponential Moving Average)
Yellow Line - The most responsive trend indicator in the system
Significantly reduces lag compared to traditional moving averages
Formula: TEMA = 3×EMA1 - 3×EMA2 + EMA3
Provides early signals for potential trend changes
Ideal for timing entries and exits with minimal delay
2. SMA21 (Simple Moving Average)
Green Line - Always displayed in green regardless of trend direction
21-period simple moving average of closing prices
Represents the baseline trend reference
Acts as the primary support/resistance level in the system
3. EMA21 (Exponential Moving Average)
Dynamic Color Line - Changes color based on trend strength
Dark Green (#159015): Confirmed uptrend (bullish conditions)
Red (#f50000): Downtrend or weak trend (bearish/neutral conditions)
More responsive than SMA21 due to exponential weighting
Provides faster reaction to recent price movements
4. Dynamic Fill Band (SMA21/EMA21 Envelope)
Color-Coded Zone between SMA21 and EMA21
Light Green (#15e915, 19% transparency): Uptrend zone
Light Red (#f50000, 19% transparency): Downtrend zone
Visualizes the strength and volatility of the current trend
Width of the band indicates trend momentum and volatility
Trend Detection LogicThe indicator uses a dual-confirmation system for trend identification:
Price Position: Close must be above SMA21
Trend Slope: SMA21 must be rising (SMA21 > SMA21 )
Both conditions must be met simultaneously for an uptrend confirmation.This conservative approach reduces false signals and ensures only h
Configurable 3MA with Crossover CloudThis script is a versatile and powerful enhancement of the classic triple moving average setup, designed to provide clear, at-a-glance insights into market trends and momentum shifts. It plots three moving averages on your chart and colors the area between the two shorter-term MAs, creating a visual "cloud" that instantly signals bullish or bearish sentiment.
The core of this indicator is its complete customizability, allowing you to tailor it precisely to your trading strategy and the asset you are analyzing.
Key Features:
Dynamic Crossover Cloud: The space between the first two moving averages is colored to represent momentum:
Green Cloud: Indicates a bullish crossover, where the shorter-term MA is above the medium-term MA.
Red Cloud: Indicates a bearish crossover, where the shorter-term MA is below the medium-term MA.
Complete Customization: Unlike standard MA indicators, every aspect of the three moving averages can be configured independently:
Length: Set the period for each MA.
Type: Choose between a Simple Moving Average (SMA) or an Exponential Moving Average (EMA) for each line.
Source: Base the calculation on any price source (close, open, high, low, hl2, etc.).
Individual Visibility Toggles: Clean up your chart by hiding any of the three moving averages directly from the settings panel.
How to Use:
This indicator is ideal for trend-following and crossover strategies.
Identify Momentum: Use the color of the cloud to quickly gauge short-term momentum. A green cloud suggests bullish strength, while a red cloud suggests bearish pressure.
Confirm the Trend: Use the third, long-term moving average (e.g., a 200-period MA) as a macro trend filter. For a higher probability trade, only consider long positions when the price is above the long-term MA and the cloud is green. Conversely, only consider short positions when the price is below the long-term MA and the cloud is red.
Customize for Your Style: Adjust the default settings (13 EMA, 50 SMA, 200 EMA) to fit your preferred timeframes and trading style, whether you're a scalper, day trader, or swing trader.
On-Balance Volume with Multiple MA TypesOn-Balance Volume with Multiple MA Types
English Description
Overview
This is the first version of the "On-Balance Volume with Multiple MA Types" indicator designed to overlay directly on the price chart, a significant evolution from its previous iterations, which functioned solely as an oscillator in a separate window. The indicator calculates On-Balance Volume (OBV) and applies various smoothing methods to provide a clear view of volume dynamics in relation to price movements. It is pinned to the price scale for seamless integration with the chart.
Interpretation Recommendations
Price Pushing the OBV Line from Below: When the price chart pushes the OBV line upward and remains below it, this indicates rising volume, suggesting strong buying pressure.
Price Above the OBV Line: When the price chart is above the OBV line, it signals falling volume, indicating weakening momentum or selling pressure.
OBV Line Crossings: When the price crosses the OBV line, it represents a balance point in volume dynamics. The price level at the current crossing can be compared to the previous crossing to assess changes in market sentiment or momentum.
Moving Average Types
The indicator offers eight smoothing options for the OBV line, each with unique characteristics:
EMA (Exponential Moving Average): A weighted average that prioritizes recent data, providing a smooth yet responsive line.
DEMA (Double Exponential Moving Average): Uses two EMAs to reduce lag, offering faster response to volume changes.
HMA (Hull Moving Average): Combines weighted moving averages to minimize lag while maintaining smoothness.
WMA (Weighted Moving Average): Assigns more weight to recent data, balancing responsiveness and noise reduction.
TMA (Triangular Moving Average): A double-smoothed simple moving average, emphasizing central data points for smoother output.
VIDYA (Variable Index Dynamic Average): Adapts smoothing based on market volatility, using a CMO (Chande Momentum Oscillator) for dynamic weighting. Controlled by the VIDYA Alpha parameter (default: 0.2, range: 0–1), which adjusts sensitivity to volatility.
FRAMA (Fractal Adaptive Moving Average): Adjusts smoothing based on fractal dimensions of the OBV data, adapting to market conditions.
JMA (Jurik Moving Average): A proprietary adaptive average designed for minimal lag and high smoothness. Controlled by two parameters:
JMA Phase (default: 50, range: -100 to 100): Adjusts the balance between responsiveness and smoothness.
JMA Power (default: 1, range: 0.1+): Controls the strength of smoothing.
Input Parameters
OBV MA Length (default: 10): The lookback period for smoothing the OBV. Higher values produce smoother results but increase lag.
OBV MA Type (default: JMA): Selects the moving average type from the eight options listed above.
Line Width (default: 2): Thickness of the OBV line on the chart.
Bullish Color (default: Blue): Color of the OBV line when rising (indicating increasing volume).
Bearish Color (default: Red): Color of the OBV line when falling (indicating decreasing volume).
JMA Phase (default: 50): Adjusts the JMA’s responsiveness (used only when JMA is selected).
JMA Power (default: 1): Adjusts the JMA’s smoothing strength (used only when JMA is selected).
VIDYA Alpha (default: 0.2): Controls the sensitivity of VIDYA to market volatility (used only when VIDYA is selected).
How to Use
Add the indicator to your TradingView chart. It will overlay directly on the price chart, aligned with the price scale.
Adjust the OBV MA Type to select your preferred smoothing method based on your trading style (e.g., JMA for low lag, TMA for smoothness).
Modify the OBV MA Length to balance responsiveness and noise reduction. Shorter periods (e.g., 5–10) are better for short-term trading, while longer periods (e.g., 20–50) suit longer-term analysis.
Use the Bullish Color and Bearish Color to visually distinguish rising and falling volume trends.
For JMA or VIDYA, fine-tune the JMA Phase, JMA Power, or VIDYA Alpha to optimize the indicator for specific market conditions.
Interpret the OBV line in relation to price:
Watch for price pushing the OBV line upward (rising volume) or moving above it (falling volume).
Note crossings of the OBV line to identify balance points and compare with prior crossings to gauge momentum shifts.
Combine with other technical tools (e.g., support/resistance levels, trendlines) for a comprehensive trading strategy.
Notes
This indicator is designed to work on any timeframe and market, but its effectiveness depends on the chosen moving average type and parameters.
Experiment with different MA types and lengths to find the best fit for your trading approach.
The indicator is licensed under the Mozilla Public License 2.0 and copyrighted by TradingStrategyCourses © 2025.
