Mean-Reversion Indicator_V2_SamleeOverview
This is the second version of my mean reversion indicator. It combines a moving average with adaptive standard deviation bands to detect when the price deviates significantly from its mean. The script provides automatic entry/exit signals, real-time PnL tracking, and shaded trade zones to make mean reversion trading more intuitive.
Core Logic
Mean benchmark: Simple Moving Average (MA).
Volatility bands: Standard deviation of the spread (close − MA) defines upper and lower bands.
Trading rules:
Price breaks below the lower band → Enter Long
Price breaks above the upper band → Enter Short
Price reverts to MA → Exit position
What’s different vs. classic Bollinger/Keltner
Bandwidth is based on the standard deviation of the price–MA spread, not raw closing prices.
Entry signals use previous-bar confirmation to reduce intrabar noise.
Exit rule is a mean-touch condition, rather than fixed profit/loss targets.
Enhanced visualization:
A shaded box dynamically shows the distance between entry and current/exit price, making it easy to see profit/loss zones over the holding period.
Instant PnL labels display current position side (Long/Short/Flat) and live profit/loss in both pips and %.
Entry and exit points are clearly marked on the chart with labels and exact prices.
These visualization tools go beyond what most indicators provide, giving traders a clearer, more practical view of trade evolution.
Key Features
Automatic detection of position status (Long / Short / Flat).
Chart labels for entries (“Entry”) and exits (“Exit”).
Real-time floating PnL calculation in both pips and %.
Info panel (top-right) showing entry price, current price, position side, and PnL.
Dynamic shading between entry and current/exit price to visualize profit/loss zones.
Usage Notes & Risk
Mean reversion may underperform in strong trending markets; parameters (len_ma, len_std, mult) should be validated per instrument and timeframe.
Works best on relatively stable, mean-reverting pairs (e.g., AUDNZD).
Risk management is essential: use independent stop-loss rules (e.g., limit risk to 1–2% of equity per trade).
This script is provided for educational purposes only and is not financial advice.
Search in scripts for "band"
02 SMC + BB Breakout (Improved)This strategy combines Smart Money Concepts (SMC) with Bollinger Band breakouts to identify potential trading opportunities. SMC focuses on identifying key price levels and market structure shifts, while Bollinger Bands help pinpoint overbought/oversold conditions and potential breakout points. The strategy also incorporates higher timeframe trend confirmation to filter out trades that go against the prevailing trend.
Key Components:
Bollinger Bands:
Calculated using a Simple Moving Average (SMA) of the closing price and a standard deviation multiplier.
The strategy uses the upper and lower bands to identify potential breakout points.
The SMA (basis) acts as a centerline and potential support/resistance level.
The fill between the upper and lower bands can be toggled by the user.
Higher Timeframe Trend Confirmation:
The strategy allows for optional confirmation of the current trend using a higher timeframe (e.g., daily).
It calculates the SMA of the higher timeframe's closing prices.
A bullish trend is confirmed if the higher timeframe's closing price is above its SMA.
This helps filter out trades that go against the prevailing long-term trend.
Smart Money Concepts (SMC):
Order Blocks:
Simplified as recent price clusters, identified by the highest high and lowest low over a specified lookback period.
These levels are considered potential areas of support or resistance.
Liquidity Zones (Swing Highs/Lows):
Identified by recent swing highs and lows, indicating areas where liquidity may be present.
The Swing highs and lows are calculated based on user defined lookback periods.
Market Structure Shift (MSS):
Identifies potential changes in market structure.
A bullish MSS occurs when the closing price breaks above a previous swing high.
A bearish MSS occurs when the closing price breaks below a previous swing low.
The swing high and low values used for the MSS are calculated based on the user defined swing length.
Entry Conditions:
Long Entry:
The closing price crosses above the upper Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bullish.
A bullish MSS must have occurred.
Short Entry:
The closing price crosses below the lower Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bearish.
A bearish MSS must have occurred.
Exit Conditions:
Long Exit:
The closing price crosses below the Bollinger Band basis.
Or the Closing price falls below 99% of the order block low.
Short Exit:
The closing price crosses above the Bollinger Band basis.
Or the closing price rises above 101% of the order block high.
