Crosses MAs (+ BB, RSI)This indicator displays the crosses of MA's with different length, the Bollinger bands and the current value of the RSI in table. Almost all of this can be customized.
Bandes de Bollinger (BB)
Trend Filter Finder Trend Filter Finder
趋势过滤器
This indicator combines Bollinger Bands and Keltner Channels to identify market trends and volatility conditions.
该指标结合了布林带和肯特纳通道来识别市场趋势和波动条件。
Usage 使用方法:
- Black bar color indicates not recommended for buy signals
K线呈黑色表示当前不建议释放买入信号
Multi-Band Comparison (Uptrend)Multi-Band Comparison
Overview:
The Multi-Band Comparison indicator is engineered to reveal critical levels of support and resistance in strong uptrends. In a healthy upward market, the price action will adhere closely to the 95th percentile line (the Upper Quantile Band), effectively “riding” it. This indicator combines a modified Bollinger Band (set at one standard deviation), quantile analysis (95% and 5% levels), and power‑law math to display a dynamic picture of market structure—highlighting a “golden channel” and robust support areas.
Key Components & Calculations:
The Golden Channel: Upper Bollinger Band & Upper Std Dev Band of the Upper Quantile
Upper Bollinger Band:
Calculation:
boll_upper=SMA(close,length)+(boll_mult×stdev)
boll_upper=SMA(close,length)+(boll_mult×stdev) Here, the 20-period SMA is used along with one standard deviation of the close, where the multiplier (boll_mult) is 1.0.
Role in an Uptrend:
In a healthy uptrend, price rides near the 95th percentile line. When price crosses above this Upper Bollinger Band, it confirms strong bullish momentum.
Upper Std Dev Band of the Upper Quantile (95th Percentile) Band:
Calculation:
quant_upper_std_up=quant_upper+stdev
quant_upper_std_up=quant_upper+stdev The Upper Quantile Band, quant_upperquant_upper, is calculated as the 95th percentile of recent price data. Adding one standard deviation creates an extension that accounts for normal volatility around this extreme level.
The Golden Channel:
When the price crosses above the Upper Bollinger Band, the Upper Std Dev Band of the Upper Quantile immediately shifts to gold (yellow) and remains gold until price falls below the Bollinger level. Together, these two lines form the “golden channel”—a visual hallmark of a healthy uptrend where the price reliably hugs the 95th percentile level.
Upper Power‑Law Band
Calculation:
The Upper Power‑Law Band is derived in two steps:
Determine the Extreme Return Factor:
power_upper=Percentile(returns,95%)
power_upper=Percentile(returns,95%) where returns are computed as:
returns=closeclose −1.
returns=close close−1.
Scale the Current Price:
power_upper_band=close×(1+power_upper)
power_upper_band=close×(1+power_upper)
Rationale and Correlation:
By focusing on the upper 5% of returns (reflecting “fat tails”), the Upper Power‑Law Band captures extreme but statistically expected movements. In an uptrend, its value often converges with the Upper Std Dev Band of the Upper Quantile because both measures reflect heightened volatility and extreme price levels. When the Upper Power‑Law Band exceeds the Upper Std Dev Band, it can signal a temporary overextension.
Upper Quantile Band (95% Percentile)
Calculation:
quant_upper=Percentile(price,95%)
quant_upper=Percentile(price,95%) This level represents where 95% of past price data falls below, and in a robust uptrend the price action practically rides this line.
Color Logic:
Its color shifts from a neutral (blackish) tone to a vibrant, bullish hue when the Upper Power‑Law Band crosses above it—signaling extra strength in the trend.
Lower Quantile and Its Support
Lower Quantile Band (5% Percentile):
Calculation:
quant_lower=Percentile(price,5%)
quant_lower=Percentile(price,5%)
Behavior:
In a healthy uptrend, price remains well above the Lower Quantile Band. It turns red only when price touches or crosses it, serving as a warning signal. Under normal conditions it remains bright green, indicating the market is not nearing these extreme lows.
Lower Std Dev Band of the Lower Quantile:
This line is calculated by subtracting one standard deviation from quant_lowerquant_lower and typically serves as absolute support in nearly all conditions (except during gap or near-gap moves). Its consistent role as support provides traders with a robust level to monitor.
How to Use the Indicator:
Golden Channel and Trend Confirmation:
As price rides the Upper Quantile (95th percentile) perfectly in a healthy uptrend, the Upper Bollinger Band (1 stdev above SMA) and the Upper Std Dev Band of the Upper Quantile form a “golden channel” once price crosses above the Bollinger level. When this occurs, the Upper Std Dev Band remains gold until price dips back below the Bollinger Band. This visual cue reinforces trend strength.
Power‑Law Insights:
The Upper Power‑Law Band, which is based on extreme (95th percentile) returns, tends to align with the Upper Std Dev Band. This convergence reinforces that extreme, yet statistically expected, price moves are occurring—indicating that even though the price rides the 95th percentile, it can only stretch so far before a correction or consolidation.
Support Indicators:
Primary and Secondary Support in Uptrends:
The Upper Bollinger Band and the Lower Std Dev Band of the Upper Quantile act as support zones for minor retracements in the uptrend.
Absolute Support:
The Lower Std Dev Band of the Lower Quantile serves as an almost invariable support area under most market conditions.
Conclusion:
The Multi-Band Comparison indicator unifies advanced statistical techniques to offer a clear view of uptrend structure. In a healthy bull market, price action rides the 95th percentile line with precision, and when the Upper Bollinger Band is breached, the corresponding Upper Std Dev Band turns gold to form a “golden channel.” This, combined with the Power‑Law analysis that captures extreme moves, and the robust lower support levels, provides traders with powerful, multi-dimensional insights for managing entries, exits, and risk.
Disclaimer:
Trading involves risk. This indicator is for educational purposes only and does not constitute financial advice. Always perform your own analysis before making trading decisions.
ema,atr and with Bollinger Bands (Indicator)1. Indicator Overview
The indicator:
Displays EMA and Bollinger Bands on the chart.
Tracks price behavior during a user-defined trading session.
Generates long/short signals based on crossover conditions of EMA or Bollinger Bands.
Provides alerts for potential entries and exits.
Visualizes tracked open and close prices to help traders interpret market conditions.
2. Key Features
Inputs
session_start and session_end: Define the active trading session using timestamps.
E.g., 17:00:00 (5:00 PM) for session start and 15:40:00 (3:40 PM) for session end.
atr_length: The lookback period for the Average True Range (ATR), used for price movement scaling.
bb_length and bb_mult: Control the Bollinger Bands' calculation, allowing customization of sensitivity.
EMA Calculation
A 21-period EMA is calculated using:
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ema21 = ta.ema(close, 21)
Purpose: Acts as a dynamic support/resistance level. Price crossing above or below the EMA indicates potential trend changes.
Bollinger Bands
Purpose: Measure volatility and identify overbought/oversold conditions.
Formula:
Basis: Simple Moving Average (SMA) of closing prices.
Upper Band: Basis + (Standard Deviation × Multiplier).
