MTF MA Ribbon and Bands + BB, Gaussian F. and R. VWAP with StDev█ Multi Timeframe Moving Average Ribbon and Bands + Bollinger Bands, Gaussian Filter and Rolling Volume Weighted Average Price with Standard Deviation Bands
Up to 9 moving averages can be independently applied.
The length , type and timeframe of each moving average are configurable .
The lines, colors and background fill are customizable too.
This script can also display:
Moving Average Bands
Bollinger Bands
Gaussian Filter
Rolling VWAP and Standard Deviation Bands
Types of Moving Averages:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Smoothed Moving Average (SMMA)
Weighted Moving Average (WMA)
Volume Weighted Moving Average (VWMA)
Least Squares Moving Average (LSMA)
Hull Moving Average (HMA)
Arnaud Legoux Moving Average (ALMA)
█ Moving Average
Moving Averages are price based, lagging (or reactive) indicators that display the average price of a security over a set period of time.
A Moving Average is a good way to gauge momentum as well as to confirm trends, and define areas of support and resistance.
█ Bollinger Bands
Bollinger Bands consist of a band of three lines which are plotted in relation to security prices.
The line in the middle is usually a Simple Moving Average (SMA) set to a period of 20 days (the type of trend line and period can be changed by the trader, a 20 day moving average is by far the most popular).
The SMA then serves as a base for the Upper and Lower Bands which are used as a way to measure volatility by observing the relationship between the Bands and price.
█ Gaussian Filter
Gaussian filter can be used for smoothing.
It rejects high frequencies (fast movements) better than an EMA and has lower lag.
A Gaussian filter is one whose transfer response is described by the familiar Gaussian bell-shaped curve.
In the case of low-pass filters, only the upper half of the curve describes the filter.
The use of gaussian filters is a move toward achieving the dual goal of reducing lag and reducing the lag of high-frequency components relative to the lag of lower-frequency components.
█ Rolling VWAP
The typical VWAP is designed to be used on intraday charts, as it resets at the beginning of the day.
Such VWAPs cannot be used on daily, weekly or monthly charts. Instead, this rolling VWAP uses a time period that automatically adjusts to the chart's timeframe.
You can thus use the rolling VWAP on any chart that includes volume information in its data feed.
Because the rolling VWAP uses a moving window, it does not exhibit the jumpiness of VWAP plots that reset.
Made with the help from scripts of: adam24x, VishvaP, loxx and pmk07.
Cerca negli script per "bands"
Mobo BandsThis indicator is the Mobo Bands (Momentum Breakout Bands). These bands are bollinger bands that have an adjusted standard deviation. There are Buy signals when it has momentum breakouts above the bands for moves to the upside and Sell signals when it has momentum breakouts below the bands for moves to the downside. The bands simply suggest that all markets have periods of chop which we all know to be true. While the price is inside the bands it is said to be trendless. Once the breakouts happen you can take trades in the breakout direction. I like to use these to swing trade options on the hourly timeframe but the bands should work on most instruments and timeframes. I like to use it to take swings on SPY on the 1 hour chart for entries and use the Daily chart for trend confirmation.
Dual Bollinger BandsIndicator Name:
Double Bollinger Bands (2-9 & 2-20)
Description:
This indicator plots two sets of Bollinger Bands on a single chart for enhanced volatility and trend analysis:
Fast Bands (2-9 Length) – Voilet
More responsive to short-term price movements.
Useful for spotting quick reversals or scalping opportunities.
Slow Bands (2-20 Length) – Black
Smoother, trend-following bands for longer-term context.
Helps confirm broader market direction.
Both bands use the standard settings (2 deviations, SMA basis) for consistency. The transparent fills improve visual clarity while keeping the chart uncluttered.
Use Cases:
Trend Confirmation: When both bands expand together, it signals strong momentum.
Squeeze Alerts: A tight overlap suggests low volatility before potential breakouts.
Multi-Timeframe Analysis: Compare short-term vs. long-term volatility in one view.
How to Adjust:
Modify lengths (2-9 and 2-20) in the settings.
Change colors or transparency as needed.
Why Use This Script?
No Repainting – Uses standard Pine Script functions for reliability.
Customizable – Easy to tweak for different trading styles.
Clear Visuals – Color-coded bands with background fills for better readability.
Ideal For:
Swing traders, day traders, and volatility scalpers.
Combining short-term and long-term Bollinger Band strategies.
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.
Volatility BandsThe Volatility Bands script is a custom indicator designed to help traders visualize volatility levels in the market. It calculates dynamic bands around a central moving average, providing insights into potential support and resistance levels based on recent price action.
The script calculates multiple volatility bands (u0, u1, u2, d0, d1, d2) that adjust based on recent price movements. The outer bands (u2 and d2) represent extreme volatility levels, while the inner bands (u0, u1, d0, d1) indicate more immediate support and resistance.
