RSI-Adaptive T3 [ChartPrime]The RSI-Adaptive T3 is a precision trend-following tool built around the legendary T3 smoothing algorithm developed by Tim Tillson , designed to enhance responsiveness while reducing lag compared to traditional moving averages. Current implementation takes it a step further by dynamically adapting the smoothing length based on real-time RSI conditions — allowing the T3 to “breathe” with market volatility. This dynamic length makes the curve faster in trending moves and smoother during consolidations.
To help traders visualize volatility and directional momentum, adaptive volatility bands are plotted around the T3 line, with visual crossover markers and a dynamic info panel on the chart. It’s ideal for identifying trend shifts, spotting momentum surges, and adapting strategy execution to the pace of the market.
HOIW IT WORKS
At its core, this indicator fuses two ideas:
The T3 Moving Average — a 6-stage recursively smoothed exponential average created by Tim Tillson , designed to reduce lag without sacrificing smoothness. It uses a volume factor to control curvature.
A Dynamic Length Engine — powered by the RSI. When RSI is low (market oversold), the T3 becomes shorter and more reactive. When RSI is high (overbought), the T3 becomes longer and smoother. This creates a feedback loop between price momentum and trend sensitivity.
// Step 1: Adaptive length via RSI
rsi = ta.rsi(src, rsiLen)
rsi_scale = 1 - rsi / 100
len = math.round(minLen + (maxLen - minLen) * rsi_scale)
pine_ema(src, length) =>
alpha = 2 / (length + 1)
sum = 0.0
sum := na(sum ) ? src : alpha * src + (1 - alpha) * nz(sum )
sum
// Step 2: T3 with adaptive length
e1 = pine_ema(src, len)
e2 = pine_ema(e1, len)
e3 = pine_ema(e2, len)
e4 = pine_ema(e3, len)
e5 = pine_ema(e4, len)
e6 = pine_ema(e5, len)
c1 = -v * v * v
c2 = 3 * v * v + 3 * v * v * v
c3 = -6 * v * v - 3 * v - 3 * v * v * v
c4 = 1 + 3 * v + v * v * v + 3 * v * v
t3 = c1 * e6 + c2 * e5 + c3 * e4 + c4 * e3
The result: an evolving trend line that adapts to market tempo in real-time.
KEY FEATURES
⯁ RSI-Based Adaptive Smoothing
The length of the T3 calculation dynamically adjusts between a Min Length and Max Length , based on the current RSI.
When RSI is low → the T3 shortens, tracking reversals faster.
When RSI is high → the T3 stretches, filtering out noise during euphoria phases.
Displayed length is shown in a floating table, colored on a gradient between min/max values.
⯁ T3 Calculation (Tim Tillson Method)
The script uses a 6-stage EMA cascade with a customizable Volume Factor (v) , as designed by Tillson (1998) .
Formula:
T3 = c1 * e6 + c2 * e5 + c3 * e4 + c4 * e3
This technique gives smoother yet faster curves than EMAs or DEMA/Triple EMA.
⯁ Visual Trend Direction & Transitions
The T3 line changes color dynamically:
Color Up (default: blue) → bullish curvature
Color Down (default: orange) → bearish curvature
Plot fill between T3 and delayed T3 creates a gradient ribbon to show momentum expansion/contraction.
Directional shift markers (“🞛”) are plotted when T3 crosses its own delayed value — helping traders spot trend flips or pullback entries.
⯁ Adaptive Volatility Bands
Optional upper/lower bands are plotted around the T3 line using a user-defined volatility window (default: 100).
Bands widen when volatility rises, and contract during compression — similar to Bollinger logic but centered on the adaptive T3.
Shaded band zones help frame breakout setups or mean-reversion zones.
⯁ Dynamic Info Table
A live stats panel shows:
Current adaptive length
Maximum smoothing (▲ MaxLen)
Minimum smoothing (▼ MinLen)
All values update in real time and are color-coded to match trend direction.
HOW TO USE
Use T3 crossovers to detect trend transitions, especially during periods of volatility compression.
Watch for volatility contraction in the bands — breakouts from narrow band periods often precede trend bursts.
The adaptive smoothing length can also be used to assess current market tempo — tighter = faster; wider = slower.
CONCLUSION
RSI-Adaptive T3 modernizes one of the most elegant smoothing algorithms in technical analysis with intelligent RSI responsiveness and built-in volatility bands. It gives traders a cleaner read on trend health, directional shifts, and expansion dynamics — all in a visually efficient package. Perfect for scalpers, swing traders, and algorithmic modelers alike, it delivers advanced logic in a plug-and-play format.
Bands
Commodity Trend Reactor [BigBeluga]
🔵 OVERVIEW
A dynamic trend-following oscillator built around the classic CCI, enhanced with intelligent price tracking and reversal signals.
Commodity Trend Reactor extends the traditional Commodity Channel Index (CCI) by integrating trend-trailing logic and reactive reversal markers. It visualizes trend direction using a trailing stop system and highlights potential exhaustion zones when CCI exceeds extreme thresholds. This dual-level system makes it ideal for both trend confirmation and mean-reversion alerts.
🔵 CONCEPTS
Based on the CCI (Commodity Channel Index) oscillator, which measures deviation from the average price.
Trend bias is determined by whether CCI is above or below user-defined thresholds.
Trailing price bands are used to lock in trend direction visually on the main chart.
Extreme values beyond ±200 are treated as potential reversal zones.
🔵 FEATURES\
CCI-Based Trend Shifts:
Triggers a bullish bias when CCI crosses above the upper threshold, and bearish when it crosses below the lower threshold.
Adaptive Trailing Stops:
In bullish mode, a trailing stop tracks the lowest price; in bearish mode, it tracks the highest.
Top & Bottom Markers:
When CCI surpasses +200 or drops below -200, it plots colored squares both on the oscillator and on price, marking potential reversal zones.
Background Highlights:
Each time a trend shift occurs, the background is softly colored (lime for bullish, orange for bearish) to highlight the change.
🔵 HOW TO USE
Use the oscillator to monitor when CCI crosses above or below threshold values to detect trend activation.
Enter trades in the direction of the trailing band once the trend bias is confirmed.
Watch for +200 and -200 square markers as warnings of potential mean reversals.
Use trailing stop areas as dynamic support/resistance to manage stop loss and exit strategies.
The background color changes offer clean confirmation of trend transitions on chart.
🔵 CONCLUSION
Commodity Trend Reactor transforms the simple CCI into a complete trend-reactive framework. With real-time trailing logic and clear reversal alerts, it serves both momentum traders and contrarian scalpers alike. Whether you’re trading breakouts or anticipating mean reversions, this indicator provides clarity and structure to your decision-making.
TCT - Envelope MatrixTCT - Envelope Matrix
A powerful multi-envelope indicator that creates a comprehensive price channel system with 4 customizable envelopes and multiple intermediate levels for precise price action analysis.
Key Features:
• 4 customizable envelopes with adjustable percentages (0.2%, 0.4%, 0.6%, 0.8% by default)
• Optional EMA or SMA basis calculation
• Color-coded bands for easy visual identification
• Automatic horizontal lines showing current band values
• Midpoint lines between adjacent bands
• Additional 25%, 50%, and 75% levels between each band pair
The indicator provides:
- Clear visual representation of price channels
- Multiple support and resistance levels
- Dynamic price boundaries that adapt to market conditions
- Enhanced precision with intermediate levels between bands
Perfect for:
• Identifying potential support and resistance zones
• Spotting overbought/oversold conditions
• Finding potential reversal points
• Analyzing price volatility and channel width
• Making informed trading decisions based on price position relative to multiple bands
Customization Options:
• Adjustable length for the basis calculation
• Choice between EMA and SMA
• Customizable colors for each envelope
• Flexible percentage settings for each band
• Optional basis line color adjustment
This indicator is particularly useful for traders who want to analyze price action within multiple dynamic channels and identify potential trading opportunities based on price interactions with various support and resistance levels.
True Range eXpansion🕯️ TRX — True Range eXpansion
Clean Candle Bodies · Volatility Bands · Adaptive Range Envelope System
Not your grandfather’s candles. Not your brokerage’s bands.
----------------------------------------------------
TRX begins with a simple concept: visualize the true range of every candle, without the noise of flickering wicks.
From there, it grows into a fully adaptive price visualization framework.
What started as a candle-only visualizer evolved into a modular, user-controlled price engine.
From wickless candle clarity to dynamic volatility envelopes, TRX adapts to you.
There are plenty of band and channel indicators out there — Bollinger, Keltner, Donchian, Envelope, the whole crew.
But none of them are built on the true candle range, adaptive ATR shaping, and full user control like TRX.
This isn’t just another indicator — it’s a new framework.
Most bands and channels are based on close price and statistical deviation — useful, but limited.
TRX uses the full true range of each candle as its foundation, then applies customizable smoothing and directional ATR scaling to form a dynamic, volatility-reactive envelope.
The result? Bands that breathe with the market — not lag behind it.
----------------------------------------------------
🔧 Core Features:
🕯️ True Range Candles — Each candle is plotted from low to high, body-only, colored by open/close.