Lower Band: Basis - (Standard Deviation × Multiplier).
Code snippet:
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bb_basis = ta.sma(close, bb_length)
bb_dev = bb_mult * ta.stdev(close, bb_length)
bb_upper = bb_basis + bb_dev
bb_lower = bb_basis - bb_dev
Session Tracking
The in_session variable ensures trading signals are only generated within the defined session:
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in_session = time >= session_start and time <= session_end
3. Entry Conditions
EMA Crossover
Long Signal: When the price crosses above the EMA during the session:
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ema_long_entry_condition = ta.crossover(close, ema21) and in_session and barstate.isconfirmed
Short Signal: When the price crosses below the EMA during the session:
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ema_short_entry_condition = ta.crossunder(close, ema21) and in_session and barstate.isconfirmed
Bollinger Bands Crossover
Long Signal: When the price crosses above the upper Bollinger Band:
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bb_long_entry_condition = ta.crossover(close, bb_upper) and in_session and barstate.isconfirmed
Short Signal: When the price crosses below the lower Bollinger Band:
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bb_short_entry_condition = ta.crossunder(close, bb_lower) and in_session and barstate.isconfirmed
4. Tracked Prices
The script keeps track of key open/close prices using the following logic:
If a long signal is detected and the close is above the open, it tracks the open price.
If the close is below the open, it tracks the close price.
Tracked values are scaled using *4 (custom scaling logic).
These tracked prices are plotted for visual feedback:
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plot(tracked_open, color=color.red, title="Tracked Open Price", linewidth=2)
plot(tracked_close, color=color.green, title="Tracked Close Price", linewidth=2)
5. Exit Conditions
Long Exit: When the price drops below the tracked open and close price:
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exit_long_condition = (close < open) and (tracked_close < tracked_open) and barstate.isconfirmed
Short Exit: When the price rises above the tracked open and close price:
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exit_short_condition = (close > open) and (tracked_close > tracked_open) and barstate.isconfirmed
6. Visualization
Plots:
21 EMA, Bollinger Bands (Basis, Upper, Lower).
Tracked open/close prices for additional context.
Background Colors:
Green for long signals, red for short signals (e.g., ema_long_entry_condition triggers a green background).
7. Alerts
The script defines alerts to notify the user about key events:
Entry Alerts:
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alertcondition(ema_long_entry_condition, title="EMA Long Entry", message="EMA Long Entry")
alertcondition(bb_long_entry_condition, title="BB Long Entry", message="BB Long Entry")
Exit Alerts:
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alertcondition(exit_long_condition, title="Exit Long", message="Exit Long")
8. Purpose
Trend Following: EMA crossovers help identify trend changes.
Volatility Breakouts: Bollinger Band crossovers highlight overbought/oversold regions.
Custom Sessions: Trading activity is restricted to specific time periods for precision.
Bank Nifty Weighted IndicatorThe Bank Nifty Weighted Indicator is a comprehensive trading tool designed to analyze the performance of the Bank Nifty Index using its constituent stocks' weighted prices. It combines advanced technical analysis tools, including Bollinger Bands, to provide highly accurate buy and sell signals, especially for intraday traders and scalpers.
Pivot + 7 EMA + Bollinger Band [by sameer]here you get one and only indicator to have bollinger band and pivot.
Momentum Range Break (MRB) Strategy - JaysalgohutAbout the Momentum Range Break (MRB) Strategy
The Momentum Range Break (MRB) strategy is a technical trading approach designed for short-term time frames, typically ranging from 5 to 30 minutes. It aims to identify and capitalize on price movements that break and close above or below an opening range, leveraging momentum and volatility dynamics to pinpoint high-probability setups.
Key components of the strategy include:
1. Opening Range Breakout (ORB): This concept, originally popularized by Toby Crabel, serves as the foundation for identifying breakout opportunities.
2. Stochastic Momentum Oscillator: Used to gauge momentum and strength, ensuring entries align with prevailing trends.
3. Bollinger Band Width Percentile (BBWP): Utilized to measure volatility expansion, particularly in setups requiring stronger price action dynamics. Credits to The_Caretaker for this part.
4. Fibonacci Ranges: Applied to project potential upward or downward price targets based on breakout levels.
This strategy has demonstrated high win rates across various cryptocurrency trading pairs during backtesting, making it an effective tool for short-term traders seeking to trade intraday momentum.
How everything works together:
- First, price must close above the opening range high to consider as a valid entry condition
- The stochastic momentum oscillator must have an uptick on that same candle closure
- The BBWP may/may not be used depending on the strategy chosen in the settings. If used, the BBWP must have an uptick as well on the same candle close
- The magic in this strategy lies in finding the sweet spot between the range of values of stochastic and range of values of the BBWP where both having a concurrent uptick and a closure above the opening range (ORB) would yield a high win rate for certain crypto pairs.
- Exit conditions are adjustable and usually is a certain fibonacci range upward for longs, and downward for shorts.
Full strategy details will be provided once access has been granted.
This strategy does not repaint. Feel free to test it yourself.
Important Considerations
- While the MRB strategy is built on rigorous backtesting and established technical principles, it is essential to note that past performance does not guarantee future results.
- This strategy does not curve fit its data and does not repaint.
- This strategy relies on a high win rate to achieve a consistently positive profit factor and full equity deployment in the strategy has been tested without failure. A failure is defined as equity going to zero before even having a chance to turn profitable. This has not happened once at all in the strategy's backtested results.
EMA + BB + ST indicatorThe EMA + BB + ST Indicator is a versatile and compact trading tool designed for traders using free accounts with limited indicators. It combines three powerful technical analysis tools into one:
Exponential Moving Average (EMA): Tracks the trend and smooths price data, making it easier to identify market direction and potential reversals. Configurable to various timeframes for both short-term and long-term trend analysis.
Bollinger Bands (BB): Measures volatility and provides dynamic support and resistance levels. Useful for spotting overbought/oversold conditions and breakout opportunities.
SuperTrend (ST): A trend-following indicator that overlays the chart with buy/sell signals. It simplifies decision-making by highlighting clear trend reversals.
This single indicator offers a streamlined experience, helping traders:
Save indicator slots on free platforms like TradingView.
Gain comprehensive market insights from a single chart.
Easily customize inputs for EMA, BB, and ST to suit various strategies.
Ideal for swing, day, and long-term traders who want to maximize efficiency and performance on free accounts without sacrificing advanced functionality.
EURCAD Score Indicator TrALorem ipsum dolor sit amet, consectetuer adipiscing elit. Nam sed tellus id magna elementum tincidunt. Integer vulputate sem a nibh rutrum consequat. Etiam neque. Praesent dapibus. Aliquam erat volutpat. Integer imperdiet lectus quis justo. Sed convallis magna eu sem. Maecenas fermentum, sem in pharetra pellentesque, velit turpis volutpat ante, in pharetra metus odio a lectus. Integer malesuada. Nullam at arcu a est sollicitudin euismod. Aliquam ornare wisi eu metus. Neque porro quisquam est, qui dolorem ipsum quia dolor sit amet, consectetur, adipisci velit, sed quia non numquam eius modi tempora incidunt ut labore et dolore magnam aliquam quaerat voluptatem. Quisque tincidunt scelerisque libero. Proin in tellus sit amet nibh dignissim sagittis.
