GCM Volatility-Adaptive Trend ChannelScript Description
Name: GCM Volatility-Adaptive Trend Channel (GCM VATC)
Overview
The GCM Volatility-Adaptive Trend Channel (VATC) is a comprehensive trading tool that merges the low-lag, smooth-trending capabilities of the Jurik Moving Average (JMA) with the classic volatility analysis of Bollinger Bands (BB).
By displaying both trend and volatility in a single, intuitive interface, this indicator aims to help traders see when a trend is stable versus when it's becoming volatile and might be poised for a change.
Core Components:
JMA Trend System: At its core are three dynamically colored JMA lines (Baseline, Fast, and Slow) that provide a clear view of trend direction. The lines change color based on their slope, offering immediate visual feedback on momentum. A colored ribbon between the Baseline and Fast JMA visualizes shorter-term momentum shifts.
Standard Bollinger Bands: Layered on top are standard Bollinger Bands. Calculated from the price, these bands serve as a classic measure of market volatility. They help identify periods where the market is expanding (high volatility) or contracting (low volatility).
How to Use It
By combining these two powerful concepts, this indicator provides a unified view of both trend and volatility. It can help traders to:
Identify the primary trend direction using the smooth JMA lines.
Gauge the strength and stability of that trend.
See when the market is becoming volatile (bands widening) or consolidating (bands contracting), which can often precede a significant price move or a change in trend.
A Note on Originality & House Rules Compliance
This indicator does not introduce a new mathematical formula. Instead, its strength lies in the thoughtful combination of two well-respected, publicly available concepts: the Jurik Moving Average and Bollinger Bands. The JMA implementation is a standard public version. The goal was to create a practical, all-in-one tool for trend and volatility analysis.
This script is published as fully open-source in compliance with TradingView's House Rules. It utilizes standard, publicly available algorithms and does not contain any protected or hidden code.
Settings
All lengths, sources, and colors for the JMA lines and Bollinger Bands are fully customizable in the settings menu, allowing you to tailor the indicator to your specific trading style and asset.
I hope with this indicator Traders even Beginner can can control their emotions which increase the probabilities of the winning rates and cutting the losing strength
Purposely I Didn't plant the High low or Buy Sell signals in the chart. Because everything is in the chart where volatility Signal with the Bollinger Band and Buy Sell Signal in the JMA Dynamic colors. and that's enough to decide when to take trade and when not to.
Thank You and Happy Trading
ابحث في النصوص البرمجية عن "band"
Zone Shift [ChartPrime]⯁ OVERVIEW
Zone Shift is a dynamic trend detection tool that uses EMA/HMA-based bands to determine trend shifts and plot key reaction levels. It highlights trend direction through colored candles and marks important retests with visual cues to help traders stay aligned with momentum.
⯁ KEY FEATURES
Dynamic EMA-HMA Band:
Creates a three-line channel using the average of an EMA and HMA for the midline, and expands it using average candle range to form upper and lower bounds. This band visually adapts to market volatility.
float ema = ta.ema(close, length)
float hma = ta.hma(close, length-40)
float dist = ta.sma(high-low, 200)
float mid = math.avg(ema, hma)
float top = mid + dist
float bot = mid - dist
Trend Detection (Band Cross Logic):
Detects an uptrend when the Low crosses above the top band.
Detects a downtrend when the High crosses below the bottom band.
Bars change color to lime for uptrends and blue for downtrends.
Trend Initiation Level:
At the start of a new trend, the indicator locks in the extreme point (low for uptrend, high for downtrend) and plots a dashed horizontal level, serving as a potential retest zone.
Trend Retest Signal:
If price crosses back over the Trend Initiation level in the direction of the trend, a diamond label (⯁) is plotted at the retest point — confirming that price is revisiting a key shift level.
Visual Band Layout:
Midline: Dashed line shows the average of EMA and HMA.
Top/Bottom: Solid lines showing dynamic thresholds above/below the midline.
These help visualize compression, expansion, and possible breakout zones.
Color-Based Candle Plotting:
Candles are recolored in real time according to the current trend, allowing instant visual alignment with the market’s directional bias.
Noise-Filtered Retests:
To avoid repetitive signals, retests are only marked if they occur more than 5 bars after the previous one — filtering out minor fluctuations.
⯁ USAGE
Use colored candles to align trades with the dominant trend.
Treat dashed trendStart levels as important support/resistance zones.
Watch for ⯁ diamond labels as confirmation of retests for continuation or entry.
Use band boundaries to assess trend strength and volatility expansion.
Combine with your existing setups to validate momentum and zone shifts.
⯁ CONCLUSION
Zone Shift helps traders visually capture trend changes and key reaction points with precision. By combining band breakouts with real-time retest signals and trend-colored candles, this tool simplifies the process of reading market structure shifts and identifying high-confluence entry areas.
Money NoodleMoney Noodle Indicator - How It Works
The Money Noodle indicator is a trend-following and support/resistance tool that combines multiple exponential moving averages (EMAs) with dynamic volatility-based bands to create a comprehensive trading system.
Core Components
1. Triple EMA System ("The Noodles")
Fast EMA (12): Most responsive to price changes, shows short-term momentum
Medium EMA (21): Intermediate trend direction
Slow EMA (35): Main trend line that acts as the central reference point
The "noodle" effect comes from how these three EMAs weave around each other and the price action, creating curved, flowing lines that resemble noodles.
2. Dynamic Volatility Bands
Upper Band: Main EMA + (ATR × Band Multiplier)
Lower Band: Main EMA - (ATR × Band Multiplier)
Uses a 20-period ATR (Average True Range) to measure market volatility
Band width automatically adjusts - wider during volatile periods, tighter during consolidation
How It Functions
Trend Identification:
When all three EMAs are aligned (fast > medium > slow), it indicates a strong uptrend
When EMAs are inverted (fast < medium < slow), it signals a downtrend
EMA crossovers provide early trend change signals
Support & Resistance:
The bands act as dynamic support and resistance levels
Price tends to bounce off the bands during trending markets
Band breaks often signal strong momentum moves or trend changes
Volatility Assessment:
Band width indicates market volatility - wider bands = higher volatility
ATR-based calculation makes the bands adaptive to current market conditions
The 0.0125 multiplier provides optimal sensitivity for most timeframes
Trading Applications
Entry Signals:
Buy when price bounces off the lower band with EMA alignment
Sell when price bounces off the upper band against the trend
Breakout trades when price decisively breaks through bands
Trend Following:
Use the main EMA (35) as your trend filter
Trade in the direction of EMA alignment
The "noodles" help identify trend strength - tighter = stronger trend
Risk Management:
Bands provide natural stop-loss levels
Band width helps size positions (wider bands = smaller size due to higher volatility)
The indicator works best on daily timeframes and provides a visual, intuitive way to read market structure, trend direction, and volatility all in one tool.