Look for price reactions at the band levels. A touch of the upper bands may indicate overbought conditions, while a touch of the lower bands may indicate oversold conditions.
Central Moving Average: A smoothed moving average that adapts to price changes, providing a clear trend direction.
The script has no input parameters.
Script Functions:
erf(x): Calculates the error function for a given input x. Used in the calculation of the smoothing factor for the UMA.
uma(input): Provides a smoothed average that adapts to recent price changes, reducing lag compared to traditional moving averages.
dev(input, mu): Used to calculate the volatility bands around the central moving average.
Bollinger Bands cross %The BB strategy (Bollinger Bands strategy) on TradingView utilizes the Bollinger Bands indicator to help traders identify market volatility and potential entry points. The Bollinger Bands indicator consists of three main components:
Middle Band: This is the simple moving average (SMA), usually calculated over a 20-period. It represents the average price over a specific period.
Upper Band and Lower Band: These bands are created by adding and subtracting a multiple of the standard deviation (typically 2) from the middle band. The upper and lower bands help determine the level of price volatility.
How the BB Strategy Works:
Break above the Upper Band: When the price moves above the upper band, it might signal that the market is in an "overbought" condition. This could be a sign to consider selling, but it could also continue if the trend is strong.
Break below the Lower Band: When the price moves below the lower band, it might signal that the market is in an "oversold" condition, which could be a signal to buy if the trend is reversing.
Squeeze (Coiling): When the Bollinger Bands contract, often referred to as a "squeeze," it indicates that the market may be preparing for a strong price move. This is a critical signal in the BB strategy because the narrowing bands signify low volatility and a potential breakout in price.
Specific Strategy:
Buy when price touches the lower band and shows signs of reversal (bullish reversal): If the price touches the lower band, you might wait for a reversal signal, such as a bullish candlestick pattern or confirmation from other indicators like RSI or MACD, indicating oversold conditions.
Sell when price touches the upper band and shows signs of reversal (bearish reversal): Similarly, when the price touches the upper band, you could wait for a bearish reversal signal, such as a bearish candlestick pattern or confirmation from other indicators, and then sell.
Trend-following when bands are expanding: If the Bollinger Bands are expanding and the price continues in the same direction, it could signal a trend-following opportunity.
Bollinger Bands with Squeeze and SMA Indicator Description: BB+SMA
Overview:
Bollinger Bands (BB): Computes and plots three bands based on a selected moving average type (SMA, EMA, SMMA (RMA), WMA, VWMA) and standard deviation multiplier. The bands indicate potential support and resistance levels relative to price volatility.
Squeeze Condition: Detects periods of low volatility (squeeze) when the distance between the upper and lower Bollinger Bands narrows significantly. This condition can signal potential price breakouts.
Simple Moving Average (SMA): Calculates and plots a simple moving average based on user-defined length. It smooths price data to highlight trends and potential reversals.
Smoothing Line: Further enhances the SMA by applying different smoothing methods (SMA, EMA, SMMA (RMA), WMA, VWMA) over a specified smoothing length. It helps in identifying smoother trends and changes in direction.
Key Components:
Inputs: Users can adjust parameters such as Bollinger Bands length, type of moving average, standard deviation multiplier, squeeze condition length, squeeze threshold percentage, SMA length, smoothing method, and smoothing length.
Plotting: Displays the Bollinger Bands (basis, upper, lower), SMA, squeeze condition bands (basis, upper, lower), and a smoothing line on the chart.
Visualization: Utilizes different colors and line styles for clarity in visualizing each component's plot on the chart.
Purpose:
Helps traders identify potential price volatility, trend reversals, and breakout opportunities using Bollinger Bands, SMA, squeeze conditions, and smoothed moving averages.
Enhances technical analysis by providing clear visual cues for trend strength and potential entry/exit points based on the specified parameters.
Conclusion:
The "BB+SMA" indicator integrates multiple technical analysis tools into a single script, offering traders a comprehensive approach to analyzing price movements and making informed trading decisions directly on TradingView charts.
Bollinger Bands - Breakout StrategyThe Bollinger Bands - Breakout Strategy is a trend-following optimized for short-term trading in the crypto market. This strategy employs the Bollinger Bands, a widely recognized technical indicator, as its primary instrument for pinpointing potential trades. It is capable of executing both long and short positions, depending on whether the market is in a spot or futures, and is particularly effective in trending markets.
The strategy boasts a high degree of configurability, allowing users to set the Bollinger Bands period and deviation, trend filter, volatility filter, trade direction filter, rate of change filter, and date filter. Furthermore, it offers options for Take Profit, Stop Loss, and Trailing Stop for both long and short positions, ensuring a comprehensive risk management approach. The inclusion of a maximum intraday loss feature adds another layer of protection, making this strategy a valuable tool for traders seeking a professional and adaptable trading system.