Fake Double ReserveThis Pine Script code implements the "Fake Double Reserve" indicator, combining several widely-used technical indicators to generate Buy and Sell signals. Here's a detailed breakdown:
Key Indicators Included
Relative Strength Index (RSI):
Used to measure the speed and change of price movements.
Overbought and oversold levels are set at 70 and 30, respectively.
MACD (Moving Average Convergence Divergence):
Compares short-term and long-term momentum with a signal line for trend confirmation.
Stochastic Oscillator:
Measures the relative position of the closing price within a recent high-low range.
Exponential Moving Averages (EMAs):
EMA 20: Short-term trend indicator.
EMA 50 & EMA 200: Medium and long-term trend indicators.
Bollinger Bands:
Shows volatility and potential reversal zones with upper, lower, and basis lines.
Signal Generation
Buy Condition:
RSI crosses above 30 (leaving oversold territory).
MACD Line crosses above the Signal Line.
Stochastic %K crosses above %D.
The closing price is above the EMA 50.
Sell Condition:
RSI crosses below 70 (leaving overbought territory).
MACD Line crosses below the Signal Line.
Stochastic %K crosses below %D.
The closing price is below the EMA 50.
Visualization
Signals:
Buy signals: Shown as green upward arrows below bars.
Sell signals: Shown as red downward arrows above bars.
Indicators on the Chart:
RSI Levels: Horizontal dotted lines at 70 (overbought) and 30 (oversold).
EMAs: EMA 20 (green), EMA 50 (blue), EMA 200 (orange).
Bollinger Bands: Upper (purple), Lower (purple), Basis (gray).
Labels:
Buy and Sell signals are also displayed as labels at relevant bars.
//@version=5
indicator("Fake Double Reserve", overlay=true)
// Include key indicators
rsiLength = 14
rsi = ta.rsi(close, rsiLength)
macdFast = 12
macdSlow = 26
macdSignal = 9
= ta.macd(close, macdFast, macdSlow, macdSignal)
stochK = ta.stoch(close, high, low, 14)
stochD = ta.sma(stochK, 3)
ema20 = ta.ema(close, 20)
ema50 = ta.ema(close, 50)
ema200 = ta.ema(close, 200)
bbBasis = ta.sma(close, 20)
bbUpper = bbBasis + 2 * ta.stdev(close, 20)
bbLower = bbBasis - 2 * ta.stdev(close, 20)
// Detect potential "Fake Double Reserve" patterns
longCondition = ta.crossover(rsi, 30) and ta.crossover(macdLine, signalLine) and ta.crossover(stochK, stochD) and close > ema50
shortCondition = ta.crossunder(rsi, 70) and ta.crossunder(macdLine, signalLine) and ta.crossunder(stochK, stochD) and close < ema50
// Plot signals
if (longCondition)
label.new(bar_index, high, "Buy", style=label.style_label_up, color=color.green, textcolor=color.white)
if (shortCondition)
label.new(bar_index, low, "Sell", style=label.style_label_down, color=color.red, textcolor=color.white)
// Plot buy and sell signals as shapes
plotshape(longCondition, style=shape.labelup, location=location.belowbar, color=color.green, size=size.small, title="Buy Signal")
plotshape(shortCondition, style=shape.labeldown, location=location.abovebar, color=color.red, size=size.small, title="Sell Signal")
// Plot indicators
plot(ema20, color=color.green, linewidth=1, title="EMA 20")
plot(ema50, color=color.blue, linewidth=1, title="EMA 50")
plot(ema200, color=color.orange, linewidth=1, title="EMA 200")
hline(70, "Overbought (RSI)", color=color.red, linestyle=hline.style_dotted)
hline(30, "Oversold (RSI)", color=color.green, linestyle=hline.style_dotted)
plot(bbUpper, color=color.purple, title="Bollinger Band Upper")
plot(bbLower, color=color.purple, title="Bollinger Band Lower")
plot(bbBasis, color=color.gray, title="Bollinger Band Basis")
BBMA. Custom BB + MACustom BB + MA Indicator
This indicator combines Bollinger Bands (BB), Moving Averages (MA), and an Exponential Moving Average (EMA) to provide a comprehensive view of market trends and price volatility.
Features:
Bollinger Bands (BB):
Configurable period and standard deviation.
Displays upper, lower, and midline bands with customizable colors and widths.
Moving Averages (MA):
Includes 5-period and 10-period Weighted Moving Averages (WMA) for both highs and lows.
Customizable colors and line widths for better visualization.
Exponential Moving Average (EMA):
Includes a 50-period EMA with customizable settings.
Usage:
Use Bollinger Bands to gauge price volatility and identify potential breakout or reversal points.
Use Moving Averages for trend direction and short-term price movements.
Use the EMA for a smoother trend analysis and long-term direction.
This indicator is fully customizable, allowing traders to adjust the settings to fit their trading strategies and preferences. Perfect for technical analysis of any market.
BBMA. Custom BB + MACustom BB + MA Indicator
This indicator combines Bollinger Bands (BB), Moving Averages (MA), and an Exponential Moving Average (EMA) to provide a comprehensive view of market trends and price volatility.
Features:
Bollinger Bands (BB):
Configurable period and standard deviation.
Displays upper, lower, and midline bands with customizable colors and widths.
Moving Averages (MA):
Includes 5-period and 10-period Weighted Moving Averages (WMA) for both highs and lows.
Customizable colors and line widths for better visualization.
Exponential Moving Average (EMA):
Includes a 50-period EMA with customizable settings.
Usage:
Use Bollinger Bands to gauge price volatility and identify potential breakout or reversal points.
Use Moving Averages for trend direction and short-term price movements.
Use the EMA for a smoother trend analysis and long-term direction.
This indicator is fully customizable, allowing traders to adjust the settings to fit their trading strategies and preferences. Perfect for technical analysis of any market.
Adaptive Momentum Reversion StrategyThe Adaptive Momentum Reversion Strategy: An Empirical Approach to Market Behavior
The Adaptive Momentum Reversion Strategy seeks to capitalize on market price dynamics by combining concepts from momentum and mean reversion theories. This hybrid approach leverages a Rate of Change (ROC) indicator along with Bollinger Bands to identify overbought and oversold conditions, triggering trades based on the crossing of specific thresholds. The strategy aims to detect momentum shifts and exploit price reversions to their mean.
Theoretical Framework
Momentum and Mean Reversion: Momentum trading assumes that assets with a recent history of strong performance will continue in that direction, while mean reversion suggests that assets tend to return to their historical average over time (Fama & French, 1988; Poterba & Summers, 1988). This strategy incorporates elements of both, looking for periods when momentum is either overextended (and likely to revert) or when the asset’s price is temporarily underpriced relative to its historical trend.