Half-Trend Channel [BigBeluga]Half Trend Channel is a powerful trend-following indicator designed to identify trend direction, fakeouts, and potential reversal points. The combination of upper/lower bands, midline coloring, and specific signals makes it ideal for spotting trend continuation and market reversals.
The base of the channel is calculated using smoothed half-trend logic.
// Initialize half trend on the first bar
if barstate.isfirst
hl_t := close
// Update half trend value based on conditions
switch
closeMA < hl_t and highestHigh < hl_t => hl_t := highestHigh
closeMA > hl_t and lowestLow > hl_t => hl_t := lowestLow
=> hl_t := hl_t
// Smooth
float s_hlt = ta.hma(hl_t, len)
🔵 Key Features:
Upper and Lower Bands:
The bands adapt dynamically to market volatility.
Price movements toward the bands help identify areas of overextension and potential reversal points.
Midline Trend Signal:
The midline changes color to reflect the current trend:
Green Midline: Indicates an uptrend.
Purple Midline: Signals a downtrend.
Fakeout Signals ("X"):
"X" markers appear when price briefly breaches the outer bands but fails to sustain the move.
Fakeouts help traders identify areas where price momentum weakens.
Reversal Signals (Triangles):
Triangles (▲ and ▼) mark potential tops and bottoms:
▲ Up Triangles: Suggest a potential bottom and a reversal to the upside.
▼ Down Triangles: Indicate a potential top and a reversal to the downside.
Dynamic Trend Labels:
At the last bar, the indicator displays labels like "Trend Up" or "Trend Dn" , reflecting the current trend direction.
🔵 Usage:
Use the colored midline to determine the overall trend direction.
Monitor "X" fakeout signals to spot failed breakouts or momentum exhaustion near the bands.
Watch for reversal triangles (▲ and ▼) to identify potential trend reversals at tops or bottoms.
Combine the bands and midline signals to confirm trade entries and exits:
Enter long trades when price bounces off the lower band with a green midline.
Consider short trades when price reverses from the upper band with a purple midline.
Use the trend label (e.g., "Trend Up" or "Trend Dn") for quick confirmation of the current market state.
The Half Trend Channel is an essential tool for traders who want to follow trends, avoid fakeouts, and identify reliable tops and bottoms to optimize their trading decisions.
GOLDEN RSI by @thejamiulGOLDEN RSI thejamiul is a versatile Relative Strength Index (RSI)-based tool designed to provide enhanced visualization and additional insights into market trends and potential reversal points. This indicator improves upon the traditional RSI by integrating gradient fills for overbought/oversold zones and divergence detection features, making it an excellent choice for traders who seek precise and actionable signals.
Source of this indicator : This indicator is based on @TradingView original RSI indicator with a little bit of customisation to enhance overbought and oversold identification.
Key Features
1. Customizable RSI Settings:
RSI Length: Adjust the RSI calculation period to suit your trading style (default: 14).
Source Selection: Choose the price source (e.g., close, open, high, low) for RSI calculation.
2. Gradient-Filled RSI Zones:
Overbought Zone (80-100): Gradient fill with shades of green to indicate strong bullish conditions.
Oversold Zone (0-20): Gradient fill with shades of red to highlight strong bearish conditions.
3. Support and Resistance Levels:
Upper Band: 80
Middle Bands: 60 (bullish) and 40 (bearish)
Lower Band: 20
These levels help identify overbought, oversold, and neutral zones.
4. Divergence Detection:
Bullish Divergence: Detects lower lows in price with corresponding higher lows in RSI, signaling potential upward reversals.
Bearish Divergence: Detects higher highs in price with corresponding lower highs in RSI, indicating potential downward reversals.
Visual Indicators:
Bullish divergence is marked with green labels and line plots.
Bearish divergence is marked with red labels and line plots.
5. Alert Functionality:
Custom Alerts: Set up alerts for bullish or bearish divergences to stay notified of potential trading opportunities without constant chart monitoring.
6. Enhanced Chart Visualization:
RSI Plot: A smooth and visually appealing RSI curve.
Color Coding: Gradient and fills for better distinction of trading zones.
Pivot Labels: Clear identification of divergence points on the RSI plot.
SufinBDThis TradingView script combines RSI, Stochastic RSI, MACD, and Bollinger Bands to generate Buy and Sell signals on two different timeframes: 4-hour (4H) and Daily (1D). The strategy aims to provide entry and exit points based on a multi-indicator confirmation approach, helping traders make more informed decisions.
Features:
RSI (Relative Strength Index):
Measures the speed and change of price movements.
The script looks for oversold conditions (RSI below 30) for buy signals and overbought conditions (RSI above 70) for sell signals.
Stochastic RSI:
Measures the level of RSI relative to its high-low range over a given period.
A Stochastic RSI below 0.2 indicates oversold conditions, and a value above 0.8 indicates overbought conditions.
It helps identify overbought and oversold conditions in a more precise manner than regular RSI.
MACD (Moving Average Convergence Divergence):
A trend-following momentum indicator that shows the relationship between two moving averages of a security's price.
The MACD line crossing above the Signal line generates bullish signals, and vice versa for bearish signals.
Bollinger Bands:
A volatility indicator that consists of a middle band (SMA of price), an upper band, and a lower band.
When the price is below the lower band, it signals potential buy opportunities, while prices above the upper band signal potential sell opportunities.
Timeframe Usage:
The script calculates indicators for both the 4-hour (4H) and Daily (1D) timeframes.
The combined signals from these two timeframes are used to generate Buy and Sell alerts.
Buy Signal:
A Buy signal is generated when all of the following conditions are met:
RSI on both 4H and 1D is below 30 (oversold conditions).
Stochastic RSI on both timeframes is below 0.2.
The MACD line is above the Signal line on both timeframes.
The price is below the lower Bollinger Band on both the 4H and 1D charts.
Sell Signal:
A Sell signal is generated when all of the following conditions are met:
RSI on both 4H and 1D is above 70 (overbought conditions).
Stochastic RSI on both timeframes is above 0.8.
The MACD line is below the Signal line on both timeframes.
The price is above the upper Bollinger Band on both the 4H and 1D charts.
Visuals:
Buy signals are marked with green labels below the bars.
Sell signals are marked with red labels above the bars.
Bollinger Bands are displayed on the chart with the upper and lower bands marked in blue (for 4H) and orange (for 1D).
Purpose:
This script aims to provide more reliable buy/sell signals by combining indicators across multiple timeframes. It is ideal for traders who want to use multiple confirmation points before entering or exiting a trade.
How to Use:
Apply the script to any chart on TradingView.
Look for Buy and Sell signals that meet the conditions above.
You can adjust the timeframe (e.g., 4H or 1D) based on your trading strategy.
This script can be used for intraday trading, swing trading, or position trading depending on your preferred timeframes.