Position Sizing:
The strategy calculates the position size based on a fixed percentage (5%) of the strategy's equity.
This helps manage risk by limiting the potential loss per trade.
Visualizations:
Bollinger Bands (upper, lower, and basis) are plotted on the chart.
SMC elements (order blocks, swing highs/lows) are plotted as lines, with user-adjustable visibility.
Entry and exit signals are plotted as shapes on the chart.
The Bollinger band fill opacity is adjustable by the user.
Trading Logic:
The strategy aims to capitalize on Bollinger Band breakouts that are confirmed by SMC signals and higher timeframe trend. It looks for breakouts that align with potential market structure shifts and key price levels (order blocks, swing highs/lows). The higher timeframe filter helps avoid trades that go against the overall trend.
In essence, the strategy attempts to identify high-probability breakout trades by combining momentum (Bollinger Bands) with structural analysis (SMC) and trend confirmation.
Key User-Adjustable Parameters:
Bollinger Bands Length
Standard Deviation Multiplier
Higher Timeframe
Higher Timeframe Confirmation (on/off)
SMC Elements Visibility (on/off)
Order block lookback length.
Swing lookback length.
Bollinger band fill opacity.
This detailed description should provide a comprehensive understanding of the strategy's logic and components.
***DISCLAIMER: This strategy is for educational purposes only. It is not financial advice. Past performance is not indicative of future results. Use at your own risk. Always perform thorough backtesting and forward testing before using any strategy in live trading.***
Predictive Order Blocks [CryptoSea]The Predictive Order Blocks Indicator is a unique and innovative tool that enhances market analysis by identifying support and resistance blocks based on standard deviations from a median line. Unlike traditional indicators that rely solely on the close price, this indicator leverages the median line and standard deviations to form areas of interest, rather than targeting a single price point. This approach provides a more accurate representation of market structure, especially during periods of consolidation and expansion.
Key Features
Multi-Term Length Analysis: The indicator offers short, medium, and long-term settings, allowing traders to customise the analysis based on their preferred trading strategy and timeframe. This flexibility ensures that the tool is adaptable to various market conditions and trading styles.
Standard Deviation-Based Order Blocks: The core functionality of the indicator revolves around calculating standard deviations from a median line to form support and resistance blocks. These blocks provide a clearer and more reliable picture of market structure compared to single-point levels. By focusing on areas rather than exact price levels, the indicator helps traders identify zones where price is likely to react, leading to more informed trading decisions.
Dynamic Box Creation: The indicator dynamically creates breakout boxes based on user-selected standard deviation ranges. These boxes are formed at the start of market expansion following periods of consolidation. This feature is particularly useful because it highlights key levels where price is likely to retrace after breaking out, providing traders with actionable insights during market transitions.
Proximity-Based Gradient Colors: The indicator features gradient colors that change based on the price's proximity to the standard deviation bands. This visual aid helps traders quickly assess the current market condition and the potential significance of the support and resistance blocks.
Adaptive Display Options: To accommodate different trading preferences, the indicator includes options to toggle the display of the trend line (median line) and the standard deviation bands. This flexibility allows traders to customise their chart view to match their analysis style, whether they prefer a more clutter-free view or a detailed breakdown of market levels.
In the example below, the indicator shows the bands compressing during a period of consolidation, highlighting the potential for a breakout.
How it Works
Median Line Calculation: The indicator calculates the median line using a user-defined period. This line serves as the central reference point from which the standard deviations are calculated. By using the median line instead of just the close price, the indicator provides a more stable and reliable baseline for identifying support and resistance areas.
Standard Deviation Bands: Around the median line, the indicator calculates multiple standard deviation bands. These bands represent areas where price is statistically likely to find support or resistance. By focusing on these areas, traders can better anticipate where price might react, rather than relying on arbitrary levels.
Dynamic Box Creation and Expansion Detection: The indicator monitors the compression and expansion of the standard deviation bands. During periods of low volatility (squeeze), the bands compress, indicating consolidation. Once the bands start expanding, it signals the potential for a breakout. At this point, the indicator dynamically creates predictive order blocks based on the selected standard deviation range. These blocks highlight key levels where price might retrace or react, providing traders with valuable entry and exit points.