Rate of Change (ROC): The ROC is a straightforward momentum indicator that measures the percentage change in price over a specified period (Wilder, 1978). The strategy calculates the ROC over a 2-period window, making it responsive to short-term price changes. By using ROC, the strategy aims to detect price acceleration and deceleration.
Bollinger Bands: Bollinger Bands are used to identify volatility and potential price extremes, often signaling overbought or oversold conditions. The bands consist of a moving average and two standard deviation bounds that adjust dynamically with price volatility (Bollinger, 2002).
The strategy employs two sets of Bollinger Bands: one for short-term volatility (lower band) and another for longer-term trends (upper band), with different lengths and standard deviation multipliers.
Strategy Construction
Indicator Inputs:
ROC Period: The rate of change is computed over a 2-period window, which provides sensitivity to short-term price fluctuations.
Bollinger Bands:
Lower Band: Calculated with a 18-period length and a standard deviation of 1.7.
Upper Band: Calculated with a 21-period length and a standard deviation of 2.1.
Calculations:
ROC Calculation: The ROC is computed by comparing the current close price to the close price from rocPeriod days ago, expressing it as a percentage.
Bollinger Bands: The strategy calculates both upper and lower Bollinger Bands around the ROC, using a simple moving average as the central basis. The lower Bollinger Band is used as a reference for identifying potential long entry points when the ROC crosses above it, while the upper Bollinger Band serves as a reference for exits, when the ROC crosses below it.
Trading Conditions:
Long Entry: A long position is initiated when the ROC crosses above the lower Bollinger Band, signaling a potential shift from a period of low momentum to an increase in price movement.
Exit Condition: A position is closed when the ROC crosses under the upper Bollinger Band, or when the ROC drops below the lower band again, indicating a reversal or weakening of momentum.
Visual Indicators:
ROC Plot: The ROC is plotted as a line to visualize the momentum direction.
Bollinger Bands: The upper and lower bands, along with their basis (simple moving averages), are plotted to delineate the expected range for the ROC.
Background Color: To enhance decision-making, the strategy colors the background when extreme conditions are detected—green for oversold (ROC below the lower band) and red for overbought (ROC above the upper band), indicating potential reversal zones.
Strategy Performance Considerations
The use of Bollinger Bands in this strategy provides an adaptive framework that adjusts to changing market volatility. When volatility increases, the bands widen, allowing for larger price movements, while during quieter periods, the bands contract, reducing trade signals. This adaptiveness is critical in maintaining strategy effectiveness across different market conditions.
The strategy’s pyramiding setting is disabled (pyramiding=0), ensuring that only one position is taken at a time, which is a conservative risk management approach. Additionally, the strategy includes transaction costs and slippage parameters to account for real-world trading conditions.
Empirical Evidence and Relevance
The combination of momentum and mean reversion has been widely studied and shown to provide profitable opportunities under certain market conditions. Studies such as Jegadeesh and Titman (1993) confirm that momentum strategies tend to work well in trending markets, while mean reversion strategies have been effective during periods of high volatility or after sharp price movements (De Bondt & Thaler, 1985). By integrating both strategies into one system, the Adaptive Momentum Reversion Strategy may be able to capitalize on both trending and reverting market behavior.
Furthermore, research by Chan (1996) on momentum-based trading systems demonstrates that adaptive strategies, which adjust to changes in market volatility, often outperform static strategies, providing a compelling rationale for the use of Bollinger Bands in this context.
Conclusion
The Adaptive Momentum Reversion Strategy provides a robust framework for trading based on the dual concepts of momentum and mean reversion. By using ROC in combination with Bollinger Bands, the strategy is capable of identifying overbought and oversold conditions while adapting to changing market conditions. The use of adaptive indicators ensures that the strategy remains flexible and can perform across different market environments, potentially offering a competitive edge for traders who seek to balance risk and reward in their trading approaches.
References
Bollinger, J. (2002). Bollinger on Bollinger Bands. McGraw-Hill Professional.
Chan, L. K. C. (1996). Momentum, Mean Reversion, and the Cross-Section of Stock Returns. Journal of Finance, 51(5), 1681-1713.
De Bondt, W. F., & Thaler, R. H. (1985). Does the Stock Market Overreact? Journal of Finance, 40(3), 793-805.
Fama, E. F., & French, K. R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research.
Uptrick: Volatility Reversion BandsUptrick: Volatility Reversion Bands is an indicator designed to help traders identify potential reversal points in the market by combining volatility and momentum analysis within one comprehensive framework. It calculates dynamic bands around a simple moving average and issues signals when price interacts with these bands. Below is a fully expanded description, structured in multiple sections, detailing originality, usefulness, uniqueness, and the purpose behind blending standard deviation-based and ATR-based concepts. All references to code have been removed to focus on the written explanation only.
Section 1: Overview
Uptrick: Volatility Reversion Bands centers on a moving average around which various bands are constructed. These bands respond to changes in price volatility and can help gauge potential overbought or oversold conditions. Signals occur when the price moves beyond certain thresholds, which may imply a reversal or significant momentum shift.
Section 2: Originality, Usefulness, Uniqness, Purpose
This indicator merges two distinct volatility measurements—Bollinger Bands and ATR—into one cohesive system. Bollinger Bands use standard deviation around a moving average, offering a baseline for what is statistically “normal” price movement relative to a recent mean. When price hovers near the upper band, it may indicate overbought conditions, whereas price near the lower band suggests oversold conditions. This straightforward construction often proves invaluable in moderate-volatility settings, as it pinpoints likely turning points and gauges a market’s typical trading range.
Yet Bollinger Bands alone can falter in conditions marked by abrupt volatility spikes or sudden gaps that deviate from recent norms. Intraday news, earnings releases, or macroeconomic data can alter market behavior so swiftly that standard-deviation bands do not keep pace. This is where ATR (Average True Range) adds an important layer. ATR tracks recent highs, lows, and potential gaps to produce a dynamic gauge of how much price is truly moving from bar to bar. In quieter times, ATR contracts, reflecting subdued market activity. In fast-moving markets, ATR expands, exposing heightened volatility on each new bar.
By overlaying Bollinger Bands and ATR-based calculations, the indicator achieves a broader situational awareness. Bollinger Bands excel at highlighting relative overbought or oversold areas tied to an established average. ATR simultaneously scales up or down based on real-time market swings, signaling whether conditions are calm or turbulent. When combined, this means a price that barely crosses the Bollinger Band but also triggers a high ATR-based threshold is likely experiencing a volatility surge that goes beyond typical market fluctuations. Conversely, a price breach of a Bollinger Band when ATR remains low may still warrant attention, but not necessarily the same urgency as in a high-volatility regime.
The resulting synergy offers balanced, context-rich signals. In a strong trend, the ATR layer helps confirm whether an apparent price breakout really has momentum or if it is just a temporary spike. In a range-bound market, standard deviation-based Bollinger Bands define normal price extremes, while ATR-based extensions highlight whether a breakout attempt has genuine force behind it. Traders gain clarity on when a move is both statistically unusual and accompanied by real volatility expansion, thus carrying a higher probability of a directional follow-through or eventual reversion.