📈 Adjustable High/Low Moving Averages — Select your smoothing style: SMA, EMA, WMA, RMA, or HMA.
🌬️ ATR-Based Expansion — Bands dynamically breathe based on market volatility.
🔀 Per-Band Multipliers — Fine-tune expansion individually for the upper and lower bands.
⚖️ Basis Line — Optional centerline between bands for structure tracking and equilibrium zones.
🎛️ Full Visual Control — Width, transparency, color, on/off toggles for each element.
----------------------------------------------------
🧠 Default Use Case:
With the included default settings, TRX behaves like an evolved Bollinger Band system — based on True Range candle structure, not just close price and standard deviation.
----------------------------------------------------
🔄 How to Zero Out the Bands (for Minimalist Use):
Want just candles? A clean MA? Single band? You got it.
➤ Use TRX like a clean moving average:
• Set ATR Multiplier to 0
• Set both Band ATR Adjustments to 0
• Leave the Basis Line ON or OFF — your call
➤ Show only candles (no bands at all):
• Turn off "Show High/Low MAs"
• Turn off Basis Line
➤ Single-line ceiling or floor tracking:
• Set one band’s Transparency to 100
• Use the remaining band as a price envelope or support/resistance guide
----------------------------------------------------
🧬 Notes:
TRX can be made:
• Spiky or silky (via smoothing & ATR)
• Wide or tight (via multipliers)
• Subtle or aggressive (via color/transparency)
• Clean as a compass or dirty as a chaos meter
Built by accident. Tuned with intention.
Released to the world as one of the most adaptable and expressive visual overlays ever made.
Created by Sherlock_MacGyver
Smooth Fibonacci BandsSmooth Fibonacci Bands
This indicator overlays adaptive Fibonacci bands on your chart, creating dynamic support and resistance zones based on price volatility. It combines a simple moving average with ATR-based Fibonacci levels to generate multiple bands that expand and contract with market conditions.
## Features
- Creates three pairs of upper and lower Fibonacci bands
- Smoothing option for cleaner, less noisy bands
- Fully customizable colors and line thickness
- Adapts automatically to changing market volatility
## Settings
Adjust the SMA and ATR lengths to match your trading timeframe. For short-term trading, try lower values; for longer-term analysis, use higher values. The Fibonacci factors determine how far each band extends from the center line - standard Fibonacci ratios (1.618, 2.618, and 4.236) are provided as defaults.
## Trading Applications
- Use band crossovers as potential entry and exit signals
- Look for price bouncing off bands as reversal opportunities
- Watch for price breaking through multiple bands as strong trend confirmation
- Identify potential support/resistance zones for placing stop losses or take profits
Fibonacci Bands combines the reliability of moving averages with the adaptability of ATR and the natural market harmony of Fibonacci ratios, offering a robust framework for both trend and range analysis.
Volume Flow OscillatorVolume Flow Oscillator
Overview
The Volume Flow Oscillator is an advanced technical analysis tool that measures buying and selling pressure by combining price direction with volume. Unlike traditional volume indicators, this oscillator reveals the force behind price movements, helping traders identify strong trends, potential reversals, and divergences between price and volume.
Reading the Indicator
The oscillator displays seven colored bands that fluctuate around a zero line:
Three bands above zero (yellow) indicate increasing levels of buying pressure
Three bands below zero (red) indicate increasing levels of selling pressure
The central band represents the baseline volume flow
Color intensity changes based on whether values are positive or negative
Trading Signals
The Volume Flow Oscillator provides several valuable trading signals:
Zero-line crossovers: When multiple bands cross from negative to positive, potential bullish shift; opposite for bearish
Divergences: When price makes new highs/lows but oscillator bands fail to confirm, signals potential reversal
Volume climax: Extreme readings where outer bands stretch far from zero often precede reversals
Trend confirmation: Strong expansion of bands in direction of price movement confirms genuine momentum
Support/resistance: During trends, bands may remain largely on one side of zero, showing continued directional pressure
Customization
Adjust these key parameters to optimize the oscillator for your trading style:
Lookback Length: Controls overall sensitivity (shorter = more responsive, longer = smoother)
Multipliers: Adjust sensitivity spread between bands for different market conditions
ALMA Settings: Fine-tune how the indicator weights recent versus historical data
VWMA Toggle: Enable for additional smoothing in volatile markets
Best Practices
For optimal results, use this oscillator in conjunction with price action and other confirmation indicators. The multi-band approach helps distinguish between minor fluctuations and significant volume events that might signal important market turns.
VolumeFlowOscillatorLibVolume Flow Oscillator Library
Overview
The Volume Flow Oscillator library provides a comprehensive framework for analyzing directional volume flow in financial markets. It creates a multi-band oscillator system that transforms price and volume data into a spectrum of sensitivity bands, revealing the underlying buying and selling pressure.
Technical Approach
The library combines price direction with trading volume to generate an oscillator that fluctuates around a zero line, with positive values indicating buying pressure and negative values showing selling pressure. Using sophisticated ALMA (Arnaud Legoux Moving Average) smoothing techniques with asymmetric sensitivity, the library creates seven distinct bands that help identify various intensity levels of volume flow.
Key Features
Multi-band oscillator system with seven sensitivity levels
Directional volume flow analysis combining price movement and volume
Zero-line oscillation showing the balance between buying and selling pressure
Asymmetric ALMA smoothing for different sensitivity on positive/negative bands
Customizable lookback periods and multipliers for fine-tuning
Color-coded visualization for intuitive chart reading
Applications
This library offers developers a versatile foundation for creating volume-based indicators that go beyond simple volume measurement to reveal the directional force behind market movements. Ideal for confirming price trends, detecting divergences, identifying volume climaxes, and assessing overall market strength.
PolyBand Convergence System (PBCS)PolyBand Convergence System (PBCS)
The PolyBand Convergence System (PBCS) is an advanced technical analysis indicator that combines multiple polynomial regressions with statistical bands to identify trend strength and potential reversal zones.
Key Features
Multi-Degree Polynomial Analysis: Combines 1st, 2nd, 3rd, and 4th degree polynomial regressions into a composite regression line
Adaptive Statistical Bands: Uses percentile-based bands enhanced with standard deviation multipliers
Asymmetric Volatility Measurement: Separately calculates upside and downside volatility for more accurate band placement
Smart Trend Detection: Identifies bullish, bearish, or neutral market conditions based on price position relative to bands
How It Works
PBCS creates a composite regression line from multiple polynomial fits to better capture the underlying price structure. This line is then surrounded by adaptive bands that represent statistical thresholds for price movement. When price breaks above the upper band, a bullish trend is signaled; when it breaks below the lower band, a bearish trend is indicated.
Customization Options
Regression Settings: Adjust source data, lookback period, and smoothing parameters
Percentile Controls: Fine-tune the statistical thresholds for upper and lower bands
Volatility Sensitivity: Modify standard deviation multipliers to control band width
Visual Preferences: Choose from multiple color schemes to match your trading platform
Disclaimer
This indicator is provided for educational and informational purposes only and does not constitute investment advice. Trading involves risk and may result in financial loss. Always perform your own research and consult with a qualified financial advisor before making any trading decisions.
Kernel Regression Bands SuiteMulti-Kernel Regression Bands
A versatile indicator that applies kernel regression smoothing to price data, then dynamically calculates upper and lower bands using a wide variety of deviation methods. This tool is designed to help traders identify trend direction, volatility, and potential reversal zones with customizable visual styles.
Key Features
Multiple Kernel Types: Choose from 17+ kernel regression styles (Gaussian, Laplace, Epanechnikov, etc.) for smoothing.
Flexible Band Calculation: Select from 12+ deviation types including Standard Deviation, Mean/Median Absolute Deviation, Exponential, True Range, Hull, Parabolic SAR, Quantile, and more.
Adaptive Bands: Bands are calculated around the kernel regression line, with a user-defined multiplier.
Signal Logic: Trend state is determined by crossovers/crossunders of price and bands, coloring the regression line and band fills accordingly.
Custom Color Modes: Six unique color palettes for visual clarity and personal preference.
Highly Customizable Inputs: Adjust kernel type, lookback, deviation method, band source, and more.
How to Use
Trend Identification: The regression line changes color based on the detected trend (up/down)
Volatility Zones: Bands expand/contract with volatility, helping spot breakouts or mean-reversion opportunities.
Visual Styling: Use color modes to match your chart theme or highlight specific market states.
Credits:
Kernel regression logic adapted from:
ChartPrime | Multi-Kernel-Regression-ChartPrime (Link in the script)
Disclaimer
This script is for educational and informational purposes only. Not financial advice. Use at your own risk.
Mean Reversion Bundle [ActiveQuants]The Mean Reversion Bundle indicator is a powerful and versatile toolkit designed for traders who specialize in mean reversion strategies . This comprehensive bundle integrates eight key technical indicators renowned for their ability to identify potential price reversals, overbought/oversold conditions, and market exhaustion points. By consolidating Moving Averages (Fast & Slow) , Bollinger Bands , RSI (with Divergence) , Stochastic , Keltner Channels , Standard Pivot Points , ATR , and the Choppiness Index into a single, efficient script, it significantly streamlines chart analysis and empowers robust strategy development.
