Bollinger Bands Entry/Exit ThresholdsBollinger Bands Entry/Exit Thresholds
Author of enhancements: chuckaschultz
Inspired and adapted from the original 'Bollinger Bands Breakout Oscillator' by LuxAlgo
Overview
Pairs nicely with Contrarian 100 MA
The Bollinger Bands Entry/Exit Thresholds is a powerful momentum-based indicator designed to help traders identify potential entry and exit points in trending or breakout markets. By leveraging Bollinger Bands, this indicator quantifies price deviations from the bands to generate bullish and bearish momentum signals, displayed as an oscillator. It includes customizable entry and exit signals based on user-defined thresholds, with visual cues plotted either on the oscillator panel or directly on the price chart.
This indicator is ideal for traders looking to capture breakout opportunities or confirm trend strength, with flexible settings to adapt to various markets and trading styles.
How It Works
The Bollinger Bands Entry/Exit Thresholds calculates two key metrics:
Bullish Momentum (Bull): Measures the extent to which the price exceeds the upper Bollinger Band, expressed as a percentage (0–100).
Bearish Momentum (Bear): Measures the extent to which the price falls below the lower Bollinger Band, also expressed as a percentage (0–100).
The indicator generates:
Long Entry Signals: Triggered when the bearish momentum (bear) crosses below a user-defined Long Threshold (default: 40). This suggests weakening bearish pressure, potentially indicating a reversal or breakout to the upside.
Exit Signals: Triggered when the bullish momentum (bull) crosses below a user-defined Sell Threshold (default: 80), indicating a potential reduction in bullish momentum and a signal to exit long positions.
Signals are visualized as tiny colored dots:
Long Entry: Blue dots, plotted either at the bottom of the oscillator or below the price bar (depending on user settings).
Exit Signal: White dots, plotted either at the top of the oscillator or above the price bar.
Calculation Methodology
Bollinger Bands:
A user-defined Length (default: 14) is used to calculate an Exponential Moving Average (EMA) of the source price (default: close).
Standard deviation is computed over the same length, multiplied by a user-defined Multiplier (default: 1.0).
Upper Band = EMA + (Standard Deviation × Multiplier)
Lower Band = EMA - (Standard Deviation × Multiplier)
Bull and Bear Momentum:
For each bar in the lookback period (length), the indicator calculates:
Bullish Momentum: The sum of positive deviations of the price above the upper band, normalized by the total absolute deviation from the upper band, scaled to a 0–100 range.
Bearish Momentum: The sum of positive deviations of the price below the lower band, normalized by the total absolute deviation from the lower band, scaled to a 0–100 range.
Formula:
bull = (sum of max(price - upper, 0) / sum of abs(price - upper)) * 100
bear = (sum of max(lower - price, 0) / sum of abs(lower - price)) * 100
Signal Generation:
Long Entry: Triggered when bear crosses below the Long Threshold.
Exit: Triggered when bull crosses below the Sell Threshold.
Settings
Length: Lookback period for EMA and standard deviation (default: 14).
Multiplier: Multiplier for standard deviation to adjust Bollinger Band width (default: 1.0).
Source: Input price data (default: close).
Long Threshold: Bearish momentum level below which a long entry signal is generated (default: 40).
Sell Threshold: Bullish momentum level below which an exit signal is generated (default: 80).
Plot Signals on Main Chart: Option to display entry/exit signals on the price chart instead of the oscillator panel (default: false).
Style:
Bullish Color: Color for bullish momentum plot (default: #f23645).
Bearish Color: Color for bearish momentum plot (default: #089981).
Visual Features
Bull and Bear Plots: Displayed as colored lines with gradient fills for visual clarity.
Midline: Horizontal line at 50 for reference.
Threshold Lines: Dashed green line for Long Threshold and dashed red line for Sell Threshold.
Signal Dots:
Long Entry: Tiny blue dots (below price bar or at oscillator bottom).
Exit: Tiny white dots (above price bar or at oscillator top).
How to Use
Add to Chart: Apply the indicator to your TradingView chart.
Adjust Settings: Customize the Length, Multiplier, Long Threshold, and Sell Threshold to suit your trading strategy.
Interpret Signals:
Enter a long position when a blue dot appears, indicating bearish momentum dropping below the Long Threshold.
Exit the long position when a white dot appears, indicating bullish momentum dropping below the Sell Threshold.
Toggle Plot Location: Enable Plot Signals on Main Chart to display signals on the price chart for easier integration with price action analysis.
Combine with Other Tools: Use alongside other indicators (e.g., trendlines, support/resistance) to confirm signals.
Notes
This indicator is inspired by LuxAlgo’s Bollinger Bands Breakout Oscillator but has been enhanced with customizable entry/exit thresholds and signal plotting options.
Best used in conjunction with other technical analysis tools to filter false signals, especially in choppy or range-bound markets.
Adjust the Multiplier to make the Bollinger Bands wider or narrower, affecting the sensitivity of the momentum calculations.
Disclaimer
This indicator is provided for educational and informational purposes only.
חפש סקריפטים עבור "bands"
Kernel Regression Bands SuiteMulti-Kernel Regression Bands
A versatile indicator that applies kernel regression smoothing to price data, then dynamically calculates upper and lower bands using a wide variety of deviation methods. This tool is designed to help traders identify trend direction, volatility, and potential reversal zones with customizable visual styles.
Key Features
Multiple Kernel Types: Choose from 17+ kernel regression styles (Gaussian, Laplace, Epanechnikov, etc.) for smoothing.
Flexible Band Calculation: Select from 12+ deviation types including Standard Deviation, Mean/Median Absolute Deviation, Exponential, True Range, Hull, Parabolic SAR, Quantile, and more.
Adaptive Bands: Bands are calculated around the kernel regression line, with a user-defined multiplier.
Signal Logic: Trend state is determined by crossovers/crossunders of price and bands, coloring the regression line and band fills accordingly.
Custom Color Modes: Six unique color palettes for visual clarity and personal preference.
Highly Customizable Inputs: Adjust kernel type, lookback, deviation method, band source, and more.