Practical advantages emerge across timeframes. Scalpers in fast-paced markets appreciate how ATR-based thresholds update rapidly, revealing if a sudden price push is routine or exceptional. Swing traders can rely on both indicators to filter out false signals in stable conditions or identify truly notable moves. By calibrating to changes in volatility, the merged system adapts naturally whether the market is trending, ranging, or transitioning between these phases.
In summary, combining Bollinger Bands (for a static sense of standard-deviation-based overbought/oversold zones) with ATR (for a dynamic read on current volatility) yields an adaptive, intuitive indicator. Traders can better distinguish fleeting noise from meaningful expansions, enabling more informed entries, exits, and risk management. Instead of relying on a single yardstick for all market conditions, this fusion provides a layered perspective, encouraging traders to interpret price moves in the broader context of changing volatility.
Section 3: Why Bollinger Bands and ATR are combined
Bollinger Bands provide a static snapshot of volatility by computing a standard deviation range above and below a central average. ATR, on the other hand, adapts in real time to expansions or contractions in market volatility. When combined, these measures offset each other’s limitations: Bollinger Bands add structure (overbought and oversold references), and ATR ensures responsiveness to rapid price shifts. This synergy helps reduce noisy signals, particularly during sudden market turbulence or extended consolidations.
Section 4: User Inputs
Traders can adjust several parameters to suit their preferences and strategies. These typically include:
1. Lookback length for calculating the moving average and standard deviation.
2. Multipliers to control the width of Bollinger Bands.
3. An ATR multiplier to set the distance for additional reversal bands.
4. An option to display weaker signals when the price merely approaches but does not cross the outer bands.
Section 5: Main Calculations
At the core of this indicator are four important steps:
1. Calculate a basis using a simple moving average.
2. Derive Bollinger Bands by adding and subtracting a product of the standard deviation and a user-defined multiplier.
3. Compute ATR over the same lookback period and multiply it by the selected factor.
4. Combine ATR-based distance with the Bollinger Bands to set the outer reversal bands, which serve as stronger signal thresholds.
Section 6: Signal Generation
The script interprets meaningful reversal points when the price:
1. Crosses below the lower outer band, potentially highlighting oversold conditions where a bullish reversal may occur.
2. Crosses above the upper outer band, potentially indicating overbought conditions where a bearish reversal may develop.
Section 7: Visualization
The indicator provides visual clarity through labeled signals and color-coded references:
1. Distinct colors for upper and lower reversal bands.
2. Markers that appear above or below bars to denote possible buying or selling signals.
3. A gradient bar color scheme indicating a bar’s position between the lower and upper bands, helping traders quickly see if the price is near either extreme.
Section 8: Weak Signals (Optional)
For those preferring early cues, the script can highlight areas where the price nears the outer bands. When weak signals are enabled:
1. Bars closer to the upper reversal zone receive a subtle marker suggesting a less robust, yet still noteworthy, potential selling area.
2. Bars closer to the lower reversal zone receive a subtle marker suggesting a less robust, yet still noteworthy, potential buying area.
Section 9: Simplicity, Effectiveness, and Lower Timeframes
Although combining standard deviation and ATR involves sophisticated volatility concepts, this indicator is visually straightforward. Reversal bands and gradient-colored bars make it easy to see at a glance when price approaches or crosses a threshold. Day traders operating on lower timeframes benefit from such clarity because it helps filter out minor fluctuations and focus on more meaningful signals.
Section 10: Adaptability across Market Phases
Because both the standard deviation (for Bollinger Bands) and ATR adapt to changing volatility, the indicator naturally adjusts to various environments:
1. Trending: The additional ATR-based outer bands help distinguish between temporary pullbacks and deeper reversals.
2. Ranging: Bollinger Bands often remain narrower, identifying smaller reversals, while the outer ATR bands remain relatively close to the main bands.
Section 11: Reduced Noise in High-Volatility Scenarios
By factoring ATR into the band calculations, the script widens or narrows the thresholds during rapid market fluctuations. This reduces the amount of false triggers typically found in indicators that rely solely on fixed calculations, preventing overreactions to abrupt but short-lived price spikes.
Section 12: Incorporation with Other Technical Tools
Many traders combine this indicator with oscillators such as RSI, MACD, or Stochastic, as well as volume metrics. Overbought or oversold signals in momentum oscillators can provide additional confirmation when price reaches the outer bands, while volume spikes may reinforce the significance of a breakout or potential reversal.
Section 13: Risk Management Considerations
All trading strategies carry risk. This indicator, like any tool, can and does produce losing trades if price unexpectedly reverses again or if broader market conditions shift rapidly. Prudent traders employ protective measures:
1. Stop-loss orders or trailing stops.
2. Position sizing that accounts for market volatility.
3. Diversification across different asset classes when possible.
Section 14: Overbought and Oversold Identification
Standard Bollinger Bands highlight regions where price might be overextended relative to its recent average. The extended ATR-based reversal bands serve as secondary lines of defense, identifying moments when price truly stretches beyond typical volatility bounds.
Section 15: Parameter Customization for Different Needs
Users can tailor the script to their unique preferences:
1. Shorter lookback settings yield faster signals but risk more noise.
2. Higher multipliers spread the bands further apart, filtering out small moves but generating fewer signals.
3. Longer lookback periods smooth out market noise, often leading to more stable but less frequent trading cues.
Section 16: Examples of Different Trading Styles
1. Day Traders: Often reduce the length to capture quick price swings.
2. Swing Traders: May use moderate lengths such as 20 to 50 bars.
3. Position Traders: Might opt for significantly longer settings to detect macro-level reversals.
Section 17: Performance Limitations and Reality Check
No technical indicator is free from false signals. Sudden fundamental news events, extreme sentiment changes, or low-liquidity conditions can render signals less reliable. Backtesting and forward-testing remain essential steps to gauge whether the indicator aligns well with a trader’s timeframe, risk tolerance, and instrument of choice.
Section 18: Merging Volatility and Momentum
A critical uniqueness of this indicator lies in how it merges Bollinger Bands (standard deviation-based) with ATR (pure volatility measure). Bollinger Bands provide a relative measure of price extremes, while ATR dynamically reacts to market expansions and contractions. Together, they offer an enhanced perspective on potential market turns, ideally reducing random noise and highlighting moments where price has traveled beyond typical bounds.
Section 19: Purpose of this Merger
The fundamental purpose behind blending standard deviation measures with real-time volatility data is to accommodate different market behaviors. Static standard deviation alone can underreact or overreact in abnormally volatile conditions. ATR alone lacks a baseline reference to normality. By merging them, the indicator aims to provide:
1. A versatile dynamic range for both typical and extreme moves.
2. A filter against frequent whipsaws, especially in choppy environments.
3. A visual framework that novices and experts can interpret rapidly.
Section 20: Summary and Practical Tips
Uptrick: Volatility Reversion Bands offers a powerful tool for traders looking to combine volatility-based signals with momentum-derived reversals. It emphasizes clarity through color-coded bars, defined reversal zones, and optional weak signal markers. While potentially useful across all major timeframes, it demands ongoing risk management, realistic expectations, and careful study of how signals behave under different market conditions. No indicator serves as a crystal ball, so integrating this script into an overall strategy—possibly alongside volume data, fundamentals, or momentum oscillators—often yields the best results.