Name : Bollinger Bands - Breakout Strategy
Category : Trend Follower based on Bollinger Bands
Operating mode : Long and Short on Futures or Long on Spot
Trade duration : Intraday
Timeframe : 2H, 3H, 4H, 5H
Market : Crypto
Suggested usage : Trending Markets
Entry : When the price crosses above or below the Bollinger Bands
Exit : Opposite Cross or Profit target, Trailing stop or Stop loss
Configuration :
- Bollinger Bands period and deviation
- Trend Filter
- Volatility Filter
- Trade direction filter
- Rate of Change filter
- Date Filter (for backtesting purposes)
- Take Profit, Stop Loss and Trailing Stop for long and short positions
- Risk Management: Max Intraday Loss
Backtesting :
⁃ Exchange: BINANCE
⁃ Pair: BTCUSDT.P
⁃ Timeframe: 4H
⁃ Fee: 0.025%
⁃ Slippage: 1
- Initial Capital: 10000 USDT
- Position sizing: 10% of Equity
- Start : 2019-09-19 (Out Of Sample from 2022-12-23)
- Bar magnifier: on
Credits :
- LucF of Pine Coders for f_security function to avoid repainting using security.
- QuantNomad for Monthly Table.
Disclaimer : Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Thanks for your attention, happy to support the TradingView community.
Extended Recursive Bands StrategyThe original indicator was created by alexgrover .
All credit goes to alexgrover for creating the indicator that this strategy uses.
This strategy was posted because there were multiple requests for it, and no strategy based on this indicator exists yet.
The Recursive Bands Indicator, an indicator specially created to be extremely efficient, I think you already know that calculation time is extra important in algorithmic trading, and this is the principal motivation for the creation of the proposed indicator. Originally described in Alex's paper "Pierrefeu, Alex (2019): Recursive Bands - A New Indicator For Technical Analysis", the indicator framework has been widely used in his previous uploaded indicators, however it would have been a shame to not upload it, however user experience being a major concern for me, I decided to add extra options, which explain the term "extended".
The Indicator
The indicator displays one upper and one lower band, every common usages applied to bands indicators such as support/resistance , breakout, trailing stop, etc, can also be applied to this one. Length controls how reactive the bands are, higher values will make the bands cross the price less often.
In order to provide more flexibility for the user alexgrover added the option to use various methods for the calculation of the indicator, therefore the indicator can use the average true range , standard deviation, average high-low range, and one totally exclusive method specially designed for this indicator.
Added logic:
We have implemented a logic that checks whether the bands have been following in the same direction for a set amount of bars. This logic must be true before it can enter trades. This is completely new code that was written by us entirely, and it makes a huge difference on strategy performance.
Strategy Long conditions:
1 — Price low is below the the lower band.
2 — The lower band keeps increasing in value until the 'lookback' setting amount of bars is reached.
Strategy Short conditions:
1 — Price high is above the upper band.
2 — The upper band keeps decreasing in value until the 'lookback' setting amount of bars is reached.
Strategy Properties:
We have set a default commission of 0.06% because these are Bybit's fees. The strategy uses an order size of 10% of equity, since drawdown is very low like this. We also use a 10 tick slippage to keep results realistic and account for this. All other settings were left as default apart from initial capital, just to decrease the size of the numbers.
Garman-Klass-Yang-Zhang Historical Volatility Bands [Loxx]Garman-Klass-Yang-Zhang Historical Volatility Bands are constructed using:
Average as the middle line.
Upper and lower bands using the Garman-Klass-Yang-Zhang Historical Volatility Bands for bands calculation.
What is Garman-Klass-Yang-Zhang Historical Volatility?
Yang and Zhang derived an extension to the Garman Klass historical volatility estimator that allows for opening jumps. It assumes Brownian motion with zero drift. This is currently the preferred version of open-high-low-close volatility estimator for zero drift and has an efficiency of 8 times the classic close-to-close estimator. Note that when the drift is nonzero, but instead relative large to the volatility, this estimator will tend to overestimate the volatility. The Garman-Klass-Yang-Zhang Historical Volatility calculation is as follows:
GKYZHV = sqrt((Z/n) * sum((log(open(k)/close(k-1)))^2 + (0.5*(log(high(k)/low(k)))^2) - (2*log(2) - 1)*(log(close(k)/open(2:end)))^2))
The color of the middle line, unlike the bands colors, has 3 colors. When colors of the bands are the same, then the middle line has the same color, otherwise it's white.