This bundle operates on the core principle of mean reversion: prices tend to revert to their historical average or mean over time . The included indicators provide multiple perspectives to assess these potential turning points:
Dynamic Support/Resistance: Moving Averages, Bollinger Bands, Keltner Channels, Pivot Points.
Momentum Oscillators: RSI, Stochastic.
Overbought/Oversold Conditions: RSI, Stochastic, Bollinger Bands.
Volatility Assessment: ATR, Bollinger Bands, Keltner Channels.
Market Condition Filter: Choppiness Index (Range vs. Trend).
Reversal Signals: RSI Divergence, Bollinger Band recovery.
By enabling users to selectively activate, extensively customize, and visualize these tools ( often with multi-timeframe capabilities ), the Mean Reversion Bundle facilitates a nuanced and layered approach to identifying high-probability mean reversion setups.
█ KEY FEATURES
All-in-One Mean Reversion Suite: Access eight distinct mean reversion indicators within a single TradingView script slot, saving valuable indicator space.
Modular Design: Easily toggle each indicator (Fast MA, Slow MA, Bollinger Bands, RSI, Stochastic, Keltner Channels, Pivot Points, ATR, Choppiness Index) On or Off through the intuitive settings menu to tailor your analysis.
Deep Customization: Fine-tune a wide array of parameters for every indicator, including lengths, sources, MA types, colors, line styles, levels, and specific calculation methods to precisely match your trading strategy and the asset's characteristics.
Multi-Timeframe (MTF) Capability: Configure most indicator components to analyze data from a different timeframe than your main chart, providing crucial higher-level context for mean reversion signals (e.g., daily RSI on an hourly chart).
Integrated Alert System: Pre-built alert conditions for critical mean reversion events such as:
- Price Crossover/Crossunder (Fast MA)
- Price Crossover/Crossunder (Slow MA)
- Lower Bollinger Band Recovery
- Upper Bollinger Band Recovery
- Bullish RSI Divergence
- Bearish RSI Divergence
Set up these alerts directly through TradingView's alert creation dialog. (See section on "█ SETTING UP ALERTS " for more details).
Advanced MA & RSI Smoothing: Option to apply a secondary smoothing MA or even Bollinger Bands directly to the Fast MA, Slow MA, and RSI lines for refined signal generation.
Sophisticated Pivot Points Module: Includes multiple Pivot Point types (Traditional, Fibonacci, Woodie, Classic, DM, Camarilla) with flexible timeframes (Daily to Decennially) and dynamic drawing of historical levels.
RSI Divergence Detection: Automatically plots potential bullish and bearish divergences between price and the RSI, a classic reversal signal.
█ USER INPUTS
The settings panel is organized into distinct sections for each of the 8 core indicator components:
Fast MA & Slow MA: On/Off, MA Type, Source, Length, Color, Line Width, Smoothing Type (None, MA, or MA + BBs), Smoothing Length, BB StdDev (if smoothing with BBs), Timeframe, Wait TF Close.
Bollinger Bands: On/Off, Length, Basis MA Type, Source, StdDev Multiplier, Offset, Colors, Timeframe, Wait TF Close.
RSI: On/Off, Source, Length, Overbought/Middle/Oversold Levels, Color, Line Width, Smoothing Type (None, MA, or MA + BBs), Smoothing Length, BB StdDev (if smoothing with BBs), Plot Divergence, Divergence Lookback Left/Right, Timeframe, Wait TF Close.
Stochastic: On/Off, %K Length, %K Smoothing, %D Smoothing, Overbought/Middle/Oversold Levels, Colors, Timeframe, Wait TF Close.
Keltner Channels: On/Off, Length, Multiplier, Source, Use Exponential MA (for basis), Bands Style (ATR, TR, Range), ATR Length, Colors, Timeframe, Wait TF Close.
Pivot Points: On/Off, Type, Pivots Timeframe (Anchor), Number of Pivots Back, Use Daily-based Values, Show Labels, Show Prices, Labels Position, Line Width, Line Style, and individual color/visibility toggles for P, S1-S5, R1-R5.
ATR: On/Off, Length, Smoothing Type, Color, Timeframe, Wait TF Close.
Choppiness Index: On/Off, Length, Offset, Upper/Middle/Lower Band Levels, Color, Timeframe, Wait TF Close.
█ SETTING UP ALERTS
The Mean Reversion Bundle comes with several pre-configured alert conditions to notify you of potential trading opportunities. To set up an alert:
Click the " Alert " button (clock icon) on TradingView's right-hand toolbar or top panel.
In the " Condition " dropdown, select " Mean Reversion Bundle ".
A second dropdown will appear, allowing you to choose from the specific alert conditions built into the script (e.g., " Price Crossover (Fast MA) ", " Bullish RSI Divergence ", " Lower Bollinger Band Recovery ").
You can also create more complex alerts by selecting one of the indicator's plotted lines (e.g., " RSI ", " Stochastic %K ", " Bollinger Band Basis ") in the first condition box, then choosing a comparison (e.g., " Crossing Down ", " Greater Than "), and then selecting another value or plotted line from the indicator in the third box.
Choose your preferred " Trigger " option:
- " Only Once ": The alert triggers the first time the condition is met, even on an unclosed (intra-bar) candle. The alert then deactivates.
- " Once Per Bar Close ": (Recommended for most mean reversion signals) The alert triggers only after the current bar closes if the condition was true on that closed bar. This ensures signals are based on confirmed price action and allows the alert to re-trigger on subsequent bars if the condition remains true.
- Other options like " Once Per Bar " or " Once Per Minute " are also available for different needs.
Customize the alert name, message, and notification preferences.
Click " Create ".
█ STRATEGY EXAMPLES
The following examples are for illustrative purposes only to demonstrate how indicators in this bundle can be combined for mean reversion strategies. They are not financial advice. Always conduct thorough backtesting and research.
1. Bollinger Band Reversal with RSI Confirmation
Goal: Identify potential reversals when price touches an outer Bollinger Band and RSI shows overbought/oversold conditions.
Setup: Enable Bollinger Bands (e.g., 20,2), RSI (e.g., 14), and optionally the Choppiness Index.
Entry (Long):
- Price touches or briefly closes below the Lower Bollinger Band.
- RSI is in the oversold region (e.g., below 30) or shows bullish divergence.
- Optional Filter: Choppiness Index > 61.8 (indicating a ranging market favorable for BB mean reversion).
- Enter on a confirming candle (e.g., price closes back inside the Lower Band, or a bullish candle pattern forms).
Entry (Short): Reverse logic for Upper Bollinger Band and overbought RSI (e.g., above 70) or bearish divergence.
Management: Stop-loss beyond the recent swing low/high or a multiple of ATR. Target the Bollinger Band basis line or the opposite band.
2. Stochastic Oversold/Overbought with Pivot Point Support/Resistance
Goal: Trade bounces from key Pivot Point levels when confirmed by Stochastic extremes.
Setup: Enable Stochastic (e.g., 14,3,3), Pivot Points (e.g., Daily Traditional), and Fast MA (e.g., 9 EMA) for short-term trend context.
Entry (Long):
- Price approaches a significant Pivot Support level (S1, S2).
- Stochastic %K and %D lines are in the oversold region (e.g., below 20) and ideally show a bullish crossover (%K crosses above %D).
- Optional Filter: Price is above the Fast MA, or the Fast MA starts to slope up.
- Enter on signs of price rejection at the Pivot level.
Entry (Short): Reverse logic for Pivot Resistance levels (R1, R2) and overbought Stochastic (e.g., above 80) with a bearish crossover.
Management: Stop-loss below the Pivot Support (for longs) or above Pivot Resistance (for shorts). Target the next Pivot level or a fixed risk-reward ratio.
3. RSI Divergence at Keltner Channel Extremes
Goal: Capitalize on weakening momentum (divergence) as price tests the outer Keltner Channel bands.
Setup: Enable RSI (with Divergence plotting enabled), Keltner Channels (e.g., 20,2 EMA basis, ATR 10), and ATR (for stop placement).
Entry (Long):
- Price is testing or near the Lower Keltner Channel band.
- A Bullish RSI Divergence is plotted (price makes a lower low, but RSI makes a higher low).
- Enter once the divergence is confirmed and price shows signs of turning up.
Entry (Short):
- Price is testing or near the Upper Keltner Channel band.
- A Bearish RSI Divergence is plotted (price makes a higher high, but RSI makes a lower high).
- Enter once divergence is confirmed and price shows signs of turning down.
Management: Place stop-loss based on ATR (e.g., 1.5x ATR below entry for longs) or beyond the Keltner Channel. Target could be the Keltner basis line or a measured move.
█ CONCLUSION
The Mean Reversion Bundle offers a sophisticated yet user-friendly suite of tools essential for traders focusing on mean reversion. By consolidating these powerful indicators, providing extensive customization , multi-timeframe analysis , and integrated alerts , this bundle simplifies the analytical workflow and aids in the development of more robust and nuanced trading strategies. Whether identifying potential exhaustion points, confirming overbought/oversold conditions, or finding precise entry near dynamic support/resistance, this bundle is a versatile asset for your technical analysis toolkit.