How to Use
Trend Identification: The regression line changes color based on the detected trend (up/down)
Volatility Zones: Bands expand/contract with volatility, helping spot breakouts or mean-reversion opportunities.
Visual Styling: Use color modes to match your chart theme or highlight specific market states.
Credits:
Kernel regression logic adapted from:
ChartPrime | Multi-Kernel-Regression-ChartPrime (Link in the script)
Disclaimer
This script is for educational and informational purposes only. Not financial advice. Use at your own risk.
VWAP Bands with ML [CryptoSea]VWAP Machine Learning Bands is an advanced indicator designed to enhance trading analysis by integrating VWAP with a machine learning-inspired adaptive smoothing approach. This tool helps traders identify trend-based support and resistance zones, predict potential price movements, and generate dynamic trade signals.
Key Features
Adaptive ML VWAP Calculation: Uses a dynamically adjusted SMA-based VWAP model with volatility sensitivity for improved trend analysis.
Forecasting Mechanism: The 'Forecast' parameter shifts the ML output forward, providing predictive insights into potential price movements.
Volatility-Based Band Adjustments: The 'Sigma' parameter fine-tunes the impact of volatility on ML smoothing, adapting to market conditions.
Multi-Tier Standard Deviation Bands: Includes two levels of bands to define potential breakout or mean-reversion zones.
Dynamic Trend-Based Colouring: The VWAP and ML lines change colour based on their relative positions, visually indicating bullish and bearish conditions.
Custom Signal Detection Modes: Allows traders to choose between signals from Band 1, Band 2, or both, for more tailored trade setups.
In the image below, you can see an example of the bands on higher timeframe showing good mean reversion signal opportunities, these tend to work better in ranging markets rather than strong trending ones.
How It Works
VWAP & ML Integration: The script computes VWAP and applies a machine learning-inspired adjustment using SMA smoothing and volatility-based adaptation.
Forecasting Impact: The 'Forecast' setting shifts the ML output forward in time, allowing for anticipatory trend analysis.
Volatility Scaling (Sigma): Adjusts the ML smoothing sensitivity based on market volatility, providing more responsive or stable trend lines.
Trend Confirmation via Colouring: The VWAP line dynamically switches colour depending on whether it is above or below the ML output.
Multi-Level Band Analysis: Two standard deviation-based bands provide a framework for identifying breakouts, trend reversals, or continuation patterns.
In the example below, we can see some of the most reliable signals where we have mean reversion signals from the band whilst the price is also pulling back into the VWAP, these signals have the additional confluence which can give you a higher probabilty move.
Alerts
Bullish Signal Band 1: Alerts when the price crosses above the lower ML Band 1.
Bearish Signal Band 1: Alerts when the price crosses below the upper ML Band 1.
Bullish Signal Band 2: Alerts when the price crosses above the lower ML Band 2.
Bearish Signal Band 2: Alerts when the price crosses below the upper ML Band 2.
Filtered Bullish Signal: Alerts when a bullish signal is triggered based on the selected signal detection mode.
Filtered Bearish Signal: Alerts when a bearish signal is triggered based on the selected signal detection mode.
Application
Trend & Momentum Analysis: Helps traders identify key market trends and potential momentum shifts.
Dynamic Support & Resistance: Standard deviation bands serve as adaptive price zones for potential breakouts or reversals.
Enhanced Trade Signal Confirmation: The integration of ML smoothing with VWAP provides clearer entry and exit signals.
Customizable Risk Management: Allows users to adjust parameters for fine-tuned signal detection, aligning with their trading strategy.
The VWAP Machine Learning Bands indicator offers traders an innovative tool to improve market entries, recognize potential reversals, and enhance trend analysis with intelligent data-driven signals.
Support BandsSupport Bands – Discount Zones for Bitcoin
⚡Overview:
-The Support Bands indicator identifies one of the most tested and respected support zones for Bitcoin using moving averages from higher timeframes.
-These zones are visualized through colored bands (blue, white, and violet), simplifying the decision making process especially for less experienced traders who seek high-probability areas to accumulate Bitcoin during retracements.
-Band levels are based on manual backtesting and real-world price behavior throughout Bitcoin’s history.
-Each zone reflects a different degree of support strength, from temporary pullback zones to historical bottoms.
⚡️ Key Characteristics:
-Highlights discount zones where Bitcoin has historically shown strong reactions.
-Uses 3 different levels of supports based on EMA/SMA combinations.
-Offers a clean, non-intrusive overlay that reduces chart clutter.
⚡ How to Use:
-Open your chart on the 1W timeframe and select the BTC Bitstamp or BLX symbol, as they provide the most complete historical data, ensuring optimal performance of the indicator.
-Use the bands as reference zones for support and potential pullbacks.
- Level 3 (violet band) historically marks the bottom of Bitcoin bear markets and is ideal for long-term entries during deep corrections.
- Level 2 (white band) often signals macro reaccumulation zones but usually requires 1–3 months of consolidation before a breakout. If the price closes below and then retests this level as resistance for 1–2 weekly candles, it often marks the start of a macro downtrend.
-Level 1 (blue band) acts as short-term support during strong bullish moves, typically after a successful rebound from Level 2.
⚡ What Makes It Unique:
- This script merges moving averages per level into three simplified bands for clearer analysis.
-Reduces chart noise by avoiding multiple overlapping lines, helping you make faster and cleaner decisions.
- Built from manual market study based on recurring Bitcoin behavior, not just random code.
-Historically backtested:
-Level 3 (violet band) until today has always marked the bitcoin bearmarket bottom.
- Level 2 (white band) is the strongest support during bull markets; losing it often signals a macro trend reversal.
- Level 1 is frequently retested during impulsive rallies and can act as short-term support or resistance.
⚡ Disclaimer:
-This script is a visual tool to assist with market analysis.
-It does not generate buy or sell signals, nor does it predict future movements.
-Historical performance is not indicative of future results.
-Always use independent judgment and proper risk management.
⚡ Why Use Support Bands:
-Ideal for traders who want clarity without dozens of lines on their charts.