Disclaimer and Educational Use
This script is intended for educational and informational purposes. It does not constitute financial advice, nor does it guarantee trading success. Sudden economic events, low-liquidity times, and unexpected market behaviors can all undermine technical signals. Traders should use proper testing procedures (backtesting and forward-testing) and maintain disciplined risk management measures.
Bollinger Bands & RSI Signal Scanner (PS by TJ)This Pine Script combines Bollinger Bands and Relative Strength Index (RSI) to identify potential buy and sell signals on the chart. It is designed for use on the TradingView platform and provides both visual cues and alerts.
Features:
Bollinger Bands Calculation:
Based on a Simple Moving Average (SMA) of the price.
Upper and lower bands are calculated using a user-defined multiplier for standard deviations.
RSI Integration:
Calculates the RSI with a user-configurable period.
Utilizes overbought (80) and oversold (20) thresholds to refine signals.
Combined Signals:
Buy Signal: Triggered when the price crosses above the lower Bollinger Band, and RSI is below the oversold threshold.
Sell Signal: Triggered when the price crosses below the upper Bollinger Band, and RSI is above the overbought threshold.
Visual Indicators:
Buy signals are displayed as upward-pointing labels below the price bars.
Sell signals are displayed as downward-pointing labels above the price bars.
MTF ScalpingMTF Scalping - A Powerful Multi-Time Frame Indicator for Scalping
The MTF Scalping indicator is designed specifically for scalpers who want to incorporate multi-time frame (MTF) analysis into their trading strategies. This innovative tool allows you to identify key market movements by leveraging higher time frame data while trading on lower time frames like the 1-minute chart.
Key Features:
Multi-Time Frame (MTF) Analysis:
Combines the data from your current time frame with that of a higher time frame, giving you a broader perspective on market direction.
Perfect for anticipating major price moves while maintaining precision for quick entries and exits.
Customizable Bollinger Bands:
Evaluate market volatility with adjustable Bollinger Bands.
Analyze band width to detect phases of market expansion or contraction.
Dynamic RSI Analysis:
Uses the RSI indicator to confirm bullish or bearish trends.
Merges RSI signals with Bollinger Band data for enhanced reliability.
Trend Detection & Expansion Movements:
Automatically identifies bullish and bearish trends using advanced algorithms.
Highlights periods of significant market expansion, helping you capitalize on trading opportunities.
Optimized Real-Time Alerts:
Generates real-time alerts when a new bullish or bearish signal is detected.
Ensures you stay responsive and never miss a potential trade.
Clear Visual Representation:
Highlights areas of interest on the chart with distinct colors (red for bearish signals, green for bullish signals).
Plots Bollinger Bands and the moving average for easy visualization of volatility.
Why Use MTF Scalping?
Tailored for Fast Scalping: Helps you quickly identify opportunities by combining multiple time frame perspectives.
Efficient and Reactive: Optimized alerts minimize the need for constant chart monitoring.
Versatile: Suitable for various trading styles, including trend-following and range trading.
Customization Options:
The indicator is fully customizable, allowing you to adjust:
The time frame for MTF analysis.
Bollinger Band parameters (period and standard deviation multiplier).
RSI period and expansion threshold.
Important Note:
While this indicator uses multi-time frame data, it may recalculate on unfinished bars due to the nature of MTF analysis. This does not affect its performance in real-time but is worth considering during historical backtesting.
The MTF Scalping indicator is your ultimate tool for scalping, combining simplicity and efficiency. Try it now to enhance your intraday trading and maximize your profits!
Forex Pair Yield Momentum This Pine Script strategy leverages yield differentials between the 2-year government bond yields of two countries to trade Forex pairs. Yield spreads are widely regarded as a fundamental driver of currency movements, as highlighted by international finance theories like the Interest Rate Parity (IRP), which suggests that currencies with higher yields tend to appreciate due to increased capital flows:
1. Dynamic Yield Spread Calculation:
• The strategy dynamically calculates the yield spread (yield_a - yield_b) for the chosen Forex pair.
• Example: For GBP/USD, the spread equals US 2Y Yield - UK 2Y Yield.
2. Momentum Analysis via Bollinger Bands:
• Yield momentum is computed as the difference between the current spread and its moving
Bollinger Bands are applied to identify extreme deviations:
• Long Entry: When momentum crosses below the lower band.
• Short Entry: When momentum crosses above the upper band.
3. Reversal Logic:
• An optional checkbox reverses the trading logic, allowing long trades at the upper band and short trades at the lower band, accommodating different market conditions.
4. Trade Management:
• Positions are held for a predefined number of bars (hold_periods), and each trade uses a fixed contract size of 100 with a starting capital of $20,000.
Theoretical Basis:
1. Yield Differentials and Currency Movements:
• Empirical studies, such as Clarida et al. (2009), confirm that interest rate differentials significantly impact exchange rate dynamics, especially in carry trade strategies .
• Higher-yields tend to appreciate against lower-yielding currencies due to speculative flows and demand for higher returns.
2. Bollinger Bands for Momentum:
• Bollinger Bands effectively capture deviations in yield momentum, identifying opportunities where price returns to equilibrium (mean reversion) or extends in trend-following scenarios (momentum breakout).
• As Bollinger (2001) emphasized, this tool adapts to market volatility by dynamically adjusting thresholds .
References:
1. Dornbusch, R. (1976). Expectations and Exchange Rate Dynamics. Journal of Political Economy.
2. Obstfeld, M., & Rogoff, K. (1996). Foundations of International Macroeconomics.
3. Clarida, R., Davis, J., & Pedersen, N. (2009). Currency Carry Trade Regimes. NBER.
4. Bollinger, J. (2001). Bollinger on Bollinger Bands.
5. Mendelsohn, L. B. (2006). Forex Trading Using Intermarket Analysis.
Soul Button Scalping (1 min chart) V 1.0Indicator Description
- P Signal: The foundational buy signal. It should be confirmed by observing RSI divergence on the 1-minute chart.
- Green, Orange, and Blue Signals: Three buy signals generated through the combination of multiple oscillators. These signals should also be cross-referenced with the RSI on the 1-minute chart.
- Big White and Big Yellow Signals: These represent strong buy signals, triggered in extreme oversold conditions.
- BEST BUY Signal: The most reliable and powerful buy signal available in this indicator.
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Red Sell Signal: A straightforward sell signal indicating potential overbought conditions.
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Usage Guidance
This scalping indicator is specifically designed for use on the 1-minute chart, incorporating data from the 5-minute chart for added context. It is most effective when used in conjunction with:
• VWAP (Volume Weighted Average Price), already included in the indicator.