█ IMPORTANT NOTES
⚠ Parameter Optimization: The default settings are starting points. Always adjust indicator parameters (lengths, multipliers, levels) based on the specific asset, its volatility, and the timeframe you are trading. Thorough backtesting is crucial.
⚠ Multi-Timeframe Dynamics: Using the " Timeframe " input can be very powerful. If " Wait TF Close " is enabled (default), signals from higher timeframes will only update upon the close of that higher timeframe bar. Disabling it may lead to signals changing intra-bar.
⚠ Confluence is Key: Avoid relying on a single indicator. The strength of this bundle lies in combining signals from multiple indicators to build a confluence case for a trade.
⚠ Chart Clarity: While many tools are available, only enable those pertinent to your current strategy to maintain a clear and actionable chart.
⚠ Signal Confirmation: Indicator signals are typically finalized on bar close. Be cautious when acting on intra-bar signals, as they can change before the bar is complete. Using " Once Per Bar Close " for alerts is generally recommended for mean reversion signals.
█ RISK DISCLAIMER
Trading involves a substantial risk of loss and is not suitable for all investors. The Mean Reversion Bundle indicator is provided for educational and informational purposes only . It does NOT constitute financial advice or a recommendation to buy or sell any asset. Indicator signals identify potential patterns based on historical data but do not guarantee future price movements or profitability. Always conduct your own thorough research, utilize multiple sources of information, and implement robust risk management practices before making any trading decisions. Past performance is not indicative of future results.
📊 Happy trading! 🚀
Savitzky Flow Bands [ChartPrime]An advanced trend-following tool that applies the Savitzky-Golay smoothing algorithm to price and dynamically adapts trend bands to visualize directional bias and trend strength.
savitzky_golay_filter_w_15_vectors(source) =>
float sum = 0.0
float polynomial = 0.0
float coefficients = array.new(16)
// Predefined 15 coefficients
for i = -4 to 4
coefficients.set(i + 4, i) // from -4 to 5
if i == 4
for j = 5 to -4
for g = 8 to 15
coefficients.set(g, j) // from 5 to -4
// Calculate normalization factor as the sum of absolute values of coefficients
float norm_factor = coefficients.sum()
// Loop through coefficients and calculate the weighted sum
for i = 0 to coefficients.size()-1
sum := sum + coefficients.get(i) * source
// Calculate the smoothed value
for i = 1 to length-1
polynomial := math.sum(sum / norm_factor, i) / i
polynomial
⯁ KEY FEATURES & HOW TO USE
Savitzky-Golay Filtered Line (Basis):
Smooths out price noise using the Savitzky-Golay method, offering a more refined trend path than traditional moving averages. This centerline acts as the trend anchor and visually changes color depending on its slope to reflect the active trend direction.
Dynamic Trend Bands (Upper/Lower):
Constructed from the filtered line with a dynamic offset based on recent price volatility (ATR). These bands shift based on price pressure and are locked once price closes beyond them.
Helpful for identifying breakout moments or exhaustion areas where reversals are likely.
Trend Direction Detection:
A directional signal is confirmed when price breaks and closes above the upper band (uptrend) or below the lower band (downtrend).
Provides a clear and systematic way to identify when a trend begins.
Trend Duration Counter (Visual Decay Line):
A fading overlay line shows how long a trend has been active since the last reversal. The longer the trend persists, the more transparent this extension becomes.
This visual fading effect helps traders anticipate potential trend exhaustion and prepare for reversals or take-profit zones.
Reversal Signals (Diamond Markers):
Diamond shapes are plotted at each market shift, allowing users to visually pinpoint when the trend has flipped.
These markers act as decision zones for entry, exit, or stop-loss adjustments based on directional flow changes.
Color-Based Bar and Candle Painting:
Candles are painted green in uptrends and orange in downtrends, providing an intuitive glance at trend state without needing to interpret numbers.
Helps users stay aligned with the trend visually and avoid counter-trend entries.
⯁ CONCLUSION
The Savitzky Flow Bands indicator offers a modernized, visually rich way to track trend shifts using a scientific smoothing method. With dynamic trend envelopes, color-coded cues, and visual markers, it equips traders with a structured framework to follow the market's flow and make data-driven decisions. Ideal for swing traders, momentum strategists, or any trader looking to trade in sync with the prevailing trend.
Moving Volume-Weighted Avg Price, % Channel, BBsThis script includes:
- Moving Volume-Weighted Average Price line.
- User-defined % band above and below, very useful for "breakout" signals, and mentally adjusting to the magnitude of price swings when viewing an automatic scale on the price axis.
- Volume-Weighted Bollinger Bands, which are more sensitive to volume.
More detail:
- This is like TV's basic VWAP in concept, except the major flaw in that is that it has reset periods that you can't override, and the volume is cumulative until the next hard reset. The 'reset' is OK for securities trading, that resets every day anyway. But not for crypto - and not if/when securities trading goes 24/7. Also, the denominator accumulating over the entire period is also *not* OK, because then what is shown means something different as the day progresses - which kind of makes it useless. In other words, it starts out very sensitive to volume, and gets progressively more numb to it as they day progresses, and starts flattening out.
- This fixes both problems, by using a user-definable moving window for the average. Essentially combining SMA with volume-weighting.
- You may also find an invaluable trading aid, in the % bands above and below.
- What can optionally be shown is standard deviation bands, aka Bollinger bands. The advantage over regular BB is that it's volume-weighted. Since it is already calculated on a moving average, the period for the standard deviation has been shortened by default, and the magnitude increased, to better approximate regular Bollinger Bands - but it's still more responsive to volume.
ZenAlgo - AvengerThe ZenAlgo - Avenger indicator provides a multi-layered view of market behavior by combining volume delta analytics, trend-following EMAs, average price comparison, and price-volume profiling into a unified overlay. It is designed to visually assist traders in identifying areas of interest, momentum shifts, and potential reversals using cumulative data from both spot and perpetual markets.
Volume Delta Calculation
This indicator computes delta as the difference between estimated buy and sell volumes using volume data from multiple centralized exchanges. It distinguishes between spot and perpetual volumes, combining them into total volume.
To estimate buying and selling volume from raw volume data, candle structure is broken down into body and wicks. The body is interpreted as the core directional movement (buy/sell), while the wicks are treated as uncertain or counteraction. This segmentation helps infer the likely share of buying and selling within each bar.
The delta is calculated per bar and then aggregated over a lookback period (default 14 bars) to generate a cumulative delta. This approach provides a smoothed value of volume pressure trends over time.
A moving average is applied to the delta values (using selectable MA types like EMA or SMA) to define signal crossovers and suppress noise.
Delta Visualization
To contextualize delta within price action, the delta is scaled dynamically (by ATR or user-defined value) and plotted as a band around the closing price. Positive delta expands upward from price, negative delta downward. This provides a visual overlay that reflects net market pressure in context with price movement.
In cases of extreme delta (threshold set at 80% of recent maximum), the indicator marks spike bars using symbols to indicate significant directional pressure.
Identification of Noteworthy Conditions
The indicator highlights points on the chart where specific conditions are met based on the interaction between volume delta and its moving average. These conditions may align with moments of market pressure imbalance and directional movement, but they are not to be interpreted as trade signals in isolation.
Instead, these chart markers serve as visual flags for potential interest. They are intended to draw the user’s attention to scenarios where:
The delta crosses above or below its moving average, suggesting a potential shift in volume pressure.
The cumulative delta supports the direction of this crossover.
Optional filters can further restrict these markings to periods where:
The short-term trend (as inferred from EMA slope) supports the direction.
Volume is elevated relative to a recent average.
A user-defined cooldown period prevents multiple markings within short succession to avoid clutter.
It is essential to underscore that these markers do not constitute buy or sell advice . Their role is diagnostic , helping the trader to identify potential moments of interest which should be analyzed in conjunction with broader context, such as trend structure, price action, support/resistance levels, or external market data.
EMA Structure
Six EMAs with fixed lengths (13 to 56) are plotted and colored dynamically based on the most recent crossover between the fastest and slowest (EMA1 and EMA6). These EMAs help visualize short- to mid-term trends. The crossover itself is marked with symbols, with vertical offset based on ATR to maintain chart readability.
Average Line (AVG)
The indicator also calculates an average price based on a fixed window (100 bars). This is not a standard moving average but rather a raw average of recent prices stored in a circular buffer. The average is plotted, and its relative distance to the current price is labeled as a percentage. This feature serves as a simplified representation of fair value or mean reversion anchor.
EMA6 vs AVG Cross
Another layer of point of interest detection involves EMA6 crossing the AVG line. This crossover is only considered valid if EMA6 shows slope consistency in the crossing direction. These events are marked using symbols and offset vertically to avoid overlapping price action.
Divergence Detection
The script detects both regular and hidden divergences between price and delta:
Regular divergences are defined when price makes a higher high or lower low, while delta fails to confirm (makes a lower high or higher low).
Hidden divergences occur when price retraces (lower high or higher low), but delta moves against this retracement, indicating underlying strength or weakness.