Included
Alerts
Signals
Loxx's Expanded Source Types
Bar coloring
Related Indicators
Garman & Klass Estimator Historical Volatility Bands
High/Low Historical Volatility Bands [Loxx]High/Low Historical Volatility Bands are constructed using:
Average as the middle line.
Upper and lower bands using the Historical Volatility high/low (instead of "regular" Historical Volatility) for bands calculation.
What is Historical Volatility?
Historical Volatility (HV) is a statistical measure of the dispersion of returns for a given security or market index over a given period of time. Generally, this measure is calculated by determining the average deviation from the average price of a financial instrument in the given time period. Using standard deviation is the most common, but not the only, way to calculate Historical Volatility .
The higher the Historical Volatility value, the riskier the security. However, that is not necessarily a bad result as risk works both ways - bullish and bearish , i.e: Historical Volatility is not a directional indicator and should not be used as other directional indicators are used. Use to to determine the rising and falling price change volatility .
SH is stock's High price in t day.
SL is stock's Low price in t day.
High/Low Return (xt^HL) is calculated as the natural logarithm of the ratio of a stock's High price to stock's Low price.
Return:
And Parkinson's number: 1 / (4 * math.log(2)) * 252 / n * Σ (n, t =1) {math.log(Ht/Lt)^2}
An important use of the Parkinson's number is the assessment of the distribution prices during the day as well as a better understanding of the market dynamics. Comparing the Parkinson's number and periodically sampled volatility helps traders understand the tendency towards mean reversion in the market as well as the distribution of stop-losses.
The color of the middle line, unlike the bands colors, has 3 colors. When colors of the bands are the same, then the middle line has the same color, otherwise it's white.
Included
Alerts
Signals
Loxx's Expanded Source Types
Bar coloring
Related indicators:
Parkinson's Historical Volatility Bands
Historical Volatility Bands
MTF EMA Ribbon & Bands + BBMulti Timeframe Exponential Moving Average Ribbon & Bands + Boillinger Bands
I used the script "EMA Ribbon - low clutter, configurable " by adam24x, I made some color change and I added a few indicators (Boillinger Bands, EMA on multi timeframe and EMA bands from "34 EMA Bands " by VishvaP).
The script can display various EMA from the chart's timeframe but also EMA from other timeframes.
Bollinger Bands and EMA bands can also be added to the chart.
Trending Bollinger Bands by SiddWolfBollinger Bands are mostly used for trend reversal. I believe they should be used for Trend Continuation and Trend Confirmation.
In this Trending Bollinger Bands script you will see two bands drawn on chart. The Upper band is suggestive of Uptrend and Lower Band is suggestive of Downtrend Market. It just provides the guidance of where the market is now and where it is headed. It is not to be used as a standalone indicator. Use this to confirm your hypothesis of Uptrend or Downtrend.
Bollinger Bands Trend
When the price crosses the moving average it is interpreted as the price is gonna continue in that direction. But most of the time it is a fake breakout. With this script you get an additional confirmation so that you know it is not a fake breakout and the price have caught the trend.
Bollinger Bands Reversal:
This indicator can also work for reversal. For example when price closes outside the outer bands, it is most likely that the trend is gonna reverse. Don't just enter the trade wait for some other confirmation as reversal trading is more complicated.
Confluence:
Confluence is the key factor for profitable trading. Don't use this indicator as standalone indicator instead combine it with other indicators and price action. Like the divergence occurring when the price is outside the bands is suggestive of trend reversal. I have created a non-delay, non-repaint indicator for finding divergence. I'd soon publish that script. Stay tuned.
Settings is the Key:
Try to play around with the settings. It is a simple yet effective indicator. Change the moving average type or length. I've found moving average RMA or WMA works better than SMA. Find the best setting that works with your setup. Set the Band Source as High/Low to make the outer bands more extreme.
Conclusion:
This is my first script but it isn't my last. I've created quite a few gems that I'm gonna publish soon. If you have any questions or suggestions feel free to comment below. I'd love to connect with you. Thank you.
Weighted Regression Bands (Zeiierman)█ Overview
Weighted Regression Bands is a precision-engineered trend and volatility tool designed to adapt to the real market structure instead of reacting to price noise.
This indicator analyzes Weighted High/Low medians and applies user-selectable smoothing methods — including Kalman Filtering, ALMA, and custom Linear Regression — to generate a Fair Value line. Around this, it constructs dynamic standard deviation bands that adapt in real-time to market volatility.
The result is a visually clean and structurally intelligent trend framework suitable for breakout traders, mean reversion strategies, and trend-driven analysis.
█ How It Works
⚪ Structural High/Low Analysis
At the heart of this indicator is a custom high/low weighting system. Instead of using just the raw high or low values, it calculates a midline = (high + low) / 2, then applies one of three weighting methods to determine which price zones matter most.