Example of Signal Interpretation:
Buy Signal:
If all conditions are met (e.g., RSI is under 30, Stochastic RSI is under 0.2, MACD is bullish, and price is below the lower Bollinger Band on both the 4-hour and daily charts), the script will show a green "BUY" label below the price bar.
Sell Signal:
If all conditions are met (e.g., RSI is over 70, Stochastic RSI is over 0.8, MACD is bearish, and price is above the upper Bollinger Band on both timeframes), the script will show a red "SELL" label above the price bar.
This combination of indicators offers a multi-layered confirmation approach, which aims to reduce the risk of false signals and increase the reliability of your trading decisions.
Volatility Signaling 50SMAOverview of the Script:
The script implements a volatility signaling indicator using a 50-period Simple Moving Average (SMA). It incorporates Bollinger Bands and the Average True Range (ATR) to dynamically adjust the SMA's color based on volatility conditions. Here's a detailed breakdown:
Components of the Script:
1. Inputs:
The script allows the user to customize key parameters for flexibility:
Bollinger Bands Length (length): Determines the period for calculating the Bollinger Bands.
Source (src): The price data to use, defaulting to the closing price.
Standard Deviation Multiplier (mult): Scales the Bollinger Bands' width.
ATR Length (atrLength): Sets the period for calculating the ATR.
The 50-period SMA length (smaLength) is fixed at 50.
2. Bollinger Bands Calculation:
Basis: Calculated as the SMA of the selected price source over the specified length.
Upper and Lower Bands: Determined by adding/subtracting a scaled standard deviation (dev) from the basis.
3. ATR Calculation:
Computes the Average True Range over the user-defined atrLength.
4. Volatility-Based Conditions:
The script establishes thresholds for Bollinger Band width relative to ATR:
Yellow Condition: When the band width (upper - lower) is less than 1.25 times the ATR.
Orange Condition: When the band width is less than 1.5 times the ATR.
Red Condition: When the band width is less than 1.75 times the ATR.
5. Dynamic SMA Coloring:
The 50-period SMA is colored based on the above conditions:
Yellow: Indicates relatively low volatility.
Orange: Indicates moderate volatility.
Red: Indicates higher volatility.
White: Default color when no conditions are met.
6. Plotting the 50-Period SMA:
The script plots the SMA (sma50) with a dynamically assigned color, enabling visual analysis of market conditions.
Use Case:
This script is ideal for traders seeking to assess market volatility and identify changes using Bollinger Bands and ATR. The colored SMA provides an intuitive way to gauge market dynamics directly on the chart.
Example Visualization:
Yellow SMA: The market is in a low-volatility phase.
Orange SMA: Volatility is picking up but remains moderate.
Red SMA: Higher volatility, potentially signaling significant market activity.
White SMA: Neutral/default state.
Enhanced Kaufman Adaptive Moving Average (KAMA) with Bollinger B# Enhanced Kaufman Adaptive Moving Average (KAMA) with Bollinger Bands
## Overview
This indicator combines the Kaufman Adaptive Moving Average (KAMA) with Bollinger Bands to create a comprehensive trading system. It provides adaptive trend following capabilities while measuring market volatility and potential reversal points.
## Key Features
- Adaptive moving average that adjusts to market conditions
- Dynamic Bollinger Bands for volatility measurement
- Color-coded KAMA line indicating trend direction
- Integrated buy/sell signals based on multiple confirmations
- Customizable parameters for both KAMA and Bollinger Bands
- Optional bar confirmation wait feature
- Built-in alert conditions for trade signals
## Main Components
### 1. Kaufman Adaptive Moving Average (KAMA)
- Adapts to market volatility using an efficiency ratio
- Changes color based on trend direction (green for uptrend, red for downtrend)
- Adjustable parameters for fine-tuning:
- Base Length: Controls the main calculation period (default: 10)
- Fast EMA Length: For rapid market response (default: 2)
- Slow EMA Length: For stable market conditions (default: 30)
### 2. Bollinger Bands
- Standard deviation-based volatility bands
- Customizable length and standard deviation multiplier
- Includes expansion threshold for volatility measurement
- Components:
- Upper Band: Upper volatility threshold
- Middle Band: Simple moving average
- Lower Band: Lower volatility threshold
## Signal Generation
### Buy Signals
Generated when:
1. KAMA color changes from red to green
2. Price closes above KAMA
3. Price closes above the middle Bollinger Band
4. Signals are marked with:
- Green triangles below the candles
- "B" labels for easy identification
### Sell Signals
Generated when:
1. KAMA color changes from green to red
2. Price closes below KAMA
3. Price closes below the middle Bollinger Band
4. Signals are marked with:
- Red triangles above the candles
- "S" labels for easy identification
## Customizable Parameters
### KAMA Settings
- Base Length (1-50)
- Fast EMA Length (1-10)
- Slow EMA Length (10-50)
- Source Price Selection
- Direction Highlight Toggle
- Bar Confirmation Option
### Bollinger Bands Settings
- Length (default: 20)
- Standard Deviation Multiplier (default: 2.0)
- Expansion Threshold (0.1-3.0)
## Alert Functionality
Built-in alerts for:
- Buy signals with customizable messages
- Sell signals with customizable messages
## Best Practices
### Timeframe Selection
- Works well on multiple timeframes
- Recommended for 15m to 4h charts for optimal signal generation
- Higher timeframes provide more reliable trend signals
### Parameter Optimization
- Adjust KAMA lengths based on trading style:
- Shorter lengths for day trading
- Longer lengths for swing trading
- Fine-tune BB multiplier based on market volatility
- Consider waiting for bar confirmation in volatile markets
### Risk Management
- Use in conjunction with other indicators for confirmation
- Consider market conditions and volatility when trading signals
- Implement proper position sizing and stop-loss levels
## Technical Notes
- Written in Pine Script™ v6
- Overlay indicator (displays on price chart)
- Compatible with all TradingView-supported markets
- Resource-efficient implementation for smooth performance
## Disclaimer
This indicator is provided under the Mozilla Public License 2.0. While it can be a valuable tool for technical analysis, it should not be used as the sole basis for trading decisions. Always combine with proper risk management and additional analysis methods.
Multifactor Buy/Sell Strategy V2 | RSI, MACD, ATR, EMA, Boll.BITGET:1INCHUSDT
This Pine Script code for TradingView is a multifactor Buy/Sell indicator that combines several technical factors to generate trading signals based on trend, volatility, and volume conditions. Here’s a breakdown of the main components and functionality:
Indicator Name
- Multifactor Buy/Sell Strategy V2 — an overlay indicator applied directly on the price chart.
### Input Parameters
The script includes multiple customizable parameters:
- RSI, EMA, MACD parameters — for setting periods and signals of MACD and RSI.
- ATR and Bollinger Bands — used for volatility analysis and level determination.
- Minimum Volatility Threshold — sets a minimum Bollinger Band width threshold for determining high volatility.