- Helps identify logical zones for entry or reaccumulation.
- Based on actual market behavior rather than hypothetical setups.
-If the blue band (Level 1) doesn't hold as support, the price often moves to the white band (Level 2), and if that fails too, the violet band (Level 3) is typically the last strong support. By dividing your capital into three planned entries, one at each level,you can manage risk more effectively compared to entering blindly without this structure.
Robust Bollinger Bands with Trend StrengthThe "Robust Bollinger Bands with Trend Strength" indicator is a technical analysis tool designed assess price volatility, identify potential trading opportunities, and gauge trend strength. It combines several robust statistical methods and percentile-based calculations to provide valuable information about price movements with Improved Resilience to Noise while mitigating the impact of outliers and non-normality in price data.
Here's a breakdown of how this indicator works and the information it provides:
Bollinger Bands Calculation: Similar to traditional Bollinger Bands, this indicator calculates the upper and lower bands that envelop the median (centerline) of the price data. These bands represent the potential upper and lower boundaries of price movements.
Robust Statistics: Instead of using standard deviation, this indicator employs robust statistical measures to calculate the bands (spread). Specifically, it uses the Interquartile Range (IQR), which is the range between the 25th percentile (low price) and the 75th percentile (high price). Robust statistics are less affected by extreme values (outliers) and data distributions that may not be perfectly normal. This makes the bands more resistant to unusual price spikes.
Median as Centerline: The indicator utilizes the median of the chosen price source (either HLC3 or VWMA) as the central reference point for the bands. The median is less affected by outliers than the mean (average), making it a robust choice. This can help identify the center of price action, which is useful for understanding whether prices are trending or ranging.
Trend Strength Assessment: The indicator goes beyond the standard Bollinger Bands by incorporating a measure of trend strength. It uses a robust rank-based correlation coefficient to assess the relationship between the price source and the bar index (time). This correlation coefficient, calculated over a specified length, helps determine whether a trend is strong, positive (uptrend), negative (down trend), or non-existent and weak. When the rank-based correlation coefficient shifts it indicates exhaustion of a prevailing trend. Trend Strength" indicator is designed to provide statistically valid information about trend strength while minimizing the impact of outliers and data distribution characteristics. The parameter choices, including a length of 14 and a correlation threshold of +/-0.7, considered to offer meaningful insights into market conditions and statistical validity (p-value ,0.05 statistically significant). The use of rank-based correlation is a robust alternative to traditional Pearson correlation, especially in the context of financial markets.
Trend Fill: Based on the robust rank-based correlation coefficient, the indicator fills the area between the upper and lower Bollinger Bands with different colors to visually represent the trend strength. For example, it may use green for an uptrend, red for a down trend, and a neutral color for a weak or ranging market. This visual representation can help traders quickly identify potential trend opportunities. In addition the middle line also informs about the overall trend direction of the median.
Volatility-Based Mean Reversion BandsThe Volatility-Based Mean Reversion Bands indicator is a powerful tool designed to identify potential mean reversion trading opportunities based on market volatility. The indicator consists of three lines: the mean line, upper band, and lower band. These bands dynamically adjust based on the average true range (ATR) and act as reference levels for identifying overbought and oversold conditions.
The calculation of the indicator involves several steps. The average true range (ATR) is calculated using a specified lookback period. The ATR measures the market's volatility by considering the range between high and low prices over a given period. The mean line is calculated as a simple moving average (SMA) of the closing prices over the same lookback period. The upper band is derived by adding the product of the ATR and a multiplier to the mean line, while the lower band is derived by subtracting the product of the ATR and the same multiplier from the mean line.
Interpreting the indicator is relatively straightforward. When the price approaches or exceeds the upper band, it suggests that the market is overbought and may be due for a potential reversal to the downside. On the other hand, when the price approaches or falls below the lower band, it indicates that the market is oversold and may be poised for a potential reversal to the upside. Traders can look for opportunities to enter short positions near the upper band and long positions near the lower band, anticipating the price to revert back towards the mean line.
The bar color and background color play a crucial role in visualizing the indicator's signals and market conditions. Lime-colored bars are used when the price is above the upper band, indicating a potential bearish mean reversion signal. Conversely, fuchsia-colored bars are employed when the price is below the lower band, suggesting a potential bullish mean reversion signal. This color scheme helps traders quickly identify the prevailing market condition and potential reversal zones. The background color complements the bar color by providing further context. Lime-colored background indicates a potential bearish condition, while fuchsia-colored background suggests a potential bullish condition. The transparency level of the background color is set to 80% to avoid obscuring the price chart while still providing a visual reference.
To provide additional confirmation for mean reversion setups, the indicator incorporates the option to use the Relative Strength Index (RSI) as a confluence factor. The RSI is a popular momentum oscillator that measures the speed and change of price movements. When enabled, the indicator checks if the RSI is in overbought territory (above 70) or oversold territory (below 30), providing additional confirmation for potential mean reversion setups.
In addition to visual signals, the indicator includes entry arrows above or below the bars to highlight the occurrence of short or long entries. When the price is above the upper band and the confluence condition is met, a fuchsia-colored triangle-up arrow is displayed above the bar, indicating a potential short entry signal. Similarly, when the price is below the lower band and the confluence condition is met, a lime-colored triangle-down arrow is displayed below the bar, indicating a potential long entry signal.
Traders can customize the indicator's parameters according to their trading preferences. The "Lookback Period" determines the number of periods used in calculating the mean line and the average true range (ATR). Adjusting this parameter can affect the sensitivity and responsiveness of the indicator. Smaller values make the indicator more reactive to short-term price movements, while larger values smooth out the indicator and make it less responsive to short-term fluctuations. The "Multiplier" parameter determines the distance between the mean line and the upper/lower bands. Increasing the multiplier widens the bands, indicating a broader range for potential mean reversion opportunities, while decreasing the multiplier narrows the bands, indicating a tighter range for potential mean reversion opportunities.