Users can select the method using the “Weighted HL Method” setting:
Simple
Selects the single most dominant median (highest or lowest) in the lookback window. Ideal for fast, reactive signals.
Advanced
Ranks each bar based on a composite score: median × range × recency. This method highlights structurally meaningful bars that had both volatility and recency. A built-in Kalman filter is applied for extra stability.
Smooth
Blends multiple bars into a single weighted average using smoothed decay and range. This provides the softest and most stable structural response.
⚪ Smoothing Methods (ALMA / Linear Regression)
ALMA provides responsive, low-lag smoothing for fast trend reading.
Linear Regression projects the Fair Value forward, ideal for trend modeling.
⚪ Kalman Smoothing Filter
Before trend calculations, the indicator applies an optional Kalman-style smoothing filter. This helps:
Reduce choppy false shifts in trend,
Retain signal clarity during volatile periods,
Provide stability for long-term setups.
⚪ Deviation Bands (Dynamic Volatility Envelopes)
The indicator builds ±1, ±2, and ±3 standard deviation bands around the fair value line:
Calculated from the standard deviation of price,
Bands expand and contract based on recent volatility,
Visualizes potential overbought/oversold or trending conditions.
█ How to Use
⚪ Trend Trading & Filtering
Use the Fair Value line to identify the dominant direction.
Only trade in the direction of the slope for higher probability setups.
⚪ Volatility-Based Entries
Watch for price reaching outer bands (+2σ, +3σ) for possible exhaustion.
Mean reversion entries become higher quality when far from Fair Value.
█ Settings
Length – Lookback for Weighted HL and trend smoothing
Deviation Multiplier – Controls how wide the bands are from the fair value line
Method – Choose between ALMA or Linear Regression smoothing
Smoothing – Strength of Kalman Filter (1 = none, <1 = stronger smoothing)
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. 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.
Dynamic RSI Regression Bands (Zeiierman)█ Overview
The Dynamic RSI Regression Bands (Zeiierman) is a regression channel tool that dynamically resets based on RSI overbought and oversold conditions. It adapts to trend shifts in real time, creating a highly responsive regression framework that visualizes market sentiment and directional momentum with every RSI-triggered event.
Unlike static regression models, this indicator recalibrates its slope and deviation bands only after the RSI crosses predefined thresholds, helping traders pinpoint new phases of momentum, exhaustion, or reversal.
You’re not just measuring the trend — you’re tracking when and where the trend deserves to be re-evaluated.
█ The Assumption:
"A major momentum shift (RSI crossing OB/OS) signals a potential regime change, and thus, the trend model should be recalibrated from that point."
Instead of using a fixed-length regression (which assumes trend relevance over a static window), this script resets the regression calculation every time RSI crosses into extreme territory. The underlying idea is that extreme RSI levels often represent emotional peaks in market behavior and are statistically likely to be followed by a new price structure.
█ How It Works
⚪ RSI-Based Channel Reset
RSI is monitored continuously
If RSI crosses above the Overbought level, the indicator resets and starts a new regression channel
If RSI crosses below the Oversold level, the same reset logic applies
These events act as “anchor points” for dynamic trend analysis
⚪ Regression Channel Logic
A custom linear regression is calculated from the RSI reset point forward
The lookback grows with each bar after the reset, up to a user-defined max
Regression lines are drawn from the reset point to the current bar
⚪ Standard Deviation Bands
Upper and lower bands are plotted around the regression line using the standard deviation
These serve as dynamic volatility envelopes, great for spotting breakouts or reversals
⚪ Rejection Markers
If price hits the upper/lower band and then closes back inside it, a rejection marker is plotted
Helps visualize failed breakouts and areas of absorption or reversal pressure
█ How to Use
⚪ Detect Trend Shifts
Use the RSI resets to identify when the trend might be starting fresh.
⚪ Watch the Bands for Volatility Extremes
Use the outer bands as soft areas of potential reversal or momentum breakout.
⚪ Spot Rejections for Potential Entry Signals
If price moves outside a band but then quickly returns inside, it often means the breakout failed, and price may reverse.
█ Settings Explained
RSI Length – How many bars RSI uses. Shorter = faster.
OB / OS Levels – Crossing these triggers a regression reset.
Base Regression Length – Max number of bars regression can use post-reset.
StdDev Multiplier – Controls band width from the regression line.
Min Bars After Reset – Ensures channel doesn’t form immediately; waits for structure.
Show Reset Markers – Triangles mark where RSI crossed OB/OS.
Show Rejection Markers – Circles mark where the price rejected the channel edge.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. 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.
Adaptive Bollinger BandsAdaptive Bollinger Bands
This indicator displays Bollinger Bands with parameters that dynamically adjust based on market volatility. Unlike standard Bollinger Bands with fixed parameters, this version adaptively modifies both the period and standard deviation multiplier in real-time based on measured market conditions.