Color-Coded Proximity Alerts: To further enhance usability, the indicator uses color gradients to indicate how close the current price is to the calculated bands. This visual representation helps traders quickly assess the potential significance of the price's current position relative to the support and resistance areas.
In the example below, the indicator shows the bands expanding with the price, triggering the formation of the predictive order block.
In the final example, the price retraces into the order block before bouncing back to the upside, demonstrating the effectiveness of the identified support area.
Alerts
Trend Line Alerts: The indicator provides alerts when the price crosses above or below the trend line (median line). This feature is crucial for traders looking to identify potential trend changes early, allowing them to act quickly on emerging opportunities.
Band Alerts: Alerts are also triggered when the price crosses above or below the upper or lower bands for each standard deviation level. This helps traders identify potential breakout or breakdown scenarios, ensuring they are notified of significant market movements as they happen.
Customisable Alert Conditions: To cater to different trading strategies, the indicator allows users to set alert conditions for each standard deviation band and the trend line. This level of customisation ensures that traders receive alerts that are relevant to their specific trading style and market analysis.
Application
Strategic Decision-Making: The Predictive Order Blocks Indicator assists traders in making informed decisions by providing detailed analysis of potential breakout zones. By identifying key support and resistance areas, the indicator helps traders plan their entries and exits with greater precision.
Trend Confirmation: The indicator reinforces trading strategies by identifying key levels where price is likely to react. This confirmation is crucial for traders looking to enter trades with higher confidence.
Customized Analysis: The indicator adapts to various trading styles with extensive input settings that control the display and calculation of order blocks. Whether you're a day trader, swing trader, or long-term investor, the indicator can be tailored to meet your specific needs.
Visual Clarity: With customizable color settings and display options, the indicator enhances chart readability, allowing traders to quickly and easily interpret market data.
The Predictive Order Blocks Indicator by CryptoSea is an invaluable addition to a trader's toolkit, offering depth and precision in market trend analysis to navigate complex market conditions effectively.
TrendSphere (Zeiierman)█ Overview
TrendSphere is designed to capture and visualize market trends and volatility effectively. It combines various volatility measures and trend analysis techniques, producing dynamic bands and a central trend line on the price chart. Its essence is to offer a real-time, reliable estimate of the underlying linear trend in the price.
█ How It Works
Real-Time Trend Estimation
At its core, TrendSphere is designed to offer instantaneous and accurate insights into the inherent linear trend of asset prices. By continually updating its estimations, it ensures traders are equipped with the most current data. This allows the construction of support and resistance bands around the estimated trend, providing trading opportunities.
Dynamic Bands and Trend Line
TrendSphere plots a central trend line and dynamic bands around it on the price chart. Influenced by volatility, the distance between these elements offers a clear view of market conditions and the strength or weakness of trends. These bands not only depict potential turning points but also offer traders valuable opportunities to trade within the confines of the overarching trend.
Volatility Measures
Traders can select their preferred volatility measure and adjust settings to best fit their analysis needs. The bands and trend line dynamically respond to these selections, offering a tailored view of market conditions.
ATR (Average True Range): Reflects market volatility by evaluating the range between high and low prices.
Historical Volatility: Computes price variability using the standard deviation of log returns.
Bollinger Band Width: Measures the distance between Bollinger Bands, providing another angle on market volatility.
Eliminating Common Complications
One of the standout features of TrendSphere is its ability to determine linear price trends without falling prey to challenges like backpainting or repainting. In layman's terms, this means traders get a more trustworthy and unaltered view of price movements, leading to enhanced decision-making in line with the genuine trajectory of price trends.
█ How to Use
Trend Analysis
Observe the central trend line; its direction indicates the prevailing trend. When the price is above the trend line, it suggests an upward trend, and when it's below, it indicates a downward trend.
Volatility Analysis
Wider bands imply higher market volatility, suggesting larger price swings, while narrower bands indicate lower volatility. Traders can use the bands to identify potential reversal points and overbought/oversold conditions.
Potential Trading Signals (Using Bollinger bandwidth as volatility measure)
Consider buying when the price is above the trend line with narrowing bands, suggesting a strong upward trend.