Divergence points are labeled with "R" (regular) or "H" (hidden) and appear at local pivot highs or lows. The number of visible divergence labels can be limited for chart clarity.
POC and nPOC Calculations
The script includes a simplified volume profile implementation, calculating:
POC (Point of Control): the price level with the highest volume for the given period.
nPOC (non-tested POC): historical POCs that have not yet been revisited by price.
Price levels are bucketed into rows (user-defined), and volume per bucket is tracked to identify the POC. Upon a new period (e.g., day, week), a horizontal POC line is drawn. Once tested by price, the line’s appearance changes (color fades, label shrinks), helping users distinguish between untouched and touched levels.
Limits are enforced on the number of retained POCs and their maximum distance from current bars to optimize performance and chart readability.
Exchange Aggregation
Volume data is aggregated across major exchanges. This ensures that the delta calculation captures a broader market picture beyond a single venue, reducing exchange-specific noise.
How to Interpret Values
Delta Band: Wide bands indicate strong directional imbalance. Narrow bands suggest indecision or low volume.
EMA Crossover Symbols: Appear on directional shifts in moving averages. Multiple EMAs reinforcing the same slope typically indicate stronger trend.
AVG Line: Represents average price over recent history. Large deviations can indicate overextension or potential mean reversion.
Divergences: Regular ones may point to weakening momentum; hidden ones can suggest continuation despite corrective price action.
POC / nPOC: Key volume-based support/resistance levels. Untested nPOCs can act as magnets for price retests.
How to Best Use This Indicator
Use in conjunction with trend context (e.g., higher timeframe EMAs) to avoid counter-trend indications.
Treat delta spikes as caution zones—especially if they occur at known support/resistance.
Watch for divergences as early warning signs before price reverses.
Use POC/nPOC as target levels, especially if aligned with delta signals.
Apply volume and trend filters to reduce noise on shorter timeframes.
Added Value
Multi-exchange volume aggregation makes the delta calculation more robust.
Real-time cumulative delta overlaid directly on the price chart provides immediate context.
Points of interest on chart are conservative and filterable, intended to reduce false positives.
The combination of delta, trend-following EMAs, fair value line, and volume profile data is rarely found in one overlay script.
POC/nPOC visualization based on real traded volume helps identify high-interest zones for future price interaction.
Why Is It Worth Paying For
While free alternatives may provide partial insights (e.g., basic delta or single EMA crossovers), this indicator integrates multiple domains—delta, divergence, average price, trend overlays, and profile levels—into a coherent, optimized chart tool. The value lies not just in having these tools, but in how they are synchronized and visualized.
Furthermore, sourcing and synchronizing volume data from multiple exchanges for delta estimation is not straightforward in Pine Script and adds to the indicator's complexity and utility.
Disclaimers and Limitations
Delta estimation is based on candle structure and assumes wick/body distribution reflects buyer/seller activity, which may not always be precise.
Multi-exchange volume data relies on availability via TradingView’s request.security() function; if exchange data is missing or delayed, results may be incomplete.
Divergences do not guarantee reversals—should be used as part of a broader analysis framework.
On illiquid instruments or exotic pairs, the value of delta and volume-based analytics may be reduced due to unreliable volume.
Trend Classifier [ChartPrime]Trend Classifier
This is a multi-level trend classification tool that detects bullish, bearish, and ranging conditions using an adaptive smoothing method. It highlights trend strength through color-coded candles and layered bands, making it easy to interpret market momentum visually.
⯁ KEY FEATURES
Classifies trend strength using 3 bullish and 3 bearish levels relative to an adaptive trend line.
Neutral (range) zones are marked when price stays between key bands, often signaling low volatility or consolidation.
Automatically filters band visibility based on current trend direction:
In uptrends, only levels below the price are displayed.
In downtrends, only levels above the price are shown.
Color-coded candles:
Aqua candles for bullish conditions.
Red candles for bearish conditions.
Orange candles during neutral or ranging conditions.
Includes a trend direction change marker (diamond), plotted when a shift in trend is detected.
Plots a central smoothed trend line to anchor the trend bands dynamically.
Displays a trend strength dashboard in the top-right corner with real-time bull and bear scores (0 to 3).
Labels with arrows (▲/▼) show current trend direction and strength on the chart.
⯁ HOW TO USE
Use bull and bear levels (1–3) to assess the momentum of the current trend.
When bull = 0 and bear = 0 , market is considered ranging or consolidating – consider fading or waiting for breakout confirmation.
Trend bands can be used as dynamic support/resistance during trending phases.
Monitor the trend change diamonds to spot potential early reversals.
Combine with volume or oscillator tools for confirmation of strength shifts.
⯁ CONCLUSION
Trend Classifier helps traders stay aligned with the dominant trend while visually breaking down market momentum into levels. Its clean color-coded design and strength dashboard make it ideal for both trend following and range trading strategies.
Dynamic Trend Bands [ChartPrime]The Dynamic Trend Bands is a versatile trend-following indicator that uses a double-smoothed Hull Moving Average (HMA) to detect market trends, combined with dynamic bands that provide insight into potential momentum shifts and volatility-based price zones.
⯁ KEY FEATURES
Double HMA Trend Filter
Utilizes a double-smoothed HMA for a smoother and more responsive trend line, reducing noise while highlighting clear market trends.
float base = ta.hma(ta.hma(close, length - 10), length)
Dynamic Volatility Bands
Plots upper and lower bands based on volatility, positioned above the price in a downtrend and below the price in an uptrend.
Momentum Shift Detection
Highlights bars in orange when a potential momentum shift occurs:
- During a downtrend, if the high breaks above the upper band.
- During an uptrend, if the low breaks below the lower band.
Customizable Band Appearance
Users can adjust the size, distance, and colors of the bands, as well as choose whether to display the mid-band line and fill the area between bands.
Timeframe Flexibility
Allows selection of different calculation timeframes, enabling traders to adapt the indicator to various trading strategies.
⯁ HOW TO USE
Identify Trend Direction
Use the double HMA line to confirm the prevailing trend:
- Above the bands: downtrend.
- Below the bands: uptrend.
Spot Potential Momentum Shifts
Watch for orange-highlighted bars signaling potential reversals or weakening trends.
Optimize Entries and Exits
Enter trades on trend continuation signals while using band breaks to spot potential reversal zones.
Customize to Fit Your Strategy
Adjust the bands’ size, distance, and calculation timeframe to suit scalping, swing, or position trading.
⯁ CONCLUSION
The Dynamic Trend Bands is an all-in-one tool that helps traders assess trend strength, detect momentum shifts, and identify key price zones. Its customizable features make it adaptable for various trading styles and market conditions.
HL2 Moving Average with BandsThis indicator is designed to assist traders in identifying potential trade entries and exits for S&P 500 (ES) and Nasdaq-100 (NQ) futures. It calculates a Simple Moving Average (SMA) based on the HL2 value (average of high and low prices) of the current candle over a user-defined lookback period (default: 200 periods). The indicator plots this SMA as a blue line, providing a smoothed reference for price trends.
Additionally, it includes upper and lower bands calculated as a percentage (default: 0.5%) above and below the SMA, plotted as green and red lines, respectively. These bands act as dynamic thresholds to identify overbought or oversold conditions. The indicator generates trade signals based on price action relative to these bands:
Long Entry: A green upward triangle is plotted below the candle when the close crosses above the upper band, signaling a potential buy.
Close Long: A red square is plotted above the candle when the close crosses back below the upper band, indicating an exit for the long position.
Short Entry: A red downward triangle is plotted above the candle when the close crosses below the lower band, signaling a potential sell.
Close Short: A green square is plotted below the candle when the close crosses back above the lower band, indicating an exit for the short position.
The script is customizable, allowing users to adjust the SMA length and band percentage to suit their trading style or market conditions. It is plotted as an overlay on the price chart for easy integration with other technical analysis tools.
Recommended Time Frame and Settings for Trading S&P 500 and Nasdaq-100 Futures
Based on research and market dynamics for S&P 500 (ES) and Nasdaq-100 (NQ) futures, the 5-minute chart is recommended as the optimal time frame for day trading with this indicator. This time frame strikes a balance between capturing intraday trends and filtering out excessive noise, which is critical for futures trading due to their high volatility and leverage. The 5-minute chart aligns well with periods of high liquidity and volatility, such as the U.S. market open (9:30 AM–11:00 AM EST) and the afternoon session (2:00 PM–4:00 PM EST), when institutional traders are most active.
Why 5-minute? It allows traders to react to short-term price movements while avoiding the rapid fluctuations of 1-minute charts, which can be prone to false signals in choppy markets. It also provides enough data points to make the SMA and bands meaningful without the lag associated with longer time frames like 15-minute or hourly charts.
Recommended Settings
SMA Length: Set to 200 periods. This longer lookback period smooths the HL2 data, reducing noise and providing a reliable trend reference for the 5-minute chart. A 200-period SMA helps identify significant trend shifts without being overly sensitive to minor price fluctuations.
Band Percentage: 0.5% is more suitable for the volatility of ES and NQ futures on a 5-minute chart, as it generates fewer but higher-probability signals. Wider bands (e.g., 1%) may miss short-term opportunities, while narrower bands (e.g., 0.1%) may produce excessive false signals.