Key Features
Dynamic adjustment of period and standard deviation based on normalized volatility
Color-coded visualization of current volatility regime (expanding, normal, contracting)
Integration with Keltner Channels for band refinement
Bandwidth analysis for volatility regime identification
Optional on-chart parameter labels showing current settings
Band cross alerts and visual markers
Volatility Visualization
The indicator uses color-coding to display different volatility regimes:
Red: Expanding volatility regime (higher measured volatility)
Blue: Normal volatility regime (average measurements)
Green: Contracting volatility regime (lower measured volatility)
Technical Information
The indicator calculates volatility by analyzing price returns over a configurable lookback period (default 50 bars). The standard deviation of returns is normalized against historical extremes to create an adaptive scaling factor.
Band adaptation occurs through two primary mechanisms:
1. Period adjustment: Higher volatility uses shorter periods (more responsive), while lower volatility uses longer periods (more stable)
2. Standard deviation multiplier adjustment: Higher volatility increases the multiplier (wider bands), while lower volatility decreases it (tighter bands)
The middle band uses a simple moving average with the adaptive period. Additional refinement occurs through Keltner Channel integration, which can tighten bands when contained within Keltner boundaries.
Volatility regimes are determined by analyzing Bollinger Bandwidth relative to its recent history, providing contextual information about the current market state.
Settings Customization
The indicator provides extensive customization options:
- Base parameters (period and standard deviation)
- Adaptive range limits (min/max period and standard deviation)
- Keltner Channel parameters for band refinement
- Bandwidth analysis settings
- Display options for visual elements
Limitations and Considerations
All technical indicators have inherent limitations and should not be used in isolation
Past performance does not guarantee future results
The indicator requires sufficient historical data for proper volatility normalization
Smaller timeframes may produce more noise in the adaptive calculations
Parameters may require adjustment for different markets and trading styles
Band crosses are not trading signals on their own and should be evaluated with other factors
This indicator is designed to provide objective information about market volatility conditions and potential support/resistance zones. Always combine with other analysis methods within a comprehensive trading approach.
Bollinger Bands + EMA 200 + EMA 50This indicator combines three technical analysis tools: the Bollinger Bands (BB), and two Exponential Moving Averages (EMA) with periods of 200 and 50.
Bollinger Bands (BB): This indicator consists of three lines—the middle line being a simple moving average (SMA), and the upper and lower bands representing two standard deviations above and below the SMA. The width of the bands indicates market volatility, with wider bands signifying higher volatility and narrower bands indicating lower volatility.
Exponential Moving Averages (EMA 200 and EMA 50): The EMA is a type of moving average that gives more weight to recent prices, making it more responsive to price changes than the simple moving average. The EMA 200 is considered a long-term trend indicator, often used to identify the overall direction of the market. The EMA 50 is a medium-term trend indicator, helping to spot more immediate market trends. Crossovers between these two EMAs (such as when EMA 50 crosses above EMA 200) are commonly used as buy or sell signals, with the idea that a short-term trend shift is occurring.
By combining these three indicators, this custom Pine Script aims to give a comprehensive view of the market conditions, helping traders to understand both the volatility (via BB), the long-term market trend (via EMA 200), and the medium-term trend (via EMA 50). The interaction between the price and these indicators, along with crossovers, can be used to identify potential entry and exit points.
Bollingers Bands Fibonacci ratios_copy of FOMOBollinger Bands Fibonacci Ratios (FiBB)
This TradingView script is a powerful tool that combines the classic Bollinger Bands with Fibonacci ratios to help traders identify potential support and resistance zones based on market volatility.
Key Features:
Dynamic Fibonacci Levels: The script calculates additional levels around a Simple Moving Average (SMA) using Fibonacci ratios (default: 1.618, 2.618, and 4.236). These levels adapt to market volatility using the Average True Range (ATR).
Customizable Parameters: Users can modify the length of the SMA and the Fibonacci ratios to fit their trading strategy and time frame.
Visual Representation: The indicator plots three upper and three lower bands, with color-coded transparency for easy interpretation.
Central SMA Line: The core SMA line provides a baseline for price movement and trend direction.
Shaded Range: The script visually fills the area between the outermost bands to highlight the overall range of price action.
How to Use:
Use the upper bands as potential resistance zones and the lower bands as potential support zones.
Look for price interactions with these levels to identify opportunities for breakout, trend continuation, or reversal trades.
Combine with other indicators or price action analysis to enhance decision-making.
This script is ideal for traders who want a unique blend of Fibonacci-based analysis and Bollinger Bands to better navigate market movements.