Core Indicators
1. RSI — calculated to identify oversold (below 30) and overbought (above 70) conditions.
2. EMA and MACD — calculates exponential moving averages and MACD histogram to determine trend direction.
3. ATR and Bollinger Bands — used to assess current volatility and establish dynamic upper and lower bands.
Volatility and Volume Analysis
- Determines the current ATR level and Bollinger Band width to evaluate high volatility.
- Calculates the volume moving average to track periods of increased volume during high volatility.
Trend Analysis
The script uses the difference between fast and slow EMAs to define strong trends:
- Uptrend — when the fast EMA is above the slow EMA, the price is above the fast EMA, and the trend is strong.
- Downtrend — when the fast EMA is below the slow EMA, the price is below the fast EMA, and the trend is strong.
Momentum Filter
- Based on the price change over the last three bars and compared against the minimum volatility threshold to identify strong momentum.
Buy and Sell Signal Generation
- Buy Signal: Uptrend with RSI oversold, positive MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
- Sell Signal: Downtrend with RSI overbought, negative MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
Visualization
- Buy and sell signals are displayed as green and red triangles on the chart.
- Plots for fast and slow EMAs, upper and lower bands, and Bollinger Bands.
Alerts
The script includes alert conditions for buy and sell signals, allowing notifications to be sent via email or mobile app.
Information Panel
A small table on the chart displays current volatility dataThis Pine Script code for TradingView is a multifactor Buy/Sell indicator that combines several technical factors to generate trading signals based on trend, volatility, and volume conditions. Here’s a breakdown of the main components and functionality:
Indicator Name
- Multifactor Buy/Sell Strategy V2 — an overlay indicator applied directly on the price chart.
Input Parameters
The script includes multiple customizable parameters:
- **RSI, EMA, MACD parameters** — for setting periods and signals of MACD and RSI.
- **ATR and Bollinger Bands** — used for volatility analysis and level determination.
- **Minimum Volatility Threshold** — sets a minimum Bollinger Band width threshold for determining high volatility.
Core Indicators
1. RSI — calculated to identify oversold (below 30) and overbought (above 70) conditions.
2. EMA and MACD — calculates exponential moving averages and MACD histogram to determine trend direction.
3. ATR and Bollinger Bands — used to assess current volatility and establish dynamic upper and lower bands.
Volatility and Volume Analysis
- Determines the current ATR level and Bollinger Band width to evaluate high volatility.
- Calculates the volume moving average to track periods of increased volume during high volatility.
Trend Analysis
The script uses the difference between fast and slow EMAs to define strong trends:
- Uptrend — when the fast EMA is above the slow EMA, the price is above the fast EMA, and the trend is strong.
- Downtrend — when the fast EMA is below the slow EMA, the price is below the fast EMA, and the trend is strong.
Momentum Filter
- Based on the price change over the last three bars and compared against the minimum volatility threshold to identify strong momentum.
Buy and Sell Signal Generation
- Buy Signal: Uptrend with RSI oversold, positive MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
- Sell Signal: Downtrend with RSI overbought, negative MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
Visualization
- Buy and sell signals are displayed as green and red triangles on the chart.
- Plots for fast and slow EMAs, upper and lower bands, and Bollinger Bands.
Alerts
The script includes alert conditions for buy and sell signals, allowing notifications to be sent via email or mobile app.
Information Panel
A small table on the chart displays current volatility
- Volatility Status — indicates high or low volatility.
- Bollinger Band Width — current width as a percentage.
- ATR Ratio — ratio of current ATR to long-term average ATR.
This script is suitable for trading in high-volatility conditions, combining multiple filters and factors to generate precise buy and sell signals.
Bitcoin wave modelBitcoin wave model is based on the logarithmic regression model and the sinusoidal waves, induced by the halving events.
This chart presents the outcome of an in-depth analysis of the complete set of Bitcoin price data available from October 2009 to August 2023.
The central concept is that the logarithm of the Bitcoin price closely adheres to the logarithmic regression model. If we plot the logarithm of the price against the logarithm of time, it forms a nearly straight line.
The parameters of this model are provided in the script as follows: log (BTCUSD) = 1.48 + 5.44log(h).
The secondary concept involves employing the inherent time unit of Bitcoin instead of days:
'h' denotes a slightly adjusted time measurement intrinsic to the Bitcoin blockchain. It can be approximated as (days since the genesis block) * 0.0007. Precisely, 'h' is defined as follows: h = 0 at the genesis block, h = 1 at the first halving block, and so forth. In general, h = block height / 210,000.
Adjustments are made to account for variations in block creation time.
The third concept revolves around investigating halving waves triggered by supply shock events resulting from the halvings. These halvings occur at regular intervals in Bitcoin's native time 'h'. All halvings transpire when 'h' is an integer. These events induce waves with intervals denoted as h = 1.
Consequently, we can model these waves using a sin(2pih - a) function. The parameter determining the time shift is assessed as 'a = 0.4', aligning with earlier expectations for halving events and their subsequent outcomes.
The fourth concept introduces the notion that the waves gradually diminish in amplitude over the progression of "time h," diminishing at a rate of 0.7^h.
Lastly, we can create bands around the modeled sinusoidal waves. The upper band is derived by multiplying the sine wave by a factor of 3.1*(1-0.16)^h, while the lower band is obtained by dividing the sine wave by the same factor, 3.1*(1-0.16)^h.
The current bandwidth is 2.5x. That means that the upper band is 2.5 times the lower band. These bands are forming an exceptionally narrow predictive channel for Bitcoin. Consequently, a highly accurate estimation of the peak of the next cycle can be derived.
The prediction indicates that the zenith past the fourth halving, expected around the summer of 2025, could result in prices ranging between 200,000 and 240,000 USD.
Enjoy the mathematical insights!
Nadaraya-Watson non repainting [LPWN]// ENGLISH
The problem of the wonderfuls Nadaraya-Watson indicators is that they repainting, @jdehorty made an aproximation of the Nadaraya-Watson Estimator using raational Quadratic Kernel so i used this indicator as inspiration i just added the Upper and lower band using ATR with this we get an aproximation of Nadaraya-Watson Envelope without repainting
Settings:
Bandwidth. This is the number of bars that the indicator will use as a lookback window.
Relative Weighting Parameter. The alpha parameter for the Rational Quadratic Kernel function. This is a hyperparameter that controls the smoothness of the curve. A lower value of alpha will result in a smoother, more stretched-out curve, while a lower value will result in a more wiggly curve with a tighter fit to the data. As this parameter approaches 0, the longer time frames will exert more influence on the estimation, and as it approaches infinity, the curve will become identical to the one produced by the Gaussian Kernel.
Color Smoothing. Toggles the mechanism for coloring the estimation plot between rate of change and cross over modes.