Consider selling when the price is below the trend line with narrowing bands, indicating a strong downward trend.
█ Settings
Select Volatility Measure
Choose the desired volatility measure: ATR, Historical Volatility, or Bollinger Band Width.
Volatility Scaling Factor
Adjusts the scale of the volatility measure, influencing the width of the bands.
Volatility Strength
Modifies the influence of volatility on the bands, adjusting their responsiveness to volatility changes.
Length
Defines the number of periods used in calculating the selected volatility measure, impacting the stability and responsiveness of the bands.
Trend Sensitivity
Adjusts the sensitivity of the trend component, affecting how quickly it reacts to price changes.
█ Related scripts with the same calculation philosophy
TrendCylinder
Predictive Trend and Structure
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Auto-Length Adaptive ChannelsIntroduction
The key innovation of the ALAC is the implementation of dynamic length identification, which allows the indicator to adjust to the "market beat" or dominant cycle in real-time.
The Auto-Length Adaptive Channels (ALAC) is a flexible technical analysis tool that combines the benefits of five different approaches to market band and price deviation calculations.
Traders often tend to overthink of what length their indicators should use, and this is the main idea behind this script. It automatically calculates length based on pivot points, averaging the distance that is in between of current market highs and lows.
This approach is very helpful to identify market deviations, because deviations are always calculated and compared to previous market behavior.
How it works
The indicator uses a Detrended Rhythm Oscillator (DRO) to identify the dominant cycle in the market. This length information is then used to calculate different market bands and price deviations. The ALAC combines five different methodologies to compute these bands:
1 - Bollinger Bands
2 - Keltner Channels
3 - Envelope
4 - Average True Range Channels
5 - Donchian Channels
By averaging these calculations, the ALAC produces an overall market band that generalizes the approaches of these five methods into a single, adaptive channel.
How to Use
When the price is at the upper band, this might suggest that the asset is overbought and may be due for a price correction. Conversely, when the price is at the lower band, the asset may be oversold and due for a price increase.
The space between the bands represents the market's volatility. Wider bands indicate higher volatility, while narrower bands suggest lower volatility.
Indicator Settings
The settings of the ALAC allow for customization to suit different trading strategies:
Use Autolength?: This allows the indicator to automatically adjust the length of the dominant cycle.
Usual Length: If "Use Autolength?" is disabled, this setting allows the user to manually specify the length of the cycle.
Moving Average Type: This selects the type of moving average to be used in the calculations. Options include SMA, EMA, ALMA, DEMA, JMA, KAMA, SMMA, TMA, TSF, VMA, VAMA, VWMA, WMA, and ZLEMA.
Channel Multiplier: This adjusts the distance between the bands.
Channel Multiplier Step: This changes the step size of the channel multiplier. Each next market band will be multiplied by a previous one. You can potentially use values below 1, which will plot bands inside the first, main channel.
Use DPO instead of source data?: This setting uses the DPO for calculations instead of the source data. Basically, this is how you can add or eliminate trend from calculation of an average leg-up / leg-down move.
Fast: This adjusts the fast length of the DPO.
Slow: This adjusts the slow length of the DPO.
Zig-zag Period: This adjusts the period of the zig-zag pattern used in the DPO.
(!) For more information about DPO visit official TradingView description here: link
Also, I want to say thanks to @StockMarketCycles for initial idea of Detrended Rhythm Oscillator (DRO) that I use in this script.
The Adaptive Average Channel is a powerful and versatile indicator that combines the strengths of multiple technical analysis methods.
In summary, with the ALAC, you can:
1 - Dynamically adapt to any asset and price action with automatic calculation of dominant cycle lengths.
2 - Identify potential overbought and oversold conditions with the adaptive market bands.
3 - Customize your analysis with various settings, including moving average type and channel multiplier.
4 - Enhance your trading strategy by using the indicator in conjunction with other forms of analysis.
Volume Channel - [With Volume Filter]The indicator calculates two volume-weighted moving averages (VWMA) using different lengths, and filters them based on a moving average of volume. The filtered VWMA values are then plotted on the chart as lines, representing the fast and slow moving averages. In addition, upper and lower bands are calculated based on the slow VWMA and plotted as lines on the chart.