Trading Session Recommendations
Futures markets for ES and NQ are open nearly 24 hours (Sunday 6:00 PM EST to Friday 5:00 PM EST, with a daily break from 4:00 PM–5:00 PM EST), but not all hours are equally optimal due to varying liquidity and volatility. The best times to trade with this indicator are:
U.S. Market Open (9:30 AM–11:00 AM EST): This period is characterized by high volume and volatility, driven by the opening of U.S. equity markets and economic data releases (e.g., 8:30 AM EST reports like CPI or GDP). The indicator’s signals are more reliable during this window due to strong order flow and price momentum.
Afternoon Session (2:00 PM–4:00 PM EST): After the lunchtime lull, volume picks up as institutional traders return, and news or FOMC announcements often drive price action. The indicator can capture breakout moves as prices test the upper or lower bands.
Pre-Market (7:30 AM–9:30 AM EST): For traders comfortable with lower liquidity, this period can offer opportunities, especially around 8:30 AM EST economic releases. However, use tighter risk management due to wider spreads and potential volatility spikes.
Additional Tips
Avoid Low-Volume Periods: Steer clear of trading during low-liquidity hours, such as the overnight session (11:00 PM–3:00 AM EST), when spreads widen and price movements can be erratic, leading to false signals from the indicator.
Combine with Other Tools: Enhance the indicator’s effectiveness by pairing it with support/resistance levels, Fibonacci retracements, or volume analysis to confirm signals. For example, a long entry signal above the upper band is stronger if it coincides with a breakout above a key resistance level.
Risk Management: Given the leverage in futures (e.g., Micro E-mini contracts require ~$1,200 margin for ES), use tight stop-losses (e.g., below the lower band for longs or above the upper band for shorts) to manage risk. Aim for a risk-reward ratio of at least 1:2.
Test Settings: Backtest the indicator on a demo account to optimize the SMA length and band percentage for your specific trading style and risk tolerance. Micro E-mini contracts (MES for S&P 500, MNQ for Nasdaq-100) are ideal for testing due to their lower capital requirements.
Why These Settings and Time Frame?
The 5-minute chart with a 200-period SMA and 0.5% bands is tailored for the volatility and liquidity of ES and NQ futures during peak trading hours. The longer SMA period ensures the indicator captures meaningful trends, while the 0.5% bands are tight enough to signal actionable breakouts but wide enough to avoid excessive whipsaws. Trading during high-volume sessions maximizes the likelihood of valid signals, as institutional participation drives clearer price action.
By focusing on these settings and time frames, traders can leverage the indicator to capitalize on the dynamic price movements of S&P 500 and Nasdaq-100 futures while managing the inherent risks of these markets.
TrendWave Bands [BigBeluga]This is a trend-following indicator that dynamically adapts to market trends using upper and lower bands. It visually highlights trend strength and duration through color intensity while providing additional wave bands for deeper trend analysis.
🔵Key Features:
Adaptive Trend Bands:
➣ Displays a lower band in uptrends and an upper band in downtrends to indicate trend direction.
➣ The bands act as dynamic support and resistance levels, helping traders identify potential entry and exit points.
Wave Bands for Additional Analysis:
➣ A dashed wave band appears opposite the main trend band for deeper trend confirmation.
➣ In an uptrend, the upper dashed wave band helps analyze momentum, while in a downtrend, the lower dashed wave band serves the same purpose.
Gradient Color Intensity:
➣ The trend bands have a color gradient that fades as the trend continues, helping traders visualize trend duration.
➣ The wave bands have an inverse gradient effect—starting with low intensity at the trend's beginning and increasing in intensity as the trend progresses.
Trend Change Signals:
➣ Circular markers appear at trend reversals, providing clear entry and exit points.
➣ These signals mark transitions between bullish and bearish phases based on price action.
🔵Usage:
Trend Following: Use the lower band for confirmation in uptrends and the upper band in downtrends to stay on the right side of the market.
Trend Duration Analysis: Gradient wavebands give an idea of the duration of the current trend — new trends will have high-intensity colored wavebands and as time goes on, trends will fade.
Trend Reversal Detection: Circular markers highlight trend shifts, making it easier to spot entry and exit opportunities.
Volatility Awareness: Volatility-based bands help traders adjust their strategies based on market volatility, ensuring better risk management.
TrendWave Bands is a powerful tool for traders seeking to follow market trends with enhanced visual clarity. By combining trend bands, wave bands, and gradient-based color scaling, it provides a detailed view of market dynamics and trend evolution.
LinearRegressionLibrary "LinearRegression"
Calculates a variety of linear regression and deviation types, with optional emphasis weighting. Additionally, multiple of slope and Pearson’s R calculations.
calcSlope(_src, _len, _condition)
Calculates the slope of a linear regression over the specified length.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The length of the lookback period for the linear regression.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast for efficiency.
Returns: (float) The slope of the linear regression.
calcReg(_src, _len, _condition)
Calculates a basic linear regression, returning y1, y2, slope, and average.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) An array of 4 values: .
calcRegStandard(_src, _len, _emphasis, _condition)
Calculates an Standard linear regression with optional emphasis.
Parameters:
_src (float) : (series float) The source data series.
_len (int) : (int) The length of the lookback period.
_emphasis (float) : (float) The emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRegRidge(_src, _len, lambda, _emphasis, _condition)
Calculates a ridge regression with optional emphasis.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
lambda (float) : (float) The ridge regularization parameter.
_emphasis (float) : (float) The emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRegLasso(_src, _len, lambda, _emphasis, _condition)
Calculates a Lasso regression with optional emphasis.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
lambda (float) : (float) The Lasso regularization parameter.
_emphasis (float) : (float) The emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcElasticNetLinReg(_src, _len, lambda1, lambda2, _emphasis, _condition)
Calculates an Elastic Net regression with optional emphasis.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
lambda1 (float) : (float) L1 regularization parameter (Lasso).
lambda2 (float) : (float) L2 regularization parameter (Ridge).
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRegHuber(_src, _len, delta, iterations, _emphasis, _condition)
Calculates a Huber regression using Iteratively Reweighted Least Squares (IRLS).
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
delta (float) : (float) Huber threshold parameter.
iterations (int) : (int) Number of IRLS iterations.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRegLAD(_src, _len, iterations, _emphasis, _condition)
Calculates a Least Absolute Deviations (LAD) regression via IRLS.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
iterations (int) : (int) Number of IRLS iterations for LAD.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRegBayesian(_src, _len, priorMean, priorSpan, sigma, _emphasis, _condition)
Calculates a Bayesian linear regression with optional emphasis.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
priorMean (float) : (float) The prior mean for the slope.
priorSpan (float) : (float) The prior variance (or span) for the slope.
sigma (float) : (float) The assumed standard deviation of residuals.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRFromLinReg(_src, _len, _slope, _average, _y1, _condition)
Calculates the Pearson correlation coefficient (R) based on linear regression parameters.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_average (float) : (float) The average value of the source data series.
_y1 (float) : (float) The starting point (y-intercept of the oldest bar) for the linear regression.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast for efficiency.
Returns: (float) The Pearson correlation coefficient (R) adjusted for the direction of the slope.
calcRFromSource(_src, _len, _condition)
Calculates the correlation coefficient (R) using a specified length and source data.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The length of the lookback period.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast for efficiency.
Returns: (float) The correlation coefficient (R).
calcSlopeLengthZero(_src, _len, _minLen, _step, _condition)
Identifies the length at which the slope is flattest (closest to zero).
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length to consider (minimum of 2).
_minLen (int) : (int) The minimum length to start from (cannot exceed the max length).
_step (int) : (int) The increment step for lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length at which the slope is flattest.
calcSlopeLengthHighest(_src, _len, _minLen, _step, _condition)
Identifies the length at which the slope is highest.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length at which the slope is highest.
calcSlopeLengthLowest(_src, _len, _minLen, _step, _condition)
Identifies the length at which the slope is lowest.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length at which the slope is lowest.
calcSlopeLengthAbsolute(_src, _len, _minLen, _step, _condition)
Identifies the length at which the absolute slope value is highest.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length at which the absolute slope value is highest.
calcRLengthZero(_src, _len, _minLen, _step, _condition)
Identifies the length with the lowest absolute R value.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length with the lowest absolute R value.
calcRLengthHighest(_src, _len, _minLen, _step, _condition)
Identifies the length with the highest R value.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length with the highest R value.
calcRLengthLowest(_src, _len, _minLen, _step, _condition)
Identifies the length with the lowest R value.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length with the lowest R value.
calcRLengthAbsolute(_src, _len, _minLen, _step, _condition)
Identifies the length with the highest absolute R value.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length with the highest absolute R value.
calcDevReverse(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates the regressive linear deviation in reverse order, with optional emphasis on recent data.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The y-intercept (oldest bar) of the linear regression.
_inputDev (float) : (float) The input deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevForward(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates the progressive linear deviation in forward order (oldest to most recent bar), with optional emphasis.
Parameters:
_src (float) : (float) The source data array, where _src is oldest and _src is most recent.