It's important to note that the Volatility-Based Mean Reversion Bands indicator is not a standalone trading strategy but rather a tool to assist traders in identifying potential mean reversion setups. Traders should consider using additional analysis techniques and risk management strategies to make informed trading decisions. Additionally, the indicator's performance may vary across different market conditions and instruments, so it's advisable to conduct thorough testing and analysis before integrating it into a trading strategy.
+ Magic Carpet BandsFun name for an indicator, eh? Well, it is true, I think; they look like magic carpets. They're actually pretty simple actually. They're Keltner Channels smoothed with a moving average. If you go down to the lookback period for the bands and set it to 1, you'll recognize them immediately.
Digging a bit deeper you see there are four magic carpets on the chart. The inner ones are set to a multiplier of 2, and the outer to a multiplier of 4. Each "carpet" is composed of two smoothed upper or lower Keltner Channels bounds, both with an optional offset, one of which is set to 13, and the other to 0 by default; and an optional color fill between these. There is also a color fill between the outer and inner carpets which gives them an interesting 3-dimensional aspect at times. They can look a bit like tunnels by default.
My thinking around the idea of using an offset with the bands is that if we assume these things to provide a dynamic support and resistance, and previous support and resistance maintains status as support and resistance until proven otherwise, then by putting an offset to past data we are creating a more obvious visual indication of that support or resistance in the present. The default offset is set to 13 bars back, so if price found resistance at some point around 13 bars ago, and price is currently revisiting it we assume it is still resistance, and that offset band is there to give us a strong visual aid. Obviously it's not foolproof, but nothing is.
Beyond that most interesting part of the indicator you have a nice selection of moving averages which the bands are calculated off of. By default it's set to my UMA. The bands themselves also have a selection of moving averages for how the keltner channels are smoothed. And a note: because the UMA and RDMA are averages of different length MAs, they can not be adjusted other than via the multiplier that sets the distance from the moving average.
The indicator is multi-timeframe, and the moving average can be colored based on a higher timeframe as well.
I popped in the divergence indicator here too. You can choose from RSI and OBV, and the divergences will be plotted on the chart. Working on finding a way to be able to have the bands/MA set to a higher timeframe while plotting the divergences on the chart timeframe, but don't have an answer to that yet.
Alerts for moving average crosses, band touches, and divergences.
I like this one a lot. Enjoy!
Pictures below.
s3.tradingview.com
One interesting thing about this indicator is that band twists often occur at areas of support or resistance. Simply drawing horizontal lines from previous twisted points can provide places from which you may look for strength or weakness to enter into a trade, or which you might use as targets for taking profits. The vertical lines are just showing the point on the chart when the cross occurred.
s3.tradingview.com
Above is a Jurik MA with a bunch of adjustments made to the bands, and the moving average itself. Everything is super adjustable, so you can play around and have fun with them quite a bit.
s3.tradingview.com
Just a different MA and bands.
s3.tradingview.com
PER Bands (Auto EPS)PER Bands Indicator - Technical Specification
Function
This PineScript v6 overlay indicator displays horizontal price bands based on Price-to-Earnings Ratio multiples. The indicator calculates price levels by multiplying earnings per share values by user-defined PER multiples, then plots these levels as horizontal lines on the chart.
Data Sources
The script attempts to automatically retrieve earnings per share data using TradingView's `request.financial()` function. The system first queries trailing twelve months EPS data, then annual EPS data if TTM is unavailable. When automatic retrieval fails or returns zero values, the indicator uses manually entered EPS values as a fallback.
Configuration Options
Users can configure five separate PER multiples (default values: 10x, 15x, 20x, 25x, 30x). Each band supports individual color customization and adjustable line width settings from 1 to 5 pixels. The indicator includes toggles for band visibility and optional fill areas between adjacent bands with 95% transparency.
Visual Components
The indicator plots five horizontal lines representing different PER valuation levels. Optional fill areas create colored zones between consecutive bands. A data table in the top-right corner displays current EPS source, EPS value, current PER ratio, and calculated price levels for each configured multiple.
Calculation Method
The indicator performs the following calculations:
- Band Price = Current EPS × PER Multiple
- Current PER = Current Price ÷ Current EPS
These calculations update on each bar close using the most recent available EPS data.
Alert System
The script includes alert conditions for price crossovers above the lowest PER band and crossunders below the highest PER band. Additional alert conditions can be configured for any band level through the alert creation interface.
Debug Features
Debug mode displays character markers on the chart indicating when TTM or annual EPS data is available. This feature helps users verify which data source the indicator is using for calculations.
Data Requirements
The indicator requires positive, non-zero EPS values to function correctly. Stocks with negative earnings or zero EPS will display "N/A" for current PER calculations, though bands will still plot using the manual EPS input value.
Exchange Compatibility
Automatic EPS data availability varies by exchange. United States equity markets typically provide comprehensive fundamental data coverage. International markets may have limited automatic data availability, requiring manual EPS input for accurate calculations.
Technical Limitations
The indicator cannot fetch real-time EPS updates and relies on TradingView's fundamental data refresh schedule. Historical EPS changes are not reflected in past band positions, as the indicator uses current EPS values for all historical calculations.
Display Settings
The information table shows EPS source type (TTM Auto, Annual Auto, Manual, or Manual Fallback), allowing users to verify data accuracy. The table refreshes only on the last bar to optimize performance and reduce computational overhead.
Code Structure
Built using PineScript v6 syntax with proper scope management for plot and fill functions. The script uses global scope for all plot declarations and conditional logic within plot parameters to handle visibility settings.
Version Requirements
This indicator requires TradingView Pine Script version 6 or later due to the use of `request.financial()` functions and updated syntax requirements for plot titles and fill operations.
[astropark] Nova BandsDear followers,
today a new analysis and scalping tool for day trading on low timeframes (5-15 minutes) or to plan swing trades on hourly timeframes. It can be used also on high timeframes just for analysis current market trend.
The indicator plots a series of levels which create a nice bands flow.
The slope of levels make you easily understand when price is in consolidation, in uptrend or in downtrend.
The golden rule is always the same: buy low and sell high .