The fast and slow VWMA lines can be used to identify trends in the market. When the fast VWMA is above the slow VWMA, it is an indication of an uptrend, and when the fast VWMA is below the slow VWMA, it is an indication of a downtrend. The position of the VWMA lines relative to the upper and lower bands can also be used to identify potential trade signals.
When the price is near the upper band, it indicates that the market is overbought, and when the price is near the lower band, it indicates that the market is oversold. Traders can use these signals to enter or exit trades.
The indicator also includes a volume filter, which means that the VWMA values are only calculated when the volume is above a certain moving average of volume. This helps to filter out noise in the market and provide more accurate signals.
Explanation for each parameter
vwmaLength1: This is the length of the fast volume-weighted moving average (VWMA) used in the calculation. The default value is 10, and it can be adjusted by the user.
vwmaLength2: This is the length of the slow volume-weighted moving average (VWMA) used in the calculation. The default value is 25, and it can be adjusted by the user.
bandLength: This is the length of the moving average used to calculate the upper and lower bands. The default value is 34, and it is not adjustable by the user.
volumeFilterLength: This is the length of the moving average of volume used as a filter for the VWMA calculation. The default value is 5, and it can be adjusted by the user.
src: This is the input source for the VWMA calculation. The default value is close, which means the indicator is using the closing price of each bar. However, the user can select a different input source by changing this parameter.
filteredVwma1: This is the filtered VWMA calculated based on the volume filter and the fast VWMA length. It is plotted as a line on the chart and can be used to identify short-term trends.
filteredVwma2: This is the filtered VWMA calculated based on the volume filter and the slow VWMA length. It is plotted as a line on the chart and can be used to identify long-term trends.
ma: This is the moving average of the filtered slow VWMA values, which is used to calculate the upper and lower bands. It is plotted as a line on the chart.
offs: This is the offset used to calculate the upper and lower bands. It is based on the standard deviation of the filtered slow VWMA values and is multiplied by 1.6185 * 3. It is plotted as a line on the chart.
up: This is the upper band calculated as the moving average plus the offset. It is plotted as a line on the chart and can be used to identify overbought conditions.
dn: This is the lower band calculated as the moving average minus the offset. It is plotted as a line on the chart and can be used to identify oversold conditions.
Adaptive RSI | Lyro RSThe Adaptive RSI | 𝓛𝔂𝓻𝓸 𝓡𝓢 indicator enhances the traditional Relative Strength Index (RSI) by integrating adaptive smoothing techniques and dynamic bands. This design aims to provide traders with a nuanced view of market momentum, highlighting potential trend shifts and overbought or oversold conditions.
Key Features
Adaptive RSI Calculation: Combines fast and slow Exponential Moving Averages (EMAs) of the RSI to capture momentum shifts effectively.
Dynamic Bands: Utilizes a smoothed standard deviation approach to create upper and lower bands around the adaptive RSI, aiding in identifying extreme market conditions.
Signal Line: An additional EMA of the adaptive RSI serves as a signal line, assisting in confirming trend directions.
Customizable Color Schemes: Offers multiple predefined color palettes, including "Classic," "Mystic," "Accented," and "Royal," with an option for users to define custom colors for bullish and bearish signals.
How It Works
Adaptive RSI Computation: Calculates the difference between fast and slow EMAs of the RSI, producing a responsive oscillator that adapts to market momentum.
Band Formation: Applies a smoothing factor to the standard deviation of the adaptive RSI, generating dynamic upper and lower bands that adjust to market volatility.
Signal Line Generation: Computes an EMA of the adaptive RSI to act as a signal line, providing additional confirmation for potential entries or exits.
Visualization: Plots the adaptive RSI as color-coded columns, with colors indicating bullish or bearish momentum. The dynamic bands are filled to visually represent overbought and oversold zones.
How to Use
Identify Momentum Shifts: Observe crossovers between the adaptive RSI and the signal line to detect potential changes in trend direction.
Spot Overbought/Oversold Conditions: Monitor when the adaptive RSI approaches or breaches the dynamic bands, signaling possible market extremes.