ATR Period. Period to calculate the ATR (upper and lower bands)
Multiplier. Separation of the bands
// SPANISH
El problema de los maravillosos indicadores de Nadaraya-Watson es que repintan, @jdehorty hizo una aproximación delNadaraya-Watson Estimator usando un Kernel cuadrático racional, así que usé este indicador como inspiración y solo agregamos la banda superior e inferior usando ATR con esto obtenemos una aproximación de Nadaraya-Watson Envelope sin volver a pintar
Configuración:
Banda ancha. Este es el número de barras que el indicador utilizará como ventana retrospectiva.
Parámetro de ponderación relativa. El parámetro alfa para la función Rational Quadratic Kernel. Este es un hiperparámetro que controla la suavidad de la curva. Un valor más bajo de alfa dará como resultado una curva más suave y estirada, mientras que un valor más bajo dará como resultado una curva más ondulada con un ajuste más ajustado a los datos. A medida que este parámetro se acerque a 0, los marcos de tiempo más largos ejercerán más influencia en la estimación y, a medida que se acerque al infinito, la curva será idéntica a la que produce el Gaussian Kernel.
Suavizado de color. Alterna el mecanismo para colorear el gráfico de estimación entre la tasa de cambio y los modos cruzados.
Período ATR. Periodo para calcular el ATR (bandas superior e inferior)
Multiplicador. Separación de las bandas
[CBB] Volatility Squeeze ToyThe main concept and features of this script are adapted from Mark Whistler's book "Volatility Illuminated". I have deviated from the use cases and strategies presented in the book, but the 3 Bollinger Bands use his optimized settings as the default length and standard deviation multiplier. Further insights into Mark's concepts and volatility research were gained by reading and watching some of TV user DadShark's materials (www.tradingview.com).
This script has been through many refinements and feature cycles, and I've added unrelated complimentary features not present in the book. The indicator is better studied than described, and unless you have read the book, any short summary of the material will just make you squint and think about the wrong things.
Here is a limited outline of features and concepts:
1. 3 Bollinger Bands of different length and/or deviation multiplier. Perhaps think of them as representing the various time frames that compression and expansion cycles and events manifest in, and also the expression of range, speed and price distribution within those time frames. You can gain insight into the magnitude of events based on how the three bands interact and stay contained, or not. If volatility is significant enough, all "time frames" represented by the bands will eventually record the event and subsequent price action, but the early signals will come from the spasms of the shortest, most volatile band. Many times the short band will contract again before, or just as it reaches a longer band, but in extreme cases, volatility will explode and all bands at all time frames will erupt in succession. In these cases you will see additional color representing shorter bands (lower time frame volatility in concept) traveling outside of longer bands. It is worth taking a look at the price levels and candles where these volatility bands cross each other.
2. In addition to the mean of the bands, there are a variety of other moving averages available to gauge trend, range, and areas of interest. This is accomplished with variable VWAP, ATR, smoothing, and a special derived loosely from the difference between them.
3. The bands are also used to derive conditions under which volatility is considered compressed, or in "squeeze" . Under these conditions the candles will turn yellow. Depending on your chart settings and indicator settings, these zones can be completely useless or drag on through fairly significant price action. Or, the can give you fantastic levels to watch for breakouts. The point is that volatility is compressed during these conditions, and you should expect the inevitable once this condition ends. Sometimes you can find yourself in a nice fat trend straight away, other times you may blow an account because you gorged your position based on arbitrary bar color. It's not like that. Pay attention to the highest and lowest bars of these squeeze ranges, and carefully observe future price action when it returns to these squeeze ranges. This info is more and more valuable at higher time frames.
The 3 bands, a smoothed long trend VWAP, and the squeeze condition colored bars are all active by default. All features can be shown or hidden on the control panel.
There are some deep market insights to mine if you live with this one for a while. As with any indicator, blunt "buy/sell here" approaches will lead to loss and frustration. however , if you pay attention to squeeze range, band/moving average confluence, high volume and/or large range candles their open/close behavior around these areas and squeeze ranges, you will start to catch the beginning of some powerful momentum moves.
Enjoy!
SuperTrendSAP1212This indicator combines Supertrend, VWAP with bands, and an optional RSI filter to generate Buy/Sell signals.
How it works
Supertrend Flip (ATR-based): Detects when trend direction changes (from bearish to bullish, or bullish to bearish).
VWAP Band Filter: Signals only trigger if the candle close is beyond the VWAP bands:
Buy = Supertrend flips up AND close > VWAP Upper Band
Sell = Supertrend flips down AND close < VWAP Lower Band
Optional RSI Filter:
Buy requires RSI < 20
Sell requires RSI > 80
Can be enabled/disabled in settings.
Features
Choice of VWAP band calculation mode: Standard Deviation or ATR.
Adjustable ATR/StDev length and multiplier for VWAP bands.
Toggle Supertrend, VWAP lines, and Buy/Sell labels.
Alerts included: add alerts on BUY or SELL conditions (use Once Per Bar Close to avoid intrabar signals).
Use
Works best on intraday or higher timeframes where VWAP is relevant.
Use the RSI filter for more selective signals.
Can be combined with your own stop-loss and risk management rules.
⚠️ Disclaimer: This script is for educational and research purposes only. It is not financial advice. Always test thoroughly and trade at your own risk.
Peak Reversal v3# Peak Reversal v3
## Summary
Peak Reversal v3 adds new configurability, clearer visuals, and a faster trader workflow. The release introduces a new Squeeze Detector , expanded Keltner Channels , and streamlined Momentum signals , with no repaints and improved performance. The menus have been reorganized and simplified. Color swatches have been added for better customization. All other colors will be derived from these swatches.
## Highlights
New Squeeze Detector to mark low-volatility periods and prepare for breakouts.
New: Bands are now fully configurable with independent MA length, ATR length, and multipliers.
Five moving average bases for bands: EMA (from v2), SMA, RMA, VMA, HMA.
Simplified color system: three swatches drive candles, on-chart marks, and band fill.
Reorganized menu with focused sections and tooltips for each parameter making the entire trader experience more intuitive.
No repaints and faster performance across calculations.
## Overview
Configuration : Pick from three color swatches and apply them to candles, plotted characters, and band fill for consistent chart context. Use the reorganized menu to reach Keltner settings, momentum signals, and squeeze detection without extra clicks; tooltips clarify each input.
Bands and averages: Choose the band basis from EMA, SMA, RMA, VMA, or HMA to match your strategy. Configure two bands independently by setting MA length, ATR length, and band multipliers for the inner and outer envelopes.
Signals : Select the band responsible for momentum signals. Choose wick or close as the price source for entries and exits. Control the window for extreme momentum with “Max Momentum Bars,” a setting now exposed in v3 for direct tuning.
Squeeze detection : The Squeeze Detector normalizes band width and uses percentile ranking to highlight volatility compression. When the market falls below a user-defined threshold, the indicator colors the region with a gradient to signal potential expansion.
## Details about major features and changes
### New
Squeeze Detector to highlight low-volatility conditions.
Five MA bases for bands: EMA, SMA, RMA, VMA, HMA.