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The y-intercept of the linear regression (value at the most recent bar, adjusted by slope).
_inputDev (float) : (float) The input deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevBalanced(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates the balanced linear deviation with optional emphasis on recent or older data.
Parameters:
_src (float) : (float) Source data array, where _src is the most recent and _src is the oldest.
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The y-intercept of the linear regression (value at the oldest bar).
_inputDev (float) : (float) The input deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevMean(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates the mean absolute deviation from a forward-applied linear trend (oldest to most recent), with optional emphasis.
Parameters:
_src (float) : (float) The source data array, where _src is the most recent and _src is the oldest.
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The y-intercept (oldest bar) of the linear regression.
_inputDev (float) : (float) The input deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevMedian(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates the median absolute deviation with optional emphasis on recent data.
Parameters:
_src (float) : (float) The source data array (index 0 = oldest, index _len - 1 = most recent).
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The y-intercept (oldest bar) of the linear regression.
_inputDev (float) : (float) The deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns:
calcDevPercent(_y1, _inputDev, _condition)
Calculates the percent deviation from a given value and a specified percentage.
Parameters:
_y1 (float) : (float) The base value from which to calculate deviation.
_inputDev (float) : (float) The deviation percentage.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevFitted(_len, _slope, _y1, _emphasis, _condition)
Calculates the weighted fitted deviation based on high and low series data, showing max deviation, with optional emphasis.
Parameters:
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The Y-intercept (oldest bar) of the linear regression.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevATR(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates an ATR-style deviation with optional emphasis on recent data.
Parameters:
_src (float) : (float) The source data (typically close).
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The Y-intercept (oldest bar) of the linear regression.
_inputDev (float) : (float) The input deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcPricePositionPercent(_top, _bot, _src)
Calculates the percent position of a price within a linear regression channel. Top=100%, Bottom=0%.
Parameters:
_top (float) : (float) The top (positive) deviation, corresponding to 100%.
_bot (float) : (float) The bottom (negative) deviation, corresponding to 0%.
_src (float) : (float) The source price.
Returns: (float) The percent position within the channel.
plotLinReg(_len, _y1, _y2, _slope, _devTop, _devBot, _scaleTypeLog, _lineWidth, _extendLines, _channelStyle, _colorFill, _colUpLine, _colDnLine, _colUpFill, _colDnFill)
Plots the linear regression line and its deviations, with configurable styles and fill.
Parameters:
_len (int) : (int) The lookback period for the linear regression.
_y1 (float) : (float) The starting y-value of the regression line.
_y2 (float) : (float) The ending y-value of the regression line.
_slope (float) : (float) The slope of the regression line (used to determine line color).
_devTop (float) : (float) The top deviation to add to the line.
_devBot (float) : (float) The bottom deviation to subtract from the line.
_scaleTypeLog (bool) : (bool) Use a log scale if true; otherwise, linear scale.
_lineWidth (int) : (int) The width of the plotted lines.
_extendLines (string) : (string) How lines should extend (none, left, right, both).
_channelStyle (string) : (string) The style of the channel lines (solid, dashed, dotted).
_colorFill (bool) : (bool) Whether to fill the space between the top and bottom deviation lines.
_colUpLine (color) : (color) Line color when slope is positive.
_colDnLine (color) : (color) Line color when slope is negative.
_colUpFill (color) : (color) Fill color when slope is positive.
_colDnFill (color) : (color) Fill color when slope is negative.
Dynamic Heat Levels [BigBeluga]This indicator visualizes dynamic support and resistance levels with an adaptive heatmap effect. It helps traders identify key price interaction zones and potential mean reversion opportunities by displaying multiple levels that react to price movement.
🔵Key Features:
Multi-Level Heatmap Channel:
- The indicator plots multiple dynamic levels forming a structured channel.
- Each level represents a historical price interaction zone, helping traders identify critical areas.
- The channel expands or contracts based on market conditions, adapting dynamically to price movements.
Heatmap-Based Strength Indication:
- Levels change in transparency and color intensity based on price interactions for the length period .
- The more frequently price interacts with a level, the more visible and intense the color becomes.
- When a level reaches a threshold (count > 10), it starts to turn red, signaling a high-heat zone with significant price activity.
🔵Usage:
Support & Resistance Analysis: Identify price levels where the market frequently interacts, making them strong areas for trade decisions.
Heatmap Strength Assessment: More intense red levels indicate areas with heavy price activity, useful for detecting key liquidity zones.
Dynamic Heat Levels is a powerful tool for traders looking to analyze price interaction zones with a heatmap effect. It offers a structured visualization of market dynamics, allowing traders to gauge the significance of key levels and detect mean reversion setups effectively.
Lowess Channel + (RSI) [ChartPrime]The Lowess Channel + (RSI) indicator applies the LOWESS (Locally Weighted Scatterplot Smoothing) algorithm to filter price fluctuations and construct a dynamic channel. LOWESS is a non-parametric regression method that smooths noisy data by fitting weighted linear regressions at localized segments. This technique is widely used in statistical analysis to reveal trends while preserving data structure.
In this indicator, the LOWESS algorithm is used to create a central trend line and deviation-based bands. The midline changes color based on trend direction, and diamonds are plotted when a trend shift occurs. Additionally, an RSI gauge is positioned at the end of the channel to display the current RSI level in relation to the price bands.
lowess_smooth(src, length, bandwidth) =>
sum_weights = 0.0
sum_weighted_y = 0.0
sum_weighted_xy = 0.0
sum_weighted_x2 = 0.0
sum_weighted_x = 0.0
for i = 0 to length - 1
x = float(i)
weight = math.exp(-0.5 * (x / bandwidth) * (x / bandwidth))
y = nz(src , 0)
sum_weights := sum_weights + weight
sum_weighted_x := sum_weighted_x + weight * x
sum_weighted_y := sum_weighted_y + weight * y
sum_weighted_xy := sum_weighted_xy + weight * x * y
sum_weighted_x2 := sum_weighted_x2 + weight * x * x
mean_x = sum_weighted_x / sum_weights
mean_y = sum_weighted_y / sum_weights
beta = (sum_weighted_xy - mean_x * mean_y * sum_weights) / (sum_weighted_x2 - mean_x * mean_x * sum_weights)
alpha = mean_y - beta * mean_x
alpha + beta * float(length / 2) // Centered smoothing
⯁ KEY FEATURES
LOWESS Price Filtering – Smooths price fluctuations to reveal the underlying trend with minimal lag.
Dynamic Trend Coloring – The midline changes color based on trend direction (e.g., bullish or bearish).
Trend Shift Diamonds – Marks points where the midline color changes, indicating a possible trend shift.
Deviation-Based Bands – Expands above and below the midline using ATR-based multipliers for volatility tracking.
RSI Gauge Display – A vertical gauge at the right side of the chart shows the current RSI level relative to the price channel.
Fully Customizable – Users can adjust LOWESS length, band width, colors, and enable or disable the RSI gauge and adjust RSIlength.
⯁ HOW TO USE
Use the LOWESS midline as a trend filter —bullish when green, bearish when purple.
Watch for trend shift diamonds as potential entry or exit signals.
Utilize the price bands to gauge overbought and oversold zones based on volatility.
Monitor the RSI gauge to confirm trend strength—high RSI near upper bands suggests overbought conditions, while low RSI near lower bands indicates oversold conditions.
⯁ CONCLUSION
The Lowess Channel + (RSI) indicator offers a powerful way to analyze market trends by applying a statistically robust smoothing algorithm. Unlike traditional moving averages, LOWESS filtering provides a flexible, responsive trendline that adapts to price movements. The integrated RSI gauge enhances decision-making by displaying momentum conditions alongside trend dynamics. Whether used for trend-following or mean reversion strategies, this indicator provides traders with a well-rounded perspective on market behavior.
Adaptive Fibonacci Volatility Bands (AFVB)
**Adaptive Fibonacci Volatility Bands (AFVB)**
### **Overview**
The **Adaptive Fibonacci Volatility Bands (AFVB)** indicator enhances standard **Fibonacci retracement levels** by dynamically adjusting them based on market **volatility**. By incorporating **ATR (Average True Range) adjustments**, this indicator refines key **support and resistance zones**, helping traders identify **more reliable entry and exit points**.
**Key Features:**
- **ATR-based adaptive Fibonacci levels** that adjust to changing market volatility.
- **Buy and Sell signals** based on price interactions with dynamic support/resistance.
- **Toggleable confirmation filter** for refining trade signals.
- **Customizable color schemes** and alerts.
---
## **How This Indicator Works**
The **AFVB** operates in three main steps:
### **1️⃣ Detecting Key Fibonacci Levels**
The script calculates **swing highs and swing lows** using a user-defined lookback period. From this, it derives **Fibonacci retracement levels**:
- **0% (High)**
- **23.6%**
- **38.2%**
- **50% (Mid-Level)**
- **61.8%**
- **78.6%**
- **100% (Low)**
### **2️⃣ Adjusting for Market Volatility**
Instead of using **fixed retracement levels**, this indicator incorporates an **ATR-based adjustment**:
- **Resistance levels** shift **upward** based on ATR.