Customize Visuals: Select from predefined color palettes or define custom colors to align the indicator's appearance with personal preferences or chart themes.
Customization Options
RSI and EMA Lengths: Adjust the lengths of the RSI, fast EMA, slow EMA, and signal EMA to fine-tune the indicator's sensitivity.
Band Settings: Modify the band length, multiplier, and smoothing factor to control the responsiveness and width of the dynamic bands.
Color Schemes: Choose from predefined color modes or enable custom color settings to personalize the indicator's appearance.
⚠️ DISCLAIMER ⚠️: This indicator alone is not reliable and should be combined with other indicator(s) for a stronger signal.
BBSS+This Pine Script implements a custom indicator overlaying Bollinger Bands with additional features for trend analysis using Exponential Moving Averages (EMAs). Here's a breakdown of its functionality:
Bollinger Bands:
The script calculates the Bollinger Bands using a 20-period Simple Moving Average (SMA) as the basis and a multiplier of 2 for the standard deviation.
It plots the Upper Band and Lower Band in red.
EMA Calculations:
Three EMAs are calculated for the close price with periods of 5, 10, and 40.
The EMAs are plotted in green (5-period), cyan (10-period), and orange (40-period) to distinguish between them.
Trend Detection:
The script determines bullish or bearish EMA alignments:
Bullish Order: EMA 5 > EMA 10 > EMA 40.
Bearish Order: EMA 5 < EMA 10 < EMA 40.
Entry Signals:
Long Entry: Triggered when:
The close price crosses above the Upper Bollinger Band.
The Upper Band is above its 5-period SMA (indicating momentum).
The EMAs are in a bullish order.
Short Entry: Triggered when:
The close price crosses below the Lower Bollinger Band.
The Lower Band is below its 5-period SMA.
The EMAs are in a bearish order.
Trend State Tracking:
A variable tracks whether the market is in a Long or Short trend based on conditions:
A Long trend continues unless conditions for a Short Entry are met or the Upper Band dips below its average.
A Short trend continues unless conditions for a Long Entry are met or the Lower Band rises above its average.
Visual Aids:
Signal Shapes:
Triangle-up shapes indicate Long Entry points below the bar.
Triangle-down shapes indicate Short Entry points above the bar.
Bar Colors:
Green bars indicate a Long trend.
Red bars indicate a Short trend.
This script combines Bollinger Bands with EMA crossovers to generate entry signals and visualize market trends, making it a versatile tool for identifying momentum and trend reversals.
Bollinger Breakout Strategy with Direction Control [4H crypto]Bollinger Breakout Strategy with Direction Control - User Guide
This strategy leverages Bollinger Bands, RSI, and directional filters to identify potential breakout trading opportunities. It is designed for traders looking to capitalize on significant price movements while maintaining control over trade direction (long, short, or both). Here’s how to use this strategy effectively:
How the Strategy Works
Indicators Used:
Bollinger Bands:
A volatility-based indicator with an upper and lower band around a simple moving average (SMA). The bands expand or contract based on market volatility.
RSI (Relative Strength Index):
Measures momentum to determine overbought or oversold conditions. In this strategy, RSI is used to confirm breakout strength.
Trade Direction Control:
You can select whether to trade:
Long only: Buy positions.
Short only: Sell positions.
Both: Trade in both directions depending on conditions.
Breakout Conditions:
Long Trade:
The price closes above the upper Bollinger Band.
RSI is above the midline (50), confirming upward momentum.
The "Trade Direction" setting allows either "Long" or "Both."
Short Trade:
The price closes below the lower Bollinger Band.
RSI is below the midline (50), confirming downward momentum.
The "Trade Direction" setting allows either "Short" or "Both."
Risk Management:
Stop-Loss:
Long trades: Set at 2% below the entry price.
Short trades: Set at 2% above the entry price.
Take-Profit:
Calculated using a Risk/Reward Ratio (default is 2:1).
Adjust this in the strategy settings.
Inputs and Customization
Key Parameters:
Bollinger Bands Length: Default is 20. Adjust based on the desired sensitivity.
Multiplier: Default is 2.0. Higher values widen the bands; lower values narrow them.
RSI Length: Default is 14, which is standard for RSI.