“Max Momentum Bars” to cap the bars used for extreme momentum.
### Keltner channel improvements
Refactored Keltner settings for flexible inner and outer band control.
MA type selection added; band calculations updated for consistency.
Removed the third Keltner band to reduce noise and simplify setup.
### Display and signals
Gradient fills for band breakouts, mean deviations, and squeeze periods.
“Show Mean EMA?” set to true and default “Signal Band” set to “Inner.”
Clearer tooltips and input descriptions.
### Reliability and performance
No more repaints. The indicator waits for confirmation before drawing occurs.
Faster execution through targeted refactors.
All algorithms have been reviewed and now use a consistent logic, naming, and structure.
ZLMA Keltner ChannelThe ZLMA Keltner Channel uses a Zero-Lag Moving Average (ZLMA) as the centerline with ATR-based bands to track trends and volatility.
The ZLMA’s reduced lag enhances responsiveness for breakouts and reversals, i.e. it's more sensitive to pivots and trend reversals.
Unlike Bollinger Bands, which use standard deviation and are more sensitive to price spikes, this uses ATR for smoother volatility measurement.
Background:
Built on John Ehlers’ lag-reduction techniques, this indicator adapts the classic Keltner Channel for dynamic markets. It excels in trending (low-entropy) markets for breakouts and range-bound (high-entropy) markets for reversals.
How to Read:
ZLMA (Blue): Tracks price trends. Above = bullish, below = bearish.
Upper Band (Green): ZLMA + (Multiplier × ATR). Cross above signals breakout or overbought.
Lower Band (Red): ZLMA - (Multiplier × ATR). Cross below signals breakout or oversold.
Channel Fill (Gray): Shows volatility. Narrow = low volatility, wide = high volatility.
Signals (Optional): Enable to show “Buy” (green) on upper band crossovers, “Sell” (red) on lower band crossunders.
Strategies: Trade breakouts in trending markets, reversals in ranges, or use bands as trailing stops.
Settings:
ZLMA Period (20): Adjusts centerline responsiveness.
ATR Period (20): Sets volatility period.
Multiplier (2.0): Controls band width.
If you are still confused between the ZLMA Keltner Channels and Bollinger Bands:
Keltner Channel (ZLMA): Uses ATR for bands, which smooths volatility and is less reactive to sudden price spikes. The ZLMA centerline reduces lag for faster trend detection.
Bollinger Bands: Uses standard deviation for bands, making them more sensitive to price volatility and prone to wider swings in high-entropy markets. Typically uses an SMA centerline, which lags more than ZLMA.
RSI Games 1.2he "RSI Games 1.2" indicator enhances the standard RSI by adding several layers of analysis:
Standard RSI Calculation: It calculates the RSI based on a configurable length (default 14 periods) and a user-selected source (default close price).
RSI Bands: It plots horizontal lines at 70 (red, overbought), 50 (yellow, neutral), and 30 (green, oversold) to easily identify extreme RSI levels.
RSI Smoothing with Moving Averages (MAs) and Bollinger Bands (BBs):
You can apply various types of moving averages (SMA, EMA, SMMA, WMA, VWMA) to smooth the RSI line.
If you choose "SMA + Bollinger Bands," the indicator will also plot Bollinger Bands around the smoothed RSI, providing dynamic overbought/oversold levels based on volatility.
The RSI line itself changes color based on whether it's above (green) or below (red) its smoothing MA.
It also fills the area between the RSI and its smoothing MA, coloring it green when RSI is above and red when below.
Bollinger Band Signals: When Bollinger Bands are enabled, the indicator marks "Buy" signals (green arrow up) when the RSI crosses above the lower Bollinger Band and "Sell" signals (red arrow down) when it crosses below the upper Bollinger Band.
Background Coloring: The background of the indicator pane changes to light green when RSI is below 30 (oversold) and light red when RSI is above 70 (overbought), visually highlighting extreme conditions.
Divergence Detection: This is a key feature. The indicator automatically identifies and labels:
Regular Bullish Divergence: Price makes a lower low, but RSI makes a higher low. This often signals a potential reversal to the upside.
Regular Bearish Divergence: Price makes a higher high, but RSI makes a lower high. This often signals a potential reversal to the downside.
Hidden Bullish Divergence: Price makes a higher low, but RSI makes a lower low. This can indicate a continuation of an uptrend.
Hidden Bearish Divergence: Price makes a lower high, but RSI makes a higher high. This can indicate a continuation of a downtrend.
Divergences are visually marked with labels and can trigger alerts.
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.
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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.
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🔧 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.
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🧠 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.
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🔄 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
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🧬 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
LGMM (flat buffers) — multivariate poly + latent statesLGMM POLYNOMIAL BANDS — DISCOVER THE MARKET’S HIDDEN STATES
Overview
Latent-Gaussian-Mixture-Models (LGMMs) view price action as a mix of several invisible regimes: trending up, drifting sideways, sudden volatility spikes, and so on.
A Gaussian Mixture learns these states directly from data and outputs, for every bar, the probability that the market is in each state.
This indicator feeds those probabilities into a rolling polynomial regression that draws a fair-value line, then builds adaptive upper and lower bands.
Band width expands when recent residuals are large *and* when the state mix is uncertain, and contracts when price is calm or one regime clearly dominates.
Crossing back into the band from below generates a buy flag; crossing back into the band from above generates a sell flag (or take-profit for longs).
Key Inputs
Price source – default is Close; you can choose HL2, OHLC4, etc.
Training window (bars) – look-back length for every retrain. 252 bars (one trading year) is a balanced default for US stocks on daily timeframe. Use fewer bars for intraday charts (say 7*24=168 for 1H bars on crypto), more for weekly periods.
Polynomial degree – 1 for a straight trend line, 2 for a curved fit. Curved fits are better when the symbol shows persistent drift.
Hidden states K – number of regimes the mixture tracks (1 to 3). Three states often map well to up-trend, chop, down-trend.
Band width ×σ – multiplier on the entropy-weighted standard deviation. Smaller values (1.5-2) give more trades; larger values (2.5-3) give fewer, higher-conviction trades.
Offline μ,σ pairs (optional) – paste component means and sigmas from an offline LGMM (format: mu1,sigma1;mu2,sigma2;…). Leave blank to let the script use its built-in approximation.
Quick Start
Add the indicator to a chart and wait until the initial Training window has filled.
Watch for green BUY triangles when price closes back above the lower band and red SELL triangles when price closes back below the upper band.
Fine-tune:
– Increase Training window to reduce noise.
– Decrease Band width ×σ for more frequent signals.
– Experiment with Hidden states K; more states capture richer behaviour but need longer windows to stay reliable.
Tips
Bands widen automatically in chaotic periods and tighten when one regime dominates.
Combine with a volume filter or a higher-time-frame trend to reduce whipsaws.
If you already run an LGMM in Python or Matlab, paste its component parameters for a perfect match between your back-test and the TradingView plot.