This indicator plots:
3 "price is low here" levels (from dark green to light green)
3 "price is average here" levels
3 "price is high here" levels (from purple to orange)
When bands are flat, price is in consolidation and this is best condition to trade with nova bands.
When price reaches higher bands, you will open a short position with targets below levels, fully closing your position when price hits the average level (black).
Here an example on Bitcoin on 15m using 1h resolution:
The same applies when price reaches lower bands, you will open a long position with targets above levels, fully closing your position when price hits the average level (black).
When bands get nearer and nearer is called "Bands Squeeze": price is next to a main breakout move, volatility is coming!
Here an example of SPX500: after long consolidation and bands getting nearer and neared, we had the breakout, downwards in this case.
In this screenshot you can see what signals algorithm provided:
Our suggestion is to play safe these kind of scenarios, no reason to FOMO buy/sell. Just wait for price consolidation / getting back inside the bands.
For example you would have skip first three buy signals, while you would have longed the last two as price came back inside bands after the big volatility which made price went below bands.
Another example is TSLA stock on 15m with 1h resolution:
Price touched the first bullish level and made a big move upwards, breaking bands with a +90% move.
In this case, you would have skipper first 2 sell signals, while you would have accepted next two with stoploss above recent high.
Acceptable also the other two sell signals, which you may have closed when price retraced to lower levels:
You can of course run trends like this buying on price hitting bullish/lower levels after a long consolidation and sell on price hitting middle and higher levels:
A trader who wants to be a winner must understand that money and risk management are very important, so manage your position size and always have a stop loss in your trades.
Here some examples how the indicator works on different markets:
EURUSD 15m with standard settings and 1h resolution
GOLD (XAUUSD) 15m with standard settings and 1h resolution
Facebook (FB) 15m with standard settings and 1h resolution
This is a premium indicator , so send me a private message in order to get access to this script.
VWAP Implied Volatility BandsThis script takes the built in VWAP function and creates bands using various Volatility Indexes from the CBOE. The script plots the bands at desired multiples, as well as the closing value of the prior day's first set of bands. Users can choose from the following:
VIX(ES), VXN(NQ), RVX(RTY), OVX(CL), GVX(GC), SIV(ZS), CIV(ZC), TYVIX(ZN), EUVIX(EURUSD), BPVIX(GBPUSD)
Upon selecting the desired volatility index, users must change the multiplier to fit the underlying product since the indexes are all calculated differently.
The goal with this script was to use market generated information (IV) to highlight potential trade locations.
Volatility BandsWe used Marc Chaikin’s Chaikin Volatility as somewhat of a baseline for this indicator and then built on it. Like Chaikin Volatility, our indicator draws primarily upon high-low spreads to quantify a security’s volatility. It also has similarities to Keltner Channels as it uses ATR rather than standard deviations in its calculation of the different bands.
Inputs:
int ‘len0’, lookback window for fast EMA of high-low ranges.
int ‘len1’, lookback window for slow EMA of high-low ranges.
int ‘len2’, lookback window for slow EMA of closing prices.
float ‘m0’, ATR multiplier for first upper and lower volatility bands.
float ‘m1’, ATR multiplier for second upper and lower volatility bands.
float ‘m2’, ATR multiplier for third upper and lower volatility bands.
int ‘lenATR’, window length for ATR calculation.
Output: 3 Upper and Lower Volatility Bands (6 total).
1. Compute High Low Spread for current period.
hlr = (high – low)
2. Calculate Exponential Moving Average of HLR at length len0
fastEMA = ema(hlr, len0)
3. Calculate Exponential Moving average of HLR at length len1 (where len1 > len0)
slowEMA = ema(hlr, len1)
4. Get EMA of closing prices at length len2(where len2 > len1 and len1 > len0)
priceEMA = ema(close, len2)
5. Use adjusted Chaikin Volatility Formula to quantify volatility
v = (fastEMA – slowEMA) / slowEMA
6. Calculate three upper and three lower volatility bands (6 total):
ex:
upper0 = priceEMA + ((1 – cv) * (atrMult0 * atr(lenATR)))
lower0 = priceEMA – ((1 – cv) * (atrMult0 * atr(lenATR)))
One possible way to use this indicator is to enter a long position when the security’s price falls below the lowest volatility band and then exit when it crosses above the third upper band. This seems to get the best results for quick, high frequency trading. Another approach is to enter a position when the bands begin to break out from a compact state and the width between them increases.
Still tweaking the idea, so any feedback would be appreciated.
Dynamic Laguerre Filter Bands | OttoThis indicator combines trend-following and volatility analysis by enhancing the traditional Laguerre filter with a dynamic, volatility-adjusted band system. Instead of using fixed thresholds, the bands adapt in real-time to changing market conditions by applying smoothed standard deviation calculations. This design keeps the indicator responsive to significant price movements while effectively filtering out short-term market noise, resulting in more accurate trend identification and breakout signals.
Core Concept
The indicator is built around the following key components:
Laguerre Filter:
The Laguerre filter is designed to smooth out price data by reducing market noise while still being quick enough to detect real changes in price direction. Its goal is to create a clear, smooth trend line that helps traders/investors focus on the overall market trend without getting distracted by small, random price swings.
It uses a parameter called gamma to control how it balances smoothness and responsiveness:
A lower gamma gives more weight to recent price data, making the filter react faster to new price changes. This means the trend line is more sensitive but may also be less smooth and more prone to small fluctuations.
A higher gamma gives more weight to past price data, making the filter smoother and less sensitive to quick changes. This helps reduce noise and produces a steadier trend line, but it also introduces more lag, meaning the filter reacts slower to new price moves.
By adjusting gamma, the Laguerre filter lets you choose the balance between following price changes quickly and having a stable, noise-free trend signal.
Standard Deviation:
shows how much price varies from the mean. In this indicator, it’s used to measure market volatility.
Volatility Bands: The upper and lower bands are based on an EMA-smoothed standard deviation of price. The EMA reduces sudden jumps in volatility, creating smoother and more stable bands that still respond to changing market conditions. These bands are plotted around the Laguerre filter line, expanding and contracting in a controlled way to stay aligned with real market movement while avoiding short-term noise.