Risk/Reward Ratio: Default is 2.0. Increase for more aggressive profit targets, decrease for conservative exits.
Trade Direction:
Options: "Long," "Short," or "Both."
Example: Set to "Long" in a bullish market to focus only on buy trades.
How to Use This Strategy
Adding the Strategy:
Paste the script into TradingView’s Pine Editor and add it to your chart.
Setting Parameters:
Adjust the Bollinger Band settings, RSI, and Risk/Reward Ratio to fit the asset and timeframe you're trading.
Analyzing Signals:
Green line (Upper Band): Signals breakout potential for long trades.
Red line (Lower Band): Signals breakout potential for short trades.
Blue line (Basis): Central Bollinger Band (SMA), helpful for understanding price trends.
Testing the Strategy:
Use the Strategy Tester in TradingView to backtest performance on your chosen asset and timeframe.
Optimizing for Assets:
Forex pairs, cryptocurrencies (like BTC), or stocks with high volatility are ideal for this strategy.
Works best on higher timeframes like 4H or Daily.
Best Practices
Combine with Volume: Confirm breakouts with increased volume for higher reliability.
Avoid Sideways Markets: Use additional trend filters (like ADX) to avoid trades in low-volatility conditions.
Optimize Parameters: Regularly adjust the Bollinger Bands multiplier and RSI settings to match the asset's behavior.
By utilizing this strategy, you can effectively trade breakouts while maintaining flexibility in trade direction. Adjust the parameters to match your trading style and market conditions for optimal results!
Wick Trend Analysis with Supertrend and RSI -AYNETScientific Explanation
1. Wick Trend Analysis
Upper and Lower Wicks:
Calculated based on the difference between the high or low price and the candlestick body (open and close).
The trend of these wick lengths is derived using the Simple Moving Average (SMA) over the defined trend_length period.
Trend Direction:
Positive change (ta.change > 0) indicates an increasing trend.
Negative change (ta.change < 0) indicates a decreasing trend.
2. Supertrend Indicator
ATR Bands:
The Supertrend uses the Average True Range (ATR) to calculate dynamic upper and lower bands:
upper_band
=
hl2
+
(
supertrend_atr_multiplier
×
ATR
)
upper_band=hl2+(supertrend_atr_multiplier×ATR)
lower_band
=
hl2
−
(
supertrend_atr_multiplier
×
ATR
)
lower_band=hl2−(supertrend_atr_multiplier×ATR)
Trend Detection:
If the price is above the upper band, the Supertrend moves to the lower band.
If the price is below the lower band, the Supertrend moves to the upper band.
The Supertrend helps identify the prevailing market trend.
3. RSI (Relative Strength Index)
The RSI measures the momentum of price changes and ranges between 0 and 100:
Overbought Zone (Above 70): Indicates that the price may be overextended and due for a pullback.
Oversold Zone (Below 30): Indicates that the price may be undervalued and due for a reversal.
Visualization Features
Wick Trend Lines:
Upper wick trend (green) and lower wick trend (red) show the relative strength of price rejection on both sides.
Wick Trend Area:
The area between the upper and lower wick trends is filled dynamically:
Green: Upper wick trend is stronger.
Red: Lower wick trend is stronger.
Supertrend Line:
Displays the Supertrend as a blue line to highlight the market's directional bias.
RSI:
Plots the RSI line, with horizontal dotted lines marking the overbought (70) and oversold (30) levels.
Applications
Trend Confirmation:
Use the Supertrend and wick trends together to confirm the market's directional bias.
For example, a rising lower wick trend with a bullish Supertrend suggests strong bullish sentiment.
Momentum Analysis:
Combine the RSI with wick trends to assess the strength of price movements.
For example, if the RSI is oversold and the lower wick trend is increasing, it may signal a potential reversal.
Signal Generation:
Generate entry signals when all three indicators align:
Bullish Signal:
Lower wick trend increasing.
Supertrend bullish.
RSI rising from oversold.
Bearish Signal:
Upper wick trend increasing.
Supertrend bearish.
RSI falling from overbought.