Works on all markets and time-frames, provided you have at least five times the Training window’s bars in history.
Happy trading!
Ehlers Instantaneous Trendline ATR LevelsOverview
This sophisticated technical analysis tool merges John Ehlers' cutting-edge Instantaneous Trendline methodology with a dynamic ATR-based bands system. The indicator is designed to provide traders with a comprehensive view of market trends while accounting for volatility, making it suitable for both trending and ranging markets. Works on all timeframes and chart types.
Key Features in Detail
1. Ehlers Instantaneous Trendline Implementation
- Advanced algorithm that reduces lag typically associated with moving averages
- Built-in volatility filtering system to minimize false signals
- Adaptive to market conditions through dynamic calculations
- Real-time trend direction identification
2. Multi-layered ATR Band System
- Hierarchical band structure with 18 total bands (9 upper, 9 lower)
- Color-coded visualization system:
Upper bands: Red gradient (darker = further from trendline)
Lower bands: Green gradient (darker = further from trendline)
Central trendline: Yellow for optimal visibility
- Customizable multipliers for each band level
- Independent visibility controls for each band
Configuration Options
Trendline Settings:
- Lower values: More responsive to price changes and faster reacting to break in ATR filter
- Higher values: Smoother trendline with less noise and slower reacting to break in ATR filter
ATR Configuration:
Period: Customizable from 1 to any positive integer
- Longer periods: More stable volatility measurement
- Shorter periods: More reactive to recent volatility changes
Filter Multiplier: Fine-tune volatility filtering
- Higher values: More filtered signals leading to less shift in bands
- Lower values: More sensitive to price movements leading to more band shifts
Practical Applications
1. Trend Analysis
Use the central trendline for primary trend direction
Monitor band crossovers for trend strength confirmation
Track price position relative to bands for trend context
2. Volatility Assessment
Band spacing indicates current market volatility
Width between bands helps identify consolidation vs. expansion phases
Price Extremes
3. Support and Resistance
Each band acts as a dynamic support/resistance level
Multiple timeframe analysis possible adjusting for different timeframe ATR
Red & Green Zone ReversalOverview
The “Red & Green Zone Reversal” indicator is designed to visually highlight potential reversal zones on your chart by using a combination of Bollinger Bands and the Relative Strength Index (RSI).
It overlays on the chart and provides background color cues—red for oversold conditions and green for overbought conditions—along with corresponding alert triggers.
Key Components
Overlay: The indicator is set to overlay the chart, meaning its visual cues (colored backgrounds) are drawn directly on the price chart.
Bollinger Bands Calculation
Period: A 20-period simple moving average (SMA) is calculated from the closing prices.
Standard Deviation Multiplier: A multiplier of 2.0 is applied.
Bands Defined:
Basis: The 20-period SMA.
Deviation: Calculated as 2 times the standard deviation over the same period.
Upper Band: Basis plus the deviation.
Lower Band: Basis minus the deviation.
RSI Calculation
Period: The RSI is computed over a 14-period span using the closing prices.
Thresholds:
Oversold Threshold: 30 (used for the red zone condition).
Overbought Threshold: 70 (used for the green zone condition).
Zone Conditions
Red Zone (Oversold):
Criteria: The price is below the lower Bollinger Band and the RSI is below 30.
Purpose: Highlights a situation where the asset may be deeply oversold, signaling a potential reversal to the upside.
Green Zone (Overbought):
Criteria: The price is above the upper Bollinger Band and the RSI is above 70.
Purpose: Indicates that the asset may be overbought, potentially signaling a reversal to the downside.
Visual and Alert Components
Background Coloring:
Red Background: Applied when the red zone condition is met (using a semi-transparent red).
Green Background: Applied when the green zone condition is met (using a semi-transparent green).
Alerts:
Red Alert: An alert condition titled “Deep Oversold Alert” is triggered with the message “Deep Oversold Signal triggered!” when the red zone criteria are satisfied.
Green Alert: Similarly, an alert condition titled “Deep Overbought Alert” is triggered with the message “Deep Overbought Signal triggered!” when the green zone criteria are met.
Important Disclaimers
Not Financial Advice:
This indicator is provided for informational and analytical purposes only. It does not constitute trading advice or a recommendation to buy or sell any asset. Traders should use it as one of several tools in their analysis and should perform their own due diligence.
Risk Management:
Trading inherently involves risk. Past performance is not indicative of future results. Always implement appropriate risk management and use stop losses where necessary.
Summary
In summary, the “Red & Green Zone Reversal” indicator uses Bollinger Bands and RSI to detect extreme market conditions. It visually marks oversold (red) and overbought (green) conditions directly on the chart and offers alert conditions to help traders monitor these potential reversal points.
Enjoy!!
Dynamic VWAP Levels (V1.0)The script calculates bands around the VWAP (Volume Weighted Average Price) using the Average True Range (ATR) to adjust the levels according to market reality. Buy and sell signals are generated when the price crosses these bands.
Customizable Parameters SmoothingLength (SmoothLength): The period used to smooth the levels. A higher value results in smoother bands that are less susceptible to rapid fluctuations.
Use EMA for smoothing?: Selects between using the Exponential Moving Average (EMA) or the Simple Moving Average (SMA) for smoothing.
ATR Length: The period used to calculate the ATR, which determines the frequency.
ATR Multiplier: A multiplier that adjusts the amplitude of the bands around the VWAP.
How the Script Works Calculating VWAP and Bands: The VWAP is calculated to obtain the volume weighted average price.
Bands are created around the VWAP by adding or subtracting a fraction of the ATR to account for the current market variation.
Smoothing Application: Price levels are smoothed to reduce market noise, allowing for better visualization of trends.
Signal Generation: Buy Signal: Generated when price crosses upwards the smoothed lower band (default dp7_smooth).
Sell Signal: Generated when price crosses downwards the smoothed upper band (default dp1_smooth).
Buy/Sell Signals for CM_Williams_Vix_FixThis script in Pine Script is designed to create an indicator that generates buy and sell signals based on the Williams VIX Fix (WVF) indicator. Here’s a brief explanation of how this script works:
Main Components:
Williams VIX Fix (WVF) – This volatility indicator is calculated using the formula:
WVF
=
(
highest(close, pd)
−
low
highest(close, pd)
)
×
100
WVF=(
highest(close, pd)
highest(close, pd)−low
)×100
where highest(close, pd) represents the highest closing price over the period pd, and low represents the lowest price over the same period.
Bollinger Bands are used to determine levels of overbought and oversold conditions. They are constructed around the moving average (SMA) of the WVF value using standard deviation (SD).
Ranges based on percentiles help identify extreme levels of WVF values to spot entry and exit points.
Buy and sell signals are generated when the WVF crosses the Bollinger Bands lines or reaches the ranges based on percentiles.
Adjustable Parameters:
LookBack Period Standard Deviation High (pd): The lookback period for calculating the highest closing price.