Signal Logic:
A long signal is triggered when the close price crosses above the upper band.
A short signal occurs when the close price falls below the lower band.
⚙️ Inputs
Source: Price source used in calculations
Gamma: Adjusts how much the Laguerre filter responds to price changes. Lower gamma values make the filter react more to recent prices, while higher values give more influence to older data, making the line smoother but slower to respond.
Volatility Length: Period used to calculate standard deviation
Volatility Smoothing Length: EMA smoothing length for standard deviation
Multiplier: Scales the width of the bands based on volatility
📈 Visual Output
Laguerre Filter Line: Plots the laguerre filter line, colored dynamically based on signal direction (green for bullish, purple for bearish)
Upper & Lower Bands: Volatility-based bands that adjust with market conditions. (green for bullish, purple for bearish)
Glow Effect: Optional glow layer to enhance visibility of the laguerre filter trend line (green for bullish, purple for bearish)
Bar Coloring: Candlesticks and bar colors reflect the active signal state for fast visual interpretation (green for bullish, purple for bearish)
How to Use
Apply the indicator to your chart and monitor for signal events:
Long Signal: When price closes above the upper band
Short Signal: When price closes below the lower band
🔔 Alerts
This indicator supports optional alert conditions you can enable for:
Long Signal: Close price crossing above the upper band
Short Signal: Close price crossing below the lower band
⚠️ Disclaimer:
This indicator is intended for educational and informational purposes only. Trading/investing involves risk, and past performance does not guarantee future results. Always test and evaluate indicators/strategies before applying them in live markets. Use at your own risk.
Volatility Profit (VPI) & Bollinger Bands (BB) [checkm8]Hello and welcome to my 2-in-1 indicator of Volatility Profit Indicator and Bollinger Bands.
Volatility Profit Indicator is a script inspired by Jim Berg, from a 2005 article titled "The Truth About Volatility". This is a set of bands, where the upper band is based on a moving average of highs over a given period, added to the average true range of the period. The lower band is based on a moving average of lows over the same given period, from which the average true range is subtracted. The formula is shown below:
VPI High Band = MA(HI, type, x) + y * ATR(z)
VPI Low Band = MA(LO, type, x) - y * ATR(z)
where... type = MA Type (default to Exponential) x = MA Period (default to 13) y = True Range Multiplier (default to 2) z = True Range Period (default to 20)
Bollinger Bands should be familiar by now, but they are calculated based on a moving average of a source ( / 3), added to a particular standard deviation of the source.
This indicator:
- Allows you to choose whether you want to plot the Volatility Profit Indicator or Bollinger Bands. By default, each will show three bands.
- Has pre-made color schemes to choose from to simplify your life.
- Has smoothing for the Volatility Profit Indicator
- Allows you to choose the source for Bollinger Bands
- Allows you to select what multiplier of the average true range the Volatility Profit Indicator plots, as well as what standard deviations the Bollinger Bands show.
If you have any additional questions, concerns, or suggestions - feel free to reach out.
All the best & happy trading.
INAZUMA Bollinger BandsThis is an indicator based on the widely used Bollinger Bands, enhanced with a unique feature that visually emphasizes the "strength of the breakout" when the price penetrates the bands.
Main Features and Characteristics
1. Standard Bollinger Bands Display
Center Line (Basis): Simple Moving Average (\text{SMA(20)}).
1 sigma Lines: Light green (+) and red (-) lines for reference.
2 sigma Lines (Upper/Lower Band): The main dark green (+) and red (-) bands.
2. Emphasized Breakout Zones: "INAZUMA / Flare" and "MAGMA"
The key feature is the activation of colored, expanding areas when the candlestick's High or Low breaks significantly outside the \pm 2\sigma bands.
Upper Side (Green Base / Flare):
When the High exceeds the +2\sigma line, a green gradient area expands upwards.
Indication: This visually suggests strong buying pressure or overbought conditions. The color deepens as the price moves further away, indicating higher momentum.
Lower Side (Red Base / Magma):
When the Low falls below the -2 sigma line, a red gradient area expands downwards.
Indication: This visually suggests strong selling pressure or oversold conditions. The color deepens as the price moves further away, indicating higher momentum.
Key Insight: This visual aid helps traders quickly assess the momentum and market excitement when the price moves outside the standard Bollinger Bands range. Use it as a reference for judging trend strength and potential entry/exit points.
Customizable Settings
You can adjust the following parameters in the indicator settings:
Length: The period used for calculating the Moving Average and Standard Deviation. (Default: 20)
StdDev (Standard Deviation): The multiplier for the band width (e.g., 2.0 for -2 sigma). (Default: 2.0)
Source: The price data used for calculation (Default: close).
Pi Cycle BTC Top + Pre-Alert BandsPi Cycle BTC Top + Pre-Alert Bands is an advanced implementation of the classic Pi Cycle Top model, designed for Bitcoin cycle analysis on higher timeframes (especially 1D BTCUSD/BTCUSD·INDEX).
The original Pi Cycle Top uses two moving averages:
• 111-day SMA (short MA)
• 350-day SMA ×2 (long MA)
A Pi Top is signaled when the 111 SMA crosses above the 350×2 SMA. Historically, this has occurred near major BTC cycle highs.
This script extends that idea with a 3-step early-warning sequence:
• Pi Green – early compression: short/long MA ratio crosses upward into the green band (convergence from below is required).
• Pi Yellow – mid-cycle warning: only fires if a valid Green has already occurred in the same cycle.
• Pi Cycle Top – final top: the classic Pi Cycle cross, limited to one top signal per cycle. After a top, no new Yellow or Top signals can appear until a new Green event starts the next cycle.
Background shading shows the active phase (Green / Yellow / late-cycle zone), so you can see at a glance where BTC is within its Pi-based macro structure.
All logic is non-repainting: request.security() uses lookahead_off and no future data is accessed.