Bollinger Bands Enhanced StrategyOverview
The common practice of using Bollinger bands is to use it for building mean reversion or squeeze momentum strategies. In the current script Bollinger Bands Enhanced Strategy we are trying to combine the strengths of both strategies types. It utilizes Bollinger Bands indicator to buy the local dip and activates trailing profit system after reaching the user given number of Average True Ranges (ATR). Also it uses 200 period EMA to filter trades only in the direction of a trend. Strategy can execute only long trades.
Unique Features
Trailing Profit System: Strategy uses user given number of ATR to activate trailing take profit. If price has already reached the trailing profit activation level, scrip will close long trade if price closes below Bollinger Bands middle line.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Major Trend Filter: Strategy utilizes 100 period EMA to take trades only in the direction of a trend.
Flexible Risk Management: Users can choose number of ATR as a stop loss (by default = 1.75) for trades. This is flexible approach because ATR is recalculated on every candle, therefore stop-loss readjusted to the current volatility.
Methodology
First of all, script checks if currently price is above the 200-period exponential moving average EMA. EMA is used to establish the current trend. Script will take long trades on if this filtering system showing us the uptrend. Then the strategy executes the long trade if candle’s low below the lower Bollinger band. To calculate the middle Bollinger line, we use the standard 20-period simple moving average (SMA), lower band is calculated by the substruction from middle line the standard deviation multiplied by user given value (by default = 2).
When long trade executed, script places stop-loss at the price level below the entry price by user defined number of ATR (by default = 1.75). This stop-loss level recalculates at every candle while trade is open according to the current candle ATR value. Also strategy set the trailing profit activation level at the price above the position average price by user given number of ATR (by default = 2.25). It is also recalculated every candle according to ATR value. When price hit this level script plotted the triangle with the label “Strong Uptrend” and start trail the price at the middle Bollinger line. It also started to be plotted as a green line.
When price close below this trailing level script closes the long trade and search for the next trade opportunity.
Risk Management
The strategy employs a combined and flexible approach to risk management:
It allows positions to ride the trend as long as the price continues to move favorably, aiming to capture significant price movements. It features a user-defined ATR stop loss parameter to mitigate risks based on individual risk tolerance. By default, this stop-loss is set to a 1.75*ATR drop from the entry point, but it can be adjusted according to the trader's preferences.
There is no fixed take profit, but strategy allows user to define user the ATR trailing profit activation parameter. By default, this stop-loss is set to a 2.25*ATR growth from the entry point, but it can be adjusted according to the trader's preferences.
Justification of Methodology
This strategy leverages Bollinger bangs indicator to open long trades in the local dips. If price reached the lower band there is a high probability of bounce. Here is an issue: during the strong downtrend price can constantly goes down without any significant correction. That’s why we decided to use 200-period EMA as a trend filter to increase the probability of opening long trades during major uptrend only.
Usually, Bollinger Bands indicator is using for mean reversion or breakout strategies. Both of them have the disadvantages. The mean reversion buys the dip, but closes on the return to some mean value. Therefore, it usually misses the major trend moves. The breakout strategies usually have the issue with too high buy price because to have the breakout confirmation price shall break some price level. Therefore, in such strategies traders need to set the large stop-loss, which decreases potential reward to risk ratio.
In this strategy we are trying to combine the best features of both types of strategies. Script utilizes ate ATR to setup the stop-loss and trailing profit activation levels. ATR takes into account the current volatility. Therefore, when we setup stop-loss with the user-given number of ATR we increase the probability to decrease the number of false stop outs. The trailing profit concept is trying to add the beat feature from breakout strategies and increase probability to stay in trade while uptrend is developing. When price hit the trailing profit activation level, script started to trail the price with middle line if Bollinger bands indicator. Only when candle closes below the middle line script closes the long trade.
Backtest Results
Operating window: Date range of backtests is 2020.10.01 - 2024.07.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -9.78%
Maximum Single Profit: +25.62%
Net Profit: +6778.11 USDT (+67.78%)
Total Trades: 111 (48.65% win rate)
Profit Factor: 2.065
Maximum Accumulated Loss: 853.56 USDT (-6.60%)
Average Profit per Trade: 61.06 USDT (+1.62%)
Average Trade Duration: 76 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Keltner Channels Bands (RMA)Keltner Channel Bands
These normally consist of:
Keltner Channel Upper Band = EMA + Multiplier ∗ ATR
Keltner Channel Lower Band = EMA − Multiplier ∗ ATR
However instead of using ATR we are using RMA
This gives us a much smoother take of the KCB
We are also using 2 sets of bands built on 1 Moving average, this is a common set up for mean reversion strategies.
This can often be paired with RSI for lower timeframe divergences
Divergence
This is using the RSI to calculate when price sets new lows/highs whilst the RSI movement is in the opposite direction.