Bolinger Band Length (bbl): The length of the period for constructing the Bollinger Bands.
Bollinger Band Standard Devaition Up (mult): The multiplier for the standard deviation used for the upper Bollinger Band.
Look Back Period Percentile High (lb): The lookback period for calculating maximum and minimum WVF values.
Highest Percentile (ph): The percentile threshold for determining the high level.
Lowest Percentile (pl): The percentile threshold for determining the low level.
Show High Range (hp): Option to display the range based on percentiles.
Show Standard Deviation Line (sd): Option to display the standard deviation line.
Signals:
Buy Signal: Generated when the WVF crosses above the lower Bollinger Band or falls below the lower boundary of the percentile-based range.
Sell Signal: Generated when the WVF crosses below the upper Bollinger Band or rises above the upper boundary of the percentile-based range.
These signals are displayed as triangles below or above the candles respectively.
Application:
The script can be used by traders to analyze market conditions and make buying or selling decisions based on volatility and price behavior.
Adaptive Kalman Trend Filter (Zeiierman)█ Overview
The Adaptive Kalman Trend Filter indicator is an advanced trend-following tool designed to help traders accurately identify market trends. Utilizing the Kalman Filter—a statistical algorithm rooted in control theory and signal processing—this indicator adapts to changing market conditions, smoothing price data to filter out noise. By focusing on state vector-based calculations, it dynamically adjusts trend and range measurements, making it an excellent tool for both trend-following and range-based trading strategies. The indicator's adaptive nature is enhanced by options for volatility adjustment and three unique Kalman filter models, each tailored for different market conditions.
█ How It Works
The Kalman Filter works by maintaining a model of the market state through matrices that represent state variables, error covariances, and measurement uncertainties. Here’s how each component plays a role in calculating the indicator’s trend:
⚪ State Vector (X): The state vector is a two-dimensional array where each element represents a market property. The first element is an estimate of the true price, while the second element represents the rate of change or trend in that price. This vector is updated iteratively with each new price, maintaining an ongoing estimate of both price and trend direction.
⚪ Covariance Matrix (P): The covariance matrix represents the uncertainty in the state vector’s estimates. It continuously adapts to changing conditions, representing how much error we expect in our trend and price estimates. Lower covariance values suggest higher confidence in the estimates, while higher values indicate less certainty, often due to market volatility.
⚪ Process Noise (Q): The process noise matrix (Q) is used to account for uncertainties in price movements that aren’t explained by historical trends. By allowing some degree of randomness, it enables the Kalman Filter to remain responsive to new data without overreacting to minor fluctuations. This noise is particularly useful in smoothing out price movements in highly volatile markets.
⚪ Measurement Noise (R): Measurement noise is an external input representing the reliability of each new price observation. In this indicator, it is represented by the setting Measurement Noise and determines how much weight is given to each new price point. Higher measurement noise makes the indicator less reactive to recent prices, smoothing the trend further.
⚪ Update Equations:
Prediction: The state vector and covariance matrix are first projected forward using a state transition matrix (F), which includes market estimates based on past data. This gives a “predicted” state before the next actual price is known.
Kalman Gain Calculation: The Kalman gain is calculated by comparing the predicted state with the actual price, balancing between the covariance matrix and measurement noise. This gain determines how much of the observed price should influence the state vector.
Correction: The observed price is then compared to the predicted price, and the state vector is updated using this Kalman gain. The updated covariance matrix reflects any adjustment in uncertainty based on the latest data.
█ Three Kalman Filter Models
Standard Model: Assumes that market fluctuations follow a linear progression without external adjustments. It is best suited for stable markets.
Volume Adjusted Model: Adjusts the filter sensitivity based on trading volume. High-volume periods result in stronger trends, making this model suitable for volume-driven assets.
Parkinson Adjusted Model: Uses the Parkinson estimator, accounting for volatility through high-low price ranges, making it effective in markets with high intraday fluctuations.
These models enable traders to choose a filter that aligns with current market conditions, enhancing trend accuracy and responsiveness.
█ Trend Strength
The Trend Strength provides a visual representation of the current trend's strength as a percentage based on oscillator calculations from the Kalman filter. This table divides trend strength into color-coded segments, helping traders quickly assess whether the market is strongly trending or nearing a reversal point. A high trend strength percentage indicates a robust trend, while a low percentage suggests weakening momentum or consolidation.
█ Trend Range
The Trend Range section evaluates the market's directional movement over a specified lookback period, highlighting areas where price oscillations indicate a trend. This calculation assesses how prices vary within the range, offering an indication of trend stability or the likelihood of reversals. By adjusting the trend range setting, traders can fine-tune the indicator’s sensitivity to longer or shorter trends.
█ Sigma Bands
The Sigma Bands in the indicator are based on statistical standard deviations (sigma levels), which act as dynamic support and resistance zones. These bands are calculated using the Kalman Filter's trend estimates and adjusted for volatility (if enabled). The bands expand and contract according to market volatility, providing a unique visualization of price boundaries. In high-volatility periods, the bands widen, offering better protection against false breakouts. During low volatility, the bands narrow, closely tracking price movements. Traders can use these sigma bands to spot potential entry and exit points, aiming for reversion trades or trend continuation setups.
Trend Based
Volatility Based
█ How to Use
Trend Following:
When the Kalman Filter is green, it signals a bullish trend, and when it’s red, it indicates a bearish trend. The Sigma Cloud provides additional insights into trend strength. In a strong bullish trend, the cloud remains below the Kalman Filter line, while in a strong bearish trend, the cloud stays above it. Expansion and contraction of the Sigma Cloud indicate market momentum changes. Rapid expansion suggests an impulsive move, which could either signal the continuation of the trend or be an early sign of a possible trend reversal.
Mean Reversion: Watch for prices touching the upper or lower sigma bands, which often act as dynamic support and resistance.
Volatility Breakouts: Enable volatility-adjusted sigma bands. During high volatility, watch for price movements that extend beyond the bands as potential breakout signals.
Trend Continuation: When the Kalman Filter line aligns with a high trend strength, it signals a continuation in that direction.
█ Settings
Measurement Noise: Adjusts how sensitive the indicator is to price changes. Higher values smooth out fluctuations but delay reaction, while lower values increase sensitivity to short-term changes.
Kalman Filter Model: Choose between the standard, volume-adjusted, and Parkinson-adjusted models based on market conditions.
Band Sigma: Sets the standard deviation used for calculating the sigma bands, directly affecting the width of the dynamic support and resistance.
Volatility Adjusted Bands: Enables bands to dynamically adapt to volatility, increasing their effectiveness in fluctuating markets.
Trend Strength: Defines the lookback period for trend strength calculation. Shorter periods result in more responsive trend strength readings, while longer periods smooth out the calculation.
Trend Range: Specifies the lookback period for the trend range, affecting the assessment of trend stability over time.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