Typical use
This indicator is intended as a macro-cycle timing and risk-awareness tool, not a stand-alone entry system. Many traders use it to:
• Watch for Pi Green as the start of a potential late-cycle advance.
• Treat Pi Yellow as a rising-risk environment and tighten risk management.
• Use the Pi Cycle Top as a historical high-risk zone where large profit-taking or hedging may be considered.
Always combine this with your own analysis (trend, volume, on-chain, macro) before making decisions.
How to set alerts
Add the indicator to your chart (1D BTCUSD or BTCUSD·INDEX recommended).
Click Alerts → Condition → Pi Cycle BTC Top + Pre-Alert Bands.
Choose one of:
• Pi Cycle – Green Pre-Alert (early convergence)
• Pi Cycle – Yellow Pre-Alert (after Green only)
• Pi Cycle – TOP (Single per Cycle, after Green)
Use “Once per bar close” for higher-timeframe reliability.
Disclaimer
This tool is for educational and analytical purposes only. The Pi Cycle concept is based on historical behavior and does not guarantee future results. This is not financial advice; always do your own research and manage risk appropriately.
Indicators: Hurst Bands and Hurst OscillatorThese 2 indicators are derivative work from Jim Hurst's book - "The Magic of Stock Transaction Timing".
The bands are % bands around a median that gets calculated according to Hurst's formula. The outer bands (called ExtremeBands) signify extreme overbought/oversold conditions. Inner bands signify potential pullback points. As you can see, they also act as dynamic S/R levels.
The oscillator bands match the bands overlaid on price, so you will get an excellent indication of where the price is gonna do by using the oscillator along with the bands. Note that Hurst Oscillator can be used separately too, there is no technical dependency on Hurst Bands.
More info on Hurst Method:
www.readtheticker.com
Fibonacci BandsFibonacci Bands are derived from Fibonacci ratios expansion from a fixed moving average.
These bands help traders find key areas of support and resistance . "Fibonacci bands" are
computed by adding a Fibonacci ratio distance (Up and Down) from a "key moving" average
(21, 34, 89 periods). An 8 period average of "True range" is computed. The multiples of
Fibonacci ratios of this range are added to the fixed moving average to compute Fibonacci
Bands
One of the best ways to find trend reversals is to watch the price action near the extreme bands
(both lower and higher). Markets tend to reverse when prices trade outside of the band for a
few bars and again trade inside the bands. After reversals, markets also tend to trade from one
extreme band to the other end (opposite) of the extreme bands.
Volume (Incremental) Weighted VOLATILITY BANDSDISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The following indicator was made for NON LUCRATIVE ACTIVITIES and must remain as is following TradingView's regulations. Use of indicator and their code are published by Invitation Only for work and knowledge sharing. All access granted over it, their use, copy or re-use should mention authorship(s) and origin(s).
WARNING NOTICE!
THE INCLUDED FUNCTION MUST BE CONSIDERED AS TESTING. The models included in the indicator have been taken from openly sources on the web, problems could occur at diverse data sceneries.
WHAT'S THIS...?
Work derived by previous own research for study:
The given indicator is another VWAP analysis tool that contains openly procedures for rolling out time sessions as in other TradingView scripts .
Some novelties are introduced in this version:
INCREMENTAL WEIGHTED STANDARD DEVIATION BANDS: The calculation on this script are strictly based in regard of University of Cambridge Computing Service, February 2009 paper by Tony Finch publicly found at people.ds.cam.ac.uk .
From the Abstract, he explain how to derive formulae for numerically stable calculation of the mean and standard deviation, which are also suitable for incremental on-line calculation. Then he generalize these formulae to weighted means and standard deviations. He unpick the difficulties that arise when generalizing further to normalized weights. Finally he shown that the exponentially weighted moving average is a special case of the incremental normalized weighted mean formula, and derive a formula for the exponentially weighted moving standard deviation.
VOLUME WEIGHTED VOLATILITY ADAPTIVE MOVING AVERAGE & BANDS: Taking the INCREMENTAL WEIGHTED STANDARD DEVIATION already described and taking a specified anchor or Rolling procedure for a VWAP, I derive the variance against the price to use it as VOLATILITY PROXY for a normalization lambda to plot a First Order Impulse Response Filter or Adaptive Average . This idea have it's roots derived from Chaiyuth Padungsaksawasdi & Robert T. Daigler paper entitled "Volume weighted volatility: empirical evidence for a new realised volatility measure".
NOTES:
This version DO NOT INCLUDE ALERTS.
This version DO NOT INCLUDE STRATEGY: Feedback are welcome.
DERIVED WORK:
Incremental calculation of weighted mean and variance by Tony Finch (fanf2@cam.ac.uk) (dot@dotat.at), 2009.
Volume weighted volatility: empirical evidence for a new realised volatility measure by Chaiyuth Padungsaksawasdi & Robert T. Daigler, 2018.
Multi-Timeframe VWAP by TradingView user @mortdiggidi
CHEERS!
@XeL_Arjona 2019.
Acceleration BandsAcceleration Bands
Description:
Acceleration Bands serve as a trading envelope that factor in an assets typical volatility over standard settings of 20 or 80 bars. They can be used across any time period, though traders prefer to use them most across weekly and monthly timeframes as breakout indicators outside these bands.
Using the shorter time frames can define likely support and resistance levels at the lower and upper Acceleration Bands.
Entry is usually made at the breakout point. Once the price closes back within the Acceleration Bands, this is taken as a signal that the acceleration period is over and it’s best to close out the trade.
Fibonacci Volatility BandsFibonacci Volatility Bands are just an alternative that allows for more margin than regular Bollinger Bands. They are created based on an average of moving averages that use the Fibonacci sequence as lookback periods.
The use of the Fibonacci Volatility Bands is exactly the same as the Bollinger Bands.
[JR] Multi Bollinger Heat BandsBollinger Bands, with incremented additional outer bands.
Set as you would normally, but with the addition of an incremental value for the added outer bands.
Defaults with Length 20, base multiplier of 2.0, and an Increment value of 0.5 for additional outer bands at 2.5 and 3.0. Adjust values to suite your needs.