• RSI on the 1-minute chart, which should be opened as a separate indicator.
• Trendlines, structure breakouts, and price action analysis to confirm signals.
Intended for Crypto Scalping:
The indicator is optimized for scalping cryptocurrency markets.
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Future Enhancements:
• Integration of price action and candlestick patterns.
• A refined version tailored for trading futures contracts, specifically ES and MES in the stock market.
Full Spectrum Delta BandsI created the Full Spectrum Delta Bands (FullSpec ΔBB) to go beyond traditional Bollinger Bands by incorporating both OHLC (Open, High, Low, Close) and Close-based data into the calculations. Instead of relying solely on closing prices, this indicator evaluates deviations from the complete bar range (OHLC), offering a more accurate view of market behavior.
A key feature is the Delta Flip, which highlights shifts between OHLC and Close-based bands. These flips are visually marked with color changes, signaling potential trend reversals, breakout zones, or volatility shifts. Traders can use these moments as inflection points to refine their entry and exit strategies.
The indicator also supports customizable sensitivity and deviation multiplier settings, allowing it to adapt to different trading styles and timeframes. Lower deviation values (e.g., 1σ or 1.5σ) are ideal for scalping on shorter timeframes like 5-min or 15-min charts, while higher values (e.g., 2.5σ or 3σ) are better suited for long-term trend analysis on weekly or monthly charts. The standard deviation multiplier fine-tunes the upper and lower bands to match specific trading goals and market conditions.
I designed Full Spectrum Delta Bands to provide deeper insights and a clearer view of market dynamics compared to traditional Bollinger Bands. Whether you’re a scalper, swing trader, or long-term investor, this tool helps you make informed and confident trading decisions.
Williams BBDiv Signal [trade_lexx]📈 Williams BBDiv Signal — Improve your trading strategy with accurate signals!
Introducing Williams BBDiv Signal , an advanced trading indicator designed for a comprehensive analysis of market conditions. This indicator combines Williams%R with Bollinger Bands, providing traders with a powerful tool for generating buy and sell signals, as well as detecting divergences. It is ideal for traders who need an advantage in detecting changing trends and market conditions.
🔍 How signals work
— A buy signal is generated when the Williams %R line crosses the lower Bollinger Bands band from bottom to top. This indicates that the market may be oversold and ready for a rebound. They are displayed as green triangles located under the Williams %R graph. On the main chart, buy signals are displayed as green triangles labeled "Buy" under candlesticks.
— A sell signal is generated when the Williams %R line crosses the upper Bollinger Bands band from top to bottom. This indicates that the market may be overbought and ready for a correction. They are displayed as red triangles located above the Williams %R chart. On the main chart, the sell signals are displayed as red triangles with the word "Sell" above the candlesticks.
— Minimum Bars Between Signals
The user can adjust the minimum number of bars between the signals to avoid false signals. This helps to filter out noise and improve signal quality.
— Mode "Wait for Opposite Signal"
In this mode, buy and sell signals are generated only after receiving the opposite signal. This adds an additional level of filtering and helps to avoid false alarms.
— Mode "Overbought and Oversold Zones"
A buy signal is generated only when Williams %R is below the -80 level (Lower Band). A sell signal is generated only when Williams %R is above -20 (Upper Band).
📊 Divergences
— Bullish divergence occurs when Williams%R shows a higher low while price shows a lower low. This indicates a possible upward reversal. They are displayed as green lines and labels labeled "Bull" on the Williams %R chart. On the main chart, bullish divergences are displayed as green triangles labeled "Bull" under candlesticks.
— A bearish divergence occurs when Williams %R shows a lower high, while the price shows a higher high. This indicates a possible downward reversal. They are displayed as red lines and labels labeled "Bear" on the Williams %R chart. On the main chart, bearish divergences are displayed as red triangles with the word "Bear" above the candlesticks.
— 🔌Connector Signal🔌 and 🔌Connector Divergence🔌
It allows you to connect the indicator to trading strategies and test signals throughout the trading history. This makes the indicator an even more powerful tool for traders who want to test the effectiveness of their strategies on historical data.
🔔 Alerts
The indicator provides the ability to set up alerts for buy and sell signals, as well as for divergences. This allows traders to keep abreast of important market developments without having to constantly monitor the chart.
🎨 Customizable Appearance
Customize the appearance of Williams BBDiv Signal according to your preferences to make the analysis more convenient and visually pleasing. In the indicator settings section, you can change the colors of the buy and sell signals, as well as divergences, so that they stand out on the chart and are easily visible.
🔧 How it works
— The indicator starts by calculating the Williams %R and Bollinger Bands values for a certain period to assess market conditions. Initial assumptions are introduced for overbought and oversold levels, as well as for the standard deviation of the Bollinger Bands. The indicator then analyzes these values to generate buy and sell signals. This classification helps to determine the appropriate level of volatility for signal calculation. As the market evolves, the indicator dynamically adjusts, providing information about the trend and volatility in real time.
Quick Guide to Using Williams BBDiv Signal
— Add the indicator to your favorites by clicking on the star icon. Adjust the parameters, such as the period length for Williams %R, the type of moving average and the standard deviation for Bollinger Bands, according to your trading style. Or leave all the default settings.
— Adjust the signal filters to improve the quality of the signals and avoid false alarms, adjust the filters in the "Signal Settings" section.
— Turn on alerts so that you don't miss important trading opportunities and don't constantly sit at the chart, set up alerts for buy and sell signals, as well as for divergences. This will allow you to keep abreast of all key market developments and respond to them in a timely manner, without being distracted from other business.
— Use signals. They will help you determine the optimal entry and exit points for your positions. Also, pay attention to bullish and bearish divergences, which may indicate possible market reversals and provide additional trading opportunities.
— Use the 🔌Connector🔌 for deeper analysis and verification of the effectiveness of signals, connect it to your trading strategies. This will allow you to test signals throughout the trading history and evaluate their accuracy based on historical data. Include the indicator in your trading strategy and run testing to see how buy and sell signals have worked in the past. Analyze the test results to determine how reliable the signals are and how they can improve your trading strategy. This will help you make better informed decisions and increase your trading efficiency.
Uptrick: Smart BoundariesThis script is an indicator that combines the RSI (Relative Strength Index) and Bollinger Bands to highlight potential points where price momentum and volatility may both be at extreme levels. Below is a detailed explanation of its components, how it calculates signals, and why these two indicators have been merged into one tool. This script is intended solely for educational purposes and for traders who want to explore the combined use of momentum and volatility measures. Please remember that no single indicator guarantees profitable results.
Purpose of This Script
This script is designed to serve as a concise, all-in-one tool for traders seeking to track both momentum and volatility extremes in real time. By overlaying RSI signals with Bollinger Band boundaries, it helps users quickly identify points on a chart where price movement may be highly stretched. The goal is to offer a clearer snapshot of potential overbought or oversold conditions without requiring two separate indicators. Additionally, its optional pyramiding feature enables users to manage how many times they initiate trades when signals repeat in the same direction. Through these combined functions, the script aims to streamline technical analysis by consolidating two popular measures—momentum via RSI and volatility via Bollinger Bands—into a single, manageable interface.