- **Support levels** shift **downward** based on ATR.
- This makes levels more **responsive** to price action.
### **3️⃣ Generating Buy & Sell Signals**
AFVB provides **two types of signals** based on price interactions with key levels:
✔ **Buy Signal**:
Occurs when price **dips below** a support level (78.6% or 100%) and **then closes back above it**.
- **Optionally**, a confirmation buffer can be enabled to require price to close **above an additional threshold** (based on ATR).
✔ **Sell Signal**:
Triggered when price **breaks above a resistance level** (0% or 23.6%) and **then closes below it**.
📌 **Important:**
- The **buy threshold setting** allows traders to **fine-tune** entry conditions.
- Turning this setting **off** generates **more frequent** buy signals.
- Keeping it **on** reduces false signals but may result in **fewer trade opportunities**.
---
## **How to Use This Indicator in Trading**
### 🔹 **Entry Strategy (Buying)**
1️⃣ Look for **buy signals** at the **78.6% or 100% Fibonacci levels**.
2️⃣ Ensure price **closes above** the support level before entering a long trade.
3️⃣ **Enable or disable** the buy threshold filter depending on desired trade strictness.
### 🔹 **Exit Strategy (Selling)**
1️⃣ Watch for **sell signals** at the **0% or 23.6% Fibonacci levels**.
2️⃣ If price **breaks above resistance and then closes below**, consider exiting long positions.
3️⃣ Can be used **alone** or **combined with trend confirmation tools** (e.g., moving averages, RSI).
### 🔹 **Using the Toggleable Buy Threshold**
- **ON**: Buy signal requires **extra confirmation** (reduces false signals but fewer trades).
- **OFF**: Buy triggers as soon as price **closes back above support** (more signals, but may include weaker setups).
---
## **User Inputs**
### **🔧 Customization Options**
- **ATR Length**: Defines the period for **ATR calculation**.
- **Swing Lookback**: Determines how far back to find **swing highs and lows**.
- **ATR Multiplier**: Adjusts the size of **volatility-based modifications**.
- **Buy/Sell Threshold Factor**: Fine-tunes the **entry signal strictness**.
- **Show Level Labels**: Enables/disables **Fibonacci level annotations**.
- **Color Settings**: Customize **support/resistance colors**.
### **📢 Alerts**
AFVB includes built-in **alert conditions** for:
- **Buy Signals** ("AFVB BUY SIGNAL - Possible reversal at support")
- **Sell Signals** ("AFVB SELL SIGNAL - Possible reversal at resistance")
- **Any Signal Triggered** (Useful for automated alerts)
---
## **Who Is This Indicator For?**
✅ **Scalpers & Day Traders** – Helps identify **short-term reversals**.
✅ **Swing Traders** – Useful for **buying dips** and **selling rallies**.
✅ **Trend Traders** – Can be combined with **momentum indicators** for confirmation.
**Best Timeframes:**
⏳ **15-minute, 1-hour, 4-hour, Daily charts** (works across multiple assets).
---
## **Limitations & Considerations**
🚨 **Important Notes**:
- **No indicator guarantees profits**. Always **combine** it with **risk management strategies**.
- Works best **in trending & mean-reverting markets**—may generate false signals in **choppy conditions**.
- Performance may vary across **different assets & timeframes**.
📢 **Backtesting is recommended** before using it for live trading.
OBV Trend Bands [Alpha Extract]OBV Trend Bands 📊
The OBV Trend Bands indicator leverages On-Balance Volume (OBV) to assess trend strength and potential reversals by plotting a dynamic median line alongside upper and lower bands based on standard deviation. This tool helps traders identify overbought or oversold conditions and visualize OBV momentum relative to historical trends.
🔶 CALCULATION
The indicator calculates OBV, a dynamic median of OBV, and standard deviation bands to measure volume-driven momentum:
• OBV: Cumulative volume that adds or subtracts based on price direction.
• Aggregate Median: A smoothed median of OBV over a user-defined lookback period, adjusted by a minimum lookback for robustness.
• Standard Deviation Bands: Upper and lower bands derived from the scaled aggregate median, adjusted by a multiplier.
• Scaled OBV: OBV divided by a customizable scaling factor for better visualization.
Formula:
• OBV = Cumulative sum of volume (positive if price increases, negative if price decreases)
• Aggregate Median = Average of simple medians over a range from minLookbackPeriod to length
• Upper Band = Aggregate Median / Scaling Factor + StdMultiplier * StdDev
• Lower Band = Aggregate Median / Scaling Factor - StdMultiplier * StdDev
🔶 DETAILS
Visual Features:
• OBV Line (Dynamic Color): Plotted with a color that shifts based on its position—green above the upper band (bullish), red below the lower band (bearish), and white between bands (neutral).
• Upper Band (Green): Represents the overbought threshold, lightly shaded for clarity.
• Lower Band (Red): Indicates the oversold threshold, also lightly shaded.
• Aggregate Median Line (Gray): Acts as the central trend reference.
• Fill Areas: Transparent green fill when OBV exceeds the upper band, transparent red fill when below the lower band, and no fill within the bands.
Interpretation:
• Bullish Signal: OBV rises above the upper band, suggesting strong buying pressure and potential trend continuation.
• Bearish Signal: OBV falls below the lower band, indicating selling pressure and possible trend weakness.
• Neutral Zone: OBV between bands reflects consolidation or indecision in the market.
🔶 EXAMPLES
The chart demonstrates:
• Bullish Momentum: OBV crosses above the upper band with a green line and fill, signaling robust accumulation.
• Bearish Momentum: OBV drops below the lower band with a red line and fill, indicating distribution or selling pressure.
• Reversal Points: Transitions of OBV from below the lower band to above the upper band (or vice versa) suggest potential trend shifts.
Example Snapshots:
• A sustained bullish phase where OBV remains above the upper band with consistent green coloring.
• A bearish trend change where OBV falls below the upper band hinting at weakening momentum leading to a change in trend.
🔶 SETTINGS
Customization Options:
• Median Length (Default: 100): Adjusts the period for calculating the aggregate median, tailoring trend sensitivity.
• Minimum Lookback Period (Default: 30): Sets the shortest period for median aggregation, refining responsiveness.
• Standard Deviation Multiplier (Default: 1.0): Controls the width of the bands—higher values widen them, lower values tighten them.
• Scaling Factor (Default: 100,000): Scales OBV for better chart readability, adjustable based on asset volume.
The OBV Trend Bands indicator is a versatile tool for traders, blending volume analysis with statistical boundaries to effectively pinpoint market extremes and momentum shifts.
Anchored Powered KAMA [LuxAlgo]The Anchored Powered KAMA tool is a new flavor of the famous Kaufman's Adaptive Moving Average (KAMA).
It adds 5 different anchoring periods, a power exponent to the original KAMA calculation to increase the degree of filtering during ranging trends, and standard deviation bands calculated against the KAMA itself.
🔶 USAGE
In the image above we can see the different parts of the tool, it displays the Anchored Powered KAMA surrounded by standard deviation bands at 2x (solid) and 1x (dashed) by default.
This tool provides a simple and easy way to determine if the current market is ranging or trending and where the market extremes are in the current period.
As a rule of thumb, traders may want to trade extremes in ranges and pullbacks in trends.
When the KAMA is flat, a range is in place, so traders may want to wait for the price to reach an extreme before opening a trade in the other direction.
Conversely, if the KAMA is moving up or down, a trend is in place and traders may want to wait for the price to pull back to the KAMA before opening a trade in the direction of the trend.
🔹 Anchor Period
On the above chart, we can see different anchor periods on different chart timeframes.
This option is very useful for those traders who use multi-timeframe analysis, allowing them to see how the market behaves over different timeframes.
The valid values for this parameter are:
Hourly
Daily
Weekly
Monthly
Yearly
The tool has a built-in Auto feature for traders convenience, it automatically selects the optimal Anchor Period in function of the chart timeframe.
timeframes up to 2m: Hourly
timeframes up to 15m: Daily
timeframes up to 1H: Weekly
timeframes up to 4H: Monthly
larger timeframes: Yearly
🔹 Choosing the Right Anchor Period
In the chart above we can see the custom error message that the tool displays when the Auto feature is disabled and the Anchor Period is too large for the current chart timeframe.
Traders can select a smaller Anchor Period or a larger chart timeframe for the tool to display correctly.
🔶 DETAILS
The tool uses Welford's algorithm to calculate the KAMA's standard deviation, then plots the outer bands at the multiplier specified in the settings panel, and the inner bands at the multiplier specified minus 1.
🔹 Power Exponent
The graph above shows how different values of this parameter can affect the output.
To display the original KAMA a value of 1 must be set, by default this parameter is set to 2.
The higher the value, the better the tool's ability to detect ranges.
🔶 SETTINGS
Anchor Period: Select up to 5 different time periods from Hourly, Daily, Weekly, Monthly, and Yearly.
Source: Choose the source for all calculations.
Power Exponent: Fine-tune the KAMA calculation, a value of 1 will output the original KAMA, and is set to 2 by default.
Band Multiplier: Select the multiplier for the standard deviation bands.