All lines and zones have colour and formatting options available - because why not eh?
Matrix bands by JaeheeMatrix Bands — multi-sigma EMA bands for price dispersion context (no signals)
📌 What it is
Matrix Bands draws an EMA-based central line with multiple standard-deviation envelopes at ±1σ, ±1.618σ, ±2σ, ±2.618σ, ±3σ.
Thin core lines show the precise band levels, while subtle outer “glow” lines improve readability without obscuring candles.
📌 How it works (concept)
Basis: EMA of the selected source (default: close)
Dispersion: Rolling sample standard deviation over the same length
Bands: Basis ± k·σ for k ∈ {1, 1.618, 2, 2.618, 3}
This is not a strategy and does not generate trade signals.
It provides price dispersion context only.
📌 Why these levels together (justification of the combination)
Using multiple σ layers reveals graduated risk zones in one view:
±1σ: routine fluctuation
±1.618σ & ±2σ: extended but still common excursions
±2.618σ & ±3σ: statistically rare extremes, where mean-reversion risk or trend acceleration risk increases
Combining these specific multipliers allows traders to judge positioning vs. volatility instantly, without switching between separate indicators or re-configuring a single band.
📌 How it differs from classic Bollinger Bands
Unlike classic Bollinger Bands, which typically use an SMA basis and only ±2σ envelopes,
Matrix Bands uses an EMA basis for faster trend responsiveness and plots five sigma levels (±1, ±1.618, ±2, ±2.618, ±3).
This design allows traders to visualize market dispersion across multiple statistical thresholds simultaneously, making it more versatile for both trend-following and mean-reversion contexts.
📌 How to read it (context, not signals)
Mean-reversion context: Moves beyond ±2σ may indicate stretched conditions; wait for your own confirmation signals before acting
Trend context: In strong trends, price can “ride” the outer bands; sustained closes near +2σ~+3σ (uptrend) or −2σ~−3σ (downtrend) suggest persistent momentum
Regime observation: Band width expands in high volatility and contracts in quiet regimes; adjust stops and sizing accordingly
📌 Inputs
BB Length: lookback period for EMA and σ (default: 20)
Source: price source for calculations
📌 Design notes
Thin inner lines = exact levels
Soft outer lines = readability “glow” only; no effect on calculations
Overlay display keeps the chart uncluttered
📌 Limitations & good practice
No entry/exit logic; use with your own strategy rules
Volatility interpretation varies by timeframe
Past patterns do not guarantee future outcomes; risk management is essential
📌 Defaults & scope
Works on any symbol with OHLCV
No alerts, no strategy results, no performance claims
Resampling Reverse Engineering Bands [DW]This is an experimental study designed to reverse engineer price levels from centered oscillators at user defined sample rates.
This study aims to educate users on the process of oscillator reverse engineering, and to give users an alternative perspective on some of the most commonly used oscillators in the trading game.
Reverse engineering price levels from an oscillator is actually a rather simple, straightforward process.
Rather than plugging price values into a function to solve for oscillator values, we rearrange the function using some basic algebraic operations and plug in a specified oscillator value to solve for price values instead.
This process tells us what price value is needed in order for the oscillator to equal a certain value.
For example, if you wanted to know what price value would be considered “overbought” or “oversold” according to your oscillator, you can do that using this process.
In this study, the reverse engineering functions are used to calculate the price values of user defined high and low oscillator thresholds, and the price values for the oscillator center.
This allows you to visualize what prices will trigger thresholds as a sort of confidence interval, which is information that isn't inherently available when simply analyzing the oscillator directly.
This script is equipped with three reverse engineering functions to choose from for calculating the band values:
-> Reverse Relative Strength Index (RRSI)
-> Reverse Stochastic Oscillator (RStoch)
-> Reverse Commodity Channel Index (RCCI)
You can easily select the function you want to utilize from the "Band Calculation Type" dropdown tab.
These functions are specially designed to calculate at any sample rate (up to 1 bar per sample) utilizing the process of downsampling that I introduced in my Resampling Filter Pack.
The sample rate can be determined with any of these three methods:
-> BPS - Resamples based on the number of bars.
-> Interval - Resamples based on time in multiples of current charting timeframe.
-> PA - Resamples based on changes in price action by a specified size. The PA algorithm in this script is derived from my Range Filter algorithm.
The range for PA method can be sized in points, pips, ticks, % of price, ATR, average change, and absolute quantity.
Utilizing downsampled rates allows you to visualize the reverse engineered values of an oscillator calculated at larger sample scales.
This can be rather beneficial for trend analysis since lower sample rates completely remove certain levels of noise.
By default, the sample rate is set to 1 BPS, which is the same as bar-to-bar calculation. Feel free to experiment with the sample rate parameters and configure them how you like.
Custom bar colors are included as well. The color scheme is based on disparity between sources and the reverse engineered center level.
In addition, background highlights are included to indicate when price is outside the bands, thus indicating "overbought" and "oversold" conditions according to the thresholds you set.
I also included four external output variables for easy integration of signals with other scripts:
-> Trend Signals (Current Resolution Prices) - Outputs 1 for bullish and -1 for bearish based on disparity between current resolution source and the central level output.
-> Trend Signals (Resampled Prices) - Outputs 1 for bullish and -1 for bearish based on disparity between resampled source and the central level output.
-> Outside Band Signal (Current Resolution Prices) - Outputs 1 for overbought and -1 for oversold based on current resolution source being outside the bands. Returns 0 otherwise.
-> Outside Band Signal (Resampled Prices) - Outputs 1 for overbought and -1 for oversold based on resampled source being outside the bands. Returns 0 otherwise.
To use these signals with another script, simply select the corresponding external output you want to use from your script's source input dropdown tab.
Reverse engineering oscillators is a simple, yet powerful approach to incorporate into your momentum or trend analysis setup.
By incorporating projected price levels from oscillators into our analysis setups, we are able to gain valuable insights, make (potentially) smarter trading decisions, and visualize the oscillators we know and love in a totally different way.
I hope you all find this script useful and enjoyable!