The way this is calculated is slightly different to traditional divergence scripts. instead of looking for pivot highs/lows in the RSI we are logging the RSI value when price makes it pivot highs/lows.
Gradient Bands
The Gradient Colouring on the bands is measuring how long price has been either side of the MA.
As Keltner bands are commonly used as a mean reversion strategy, I thought it would be useful to see how long price has been trending in a certain direction, the stronger the colours get,
the longer price has been trending that direction which could suggest we are looking for a retrace soon.
Alerts
Alerts included let you choose whether you want to receive an alert for the inside, outside or both band touches.
To set up these alerts, simply toggle them on in the settings, then click on the 3 dots next to the indicators name, from there you click 'Add Alert'.
From there you can customise the alert settings but make sure to leave the 2 top boxes which control the alert conditions. They will be default selected onto your correct settings, the rest you may want to change.
Once you create the alert, it will then trigger as soon as price touches your chosen inside/outside band.
Suggestions
Please feel free to offer any suggestions which you think could improve the script
Disclaimer
The default settings/parameters were shared by Jimtalbott, feel free to play about with the and use this code to make your own strategies.
Roger & Satchell Estimator Historical Volatility Bands [Loxx]Roger & Satchell Estimator Historical Volatility Bands are constructed using:
Average as the middle line.
Upper and lower bands using theRoger & Satchell Estimator Historical Volatility Bands for bands calculation.
What is Roger & Satchell Estimator Historical Volatility?
The Rogers–Satchell estimator does not handle opening jumps; therefore, it underestimates the volatility. It accurately explains the volatility portion that can be attributed entirely to a trend in the price evolution. Rogers and Satchell try to embody the frequency of price observations in the model in order to overcome the drawback. They claim that the corrected estimator outperforms the uncorrected one in a study based on simulated data.
RSEHV = sqrt((Z/n) * sum((log(high/close)*log(high/open)) + (log(low/close)*log(low/open))))
The color of the middle line, unlike the bands colors, has 3 colors. When colors of the bands are the same, then the middle line has the same color, otherwise it's white.
Included
Alerts
Signals
Loxx's Expanded Source Types
Bar coloring
Garman & Klass Estimator Historical Volatility Bands [Loxx]Garman & Klass Estimator Historical Volatility Bands are constructed using:
Average as the middle line.
Upper and lower bands using the Garman & Klass Estimator Historical Volatility (instead of "regular" Historical Volatility ) for bands calculation.
What is Garman & Klaus Historical Volatility?
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security. The Garman and Klass estimator for estimating historical volatility assumes Brownian motion with zero drift and no opening jumps (i.e. the opening = close of the previous period). This estimator is 7.4 times more efficient than the close-to-close estimator. Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate. Garman and Klass also assumed that the process of price change is a process of continuous diffusion (geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements. Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
The Garman & Klass Estimator is as follows:
GKE = sqrt((Z/n)* sum((0.5*(log(high./low)).^2) - (2*log(2) - 1).*(log(close./open)).^2))
The color of the middle line, unlike the bands colors, has 3 colors. When colors of the bands are the same, then the middle line has the same color, otherwise it's white.
Included
Alerts
Signals
Loxx's Expanded Source Types
Bar coloring
Related indicators:
Parkinson's Historical Volatility Bands
Parkinson's Historical Volatility Bands [Loxx]Parkinson's Historical Volatility Bands are constructed using:
Average as the middle line.
Upper and lower bands using the Parkinson's historical volatility (instead of "regular" Historical Volatility) for bands calculation.
What is Parkinson's Historical Volatility?
The Parkinson's number, or High Low Range Volatility developed by the physicist, Michael Parkinson in 1980, aims to estimate the Volatility of returns for a random walk using the High and Low in any particular period. IVolatility.com calculates daily Parkinson values. Prices are observed on a fixed time interval: n = 10, 20, 30, 60, 90, 120, 150, 180 days.
SH is stock's High price in t day.
SL is stock's Low price in t day.
High/Low Return (xt^HL) is calculated as the natural logarithm of the ratio of a stock's High price to stock's Low price.
Return:
And Parkinson's number: 1 / (4 * math.log(2)) * 252 / n * Σ (n, t =1) {math.log(Ht/Lt)^2}
An important use of the Parkinson's number is the assessment of the distribution prices during the day as well as a better understanding of the market dynamics. Comparing the Parkinson's number and periodically sampled volatility helps traders understand the tendency towards mean reversion in the market as well as the distribution of stop-losses.
The color of the middle line, unlike the bands colors, has 3 colors. When colors of the bands are the same, then the middle line has the same color, otherwise it's white.
Included
Alerts
Signals
Loxx's Expanded Source Types
Bar coloring