1. Why Combine RSI and Bollinger Bands
• RSI (Relative Strength Index): This is a momentum oscillator that measures the speed and magnitude of recent price changes. It typically ranges between 0 and 100. Traders often watch for RSI crossing into “overbought” or “oversold” levels because it may indicate a potential shift in momentum.
• Bollinger Bands: These bands are plotted around a moving average, using a standard deviation multiplier to create an upper and lower boundary. They help illustrate how volatile the price has been relative to its recent average. When price moves outside these boundaries, some traders see it as a sign the price may be overstretched and could revert closer to the average.
Combining these two can be useful because it blends two different perspectives on market movement. RSI attempts to identify momentum extremes, while Bollinger Bands track volatility extremes. By looking for moments when both conditions agree, the script tries to highlight points where price might be unusually stretched in terms of both momentum and volatility.
2. How Signals Are Generated
• Buy Condition:
- RSI dips below a specified “oversold” level (for example, 30 by default).
- Price closes below the lower Bollinger Band.
When these occur together, the script draws a label indicating a potential bullish opportunity. The underlying reasoning is that momentum (RSI) suggests a stronger-than-usual sell-off, and price is also stretched below the lower Bollinger Band.
• Sell Condition:
- RSI rises above a specified “overbought” level (for example, 70 by default).
- Price closes above the upper Bollinger Band.
When these occur together, a label is plotted for a potential bearish opportunity. The rationale is that momentum (RSI) may be overheated, and the price is trading outside the top of its volatility range.
3. Pyramiding Logic and Trade Count Management
• Pyramiding refers to taking multiple positions in the same direction when signals keep firing. While some traders prefer just one position per signal, others like to scale into a trade if the market keeps pushing in their favor.
• This script uses variables that keep track of how many recent buy or sell signals have fired. If the count reaches a user-defined maximum, no more signals of that type will trigger additional labels. This protects traders from over-committing to one direction if the market conditions remain “extreme” for a prolonged period.
• If you disable the pyramiding feature, the script will only plot one label per side until the condition resets (i.e., until RSI and price conditions are no longer met).
4. Labels and Visual Feedback
• Whenever a buy or sell condition appears, the script plots a label directly on the chart:
- Buy labels under the price bar.
- Sell labels above the price bar.
These labels make it easier to review where both RSI and Bollinger Band conditions align. It can be helpful for visually scanning the chart to see if the signals show any patterns related to market reversals or trend continuations.
• The Bollinger Bands themselves are plotted so traders can see when the price is approaching or exceeding the upper or lower band. Watching the RSI and Bollinger Band plots simultaneously can give traders more context for each signal.
5. Originality and Usefulness
This script provides a distinct approach by merging two well-established concepts—RSI and Bollinger Bands—within a single framework, complemented by optional pyramiding controls. Rather than using each indicator separately, it attempts to uncover moments when momentum signals from RSI align with volatility extremes highlighted by Bollinger Bands. This combined perspective can aid in spotting areas of possible overextension in price. Additionally, the built-in pyramiding mechanism offers a method to manage multiple signals in the same direction, allowing users to adjust how aggressively they scale into trades. By integrating these elements together, the script aims to deliver a tool that caters to diverse trading styles while remaining straightforward to configure and interpret.
6. How to Use the Indicator
• Configure the Inputs:
- RSI Length (the lookback period used for the RSI calculation).
- RSI Overbought and Oversold Levels.
- Bollinger Bands Length and Multiplier (defines the moving average period and the degree of deviation).
- Option to reduce pyramiding.
• Set Alerts (Optional):
- You can create TradingView alerts for when these conditions occur, so you do not have to monitor the chart constantly. Choose the buy or sell alert conditions in your alert settings.
• Integration in a Trading Plan:
- This script alone is not a complete trading system. Consider combining it with other forms of analysis, such as support and resistance, volume profiles, or candlestick patterns. Thorough research, testing on historical data, and risk management are always recommended.
7. No Performance Guarantees
• This script does not promise any specific trading results. It is crucial to remember that no single indicator can accurately predict future market movements all the time. The script simply tries to highlight moments when two well-known indicators both point to an extreme condition.
• Actual trading decisions should factor in a range of market information, including personal risk tolerance and broader market conditions.
8. Purpose and Limitations
• Purpose:
- Provide a combined view of momentum (RSI) and volatility (Bollinger Bands) in a single script.
- Assist in spotting times when price may be at an extreme.
- Offer a configurable system for labeling potential buy or sell points based on these extremes.
• Limitations:
- Overbought and oversold conditions can persist for an extended period in trending markets.
- Bollinger Band breakouts do not always result in immediate reversals. Sometimes price keeps moving in the same direction.
- The script does not include a built-in exit strategy or risk management rules. Traders must handle these themselves.
Additional Disclosures
This script is published open-source and does not rely on any external or private libraries. It does not use lookahead methods or repaint signals; all calculations are performed on the current bar without referencing future data. Furthermore, the script is designed for standard candlestick or bar charts rather than non-standard chart types (e.g., Heikin Ashi, Renko). Traders should keep in mind that while the script can help locate potential momentum and volatility extremes, it does not include an exit strategy or account for factors like slippage or commission. All code comes from built-in Pine Script functions and standard formulas for RSI and Bollinger Bands. Anyone reviewing or modifying this script should exercise caution and incorporate proper risk management when applying it to their own trading.
Calculation Details
The script computes RSI by examining a user-defined number of prior bars (the RSI Length) and determining the average of up-moves relative to the average of down-moves over that period. This ratio is then scaled to a 0–100 range, so lower values typically indicate stronger downward momentum, while higher values suggest stronger upward momentum. In parallel, Bollinger Bands are generated by first calculating a simple moving average (SMA) of the closing price for the user-specified length. The script then measures the standard deviation of closing prices over the same period and multiplies it by the chosen factor (the Bollinger Bands Multiplier) to form the upper and lower boundaries around the SMA. These two measures are checked in tandem: if the RSI dips below a certain oversold threshold and price trades below the lower Bollinger Band, a condition is met that may imply a strong short-term sell-off; similarly, if the RSI surpasses the overbought threshold and price rises above the upper Band, it may indicate an overextended move to the upside. The pyramiding counters track how many of these signals occur in sequence, preventing excessive stacking of labels on the chart if conditions remain extreme for multiple bars.
Conclusion
This indicator aims to provide a more complete view of potential market extremes by overlaying the RSI’s momentum readings on top of Bollinger Band volatility signals. By doing so, it attempts to help traders see when both indicators suggest that the market might be oversold or overbought. The optional reduced pyramiding logic further refines how many signals appear, giving users the choice of a single entry or multiple scaling entries. It does not claim any guaranteed success or predictive power, but rather serves as a tool for those wanting to explore this combined approach. Always be cautious and consider multiple factors before placing any trades.