Future Improvements
Alert System:
Add alerts for alignment of Supertrend, RSI, and wick trends:
pinescript
Kodu kopyala
alertcondition(upper_trend_direction == 1 and supertrend < close and rsi > 50, title="Bullish Signal", message="Bullish alignment detected.")
alertcondition(lower_trend_direction == 1 and supertrend > close and rsi < 50, title="Bearish Signal", message="Bearish alignment detected.")
Custom Thresholds:
Add thresholds for wick lengths and RSI levels to filter weak signals.
Multiple Timeframes:
Incorporate multi-timeframe analysis for more robust signal generation.
Conclusion
This script combines wick trends, Supertrend, and RSI to create a comprehensive framework for analyzing market sentiment and detecting potential trading opportunities. By visualizing trends, market bias, and momentum, traders can make more informed decisions and reduce reliance on single-indicator strategies.
MACD+RSI+BBDESCRIPTION
The MACD + RSI + Bollinger Bands Indicator is a comprehensive technical analysis tool designed for traders and investors to identify potential market trends and reversals. This script combines three indicators: the Moving Average Convergence Divergence (MACD), the Relative Strength Index (RSI), and Bollinger Bands. Each of these indicators provides unique insights into market behavior.
FEATURES
MACD (Moving Average Convergence Divergence)
The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price.
The script calculates the MACD line, the signal line, and the histogram, which visually represents the difference between the MACD line and the signal line.
RSI (Relative Strength Index)
The RSI is a momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and is typically used to identify overbought or oversold conditions.
The script allows users to set custom upper and lower thresholds for the RSI, with default values of 70 and 30, respectively.
Bollinger Bands
Bollinger Bands consist of a middle band (EMA) and two outer bands (standard deviations away from the EMA). They help traders identify volatility and potential price reversals.
The script allows users to customize the length of the Bollinger Bands and the multiplier for the standard deviation.
Color-Coding Logic
The histogram color changes based on the following conditions:
Black: If the RSI is above the upper threshold and the closing price is above the upper Bollinger Band, or if the RSI is below the lower threshold and the closing price is below the lower Bollinger Band.
Green (#4caf50): If the RSI is above the upper threshold but the closing price is not above the upper Bollinger Band.
Light Green (#a5d6a7): If the histogram is positive and the RSI is not above the upper threshold.
Red (#f23645): If the RSI is below the lower threshold but the closing price is not below the lower Bollinger Band.
Light Red (#faa1a4): If the histogram is negative and the RSI is not below the lower threshold.
Inputs
Bollinger Bands Settings
Length: The number of periods for the moving average.
Basis MA Type: The type of moving average (SMA, EMA, SMMA, WMA, VWMA).
Source: The price source for the Bollinger Bands calculation.
StdDev: The multiplier for the standard deviation.
RSI Settings
RSI Length: The number of periods for the RSI calculation.
RSI Upper: The upper threshold for the RSI.
RSI Lower: The lower threshold for the RSI.
Source: The price source for the RSI calculation.
MACD Settings
Fast Length: The length for the fast moving average.
Slow Length: The length for the slow moving average.
Signal Smoothing: The length for the signal line smoothing.
Oscillator MA Type: The type of moving average for the MACD calculation.
Signal Line MA Type: The type of moving average for the signal line.
Usage
This indicator is suitable for various trading strategies, including day trading, swing trading, and long-term investing.
Traders can use the MACD histogram to identify potential buy and sell signals, while the RSI can help confirm overbought or oversold conditions.
The Bollinger Bands provide context for price volatility and potential breakout or reversal points.
Example:
From the example, it can clearly see that the Selling Climax and Buying Climax, marked as orange circle when a black histogram occurs.
Conclusion
The MACD + RSI + Bollinger Bands Indicator is a versatile tool that combines multiple technical analysis methods to provide traders with a comprehensive view of market conditions. By utilizing this script, traders can enhance their analysis and improve their decision-making process.
Bitcoin Logarithmic Growth Curve 2024The Bitcoin logarithmic growth curve is a concept used to analyze Bitcoin's price movements over time. The idea is based on the observation that Bitcoin's price tends to grow exponentially, particularly during bull markets. It attempts to give a long-term perspective on the Bitcoin price movements.
The curve includes an upper and lower band. These bands often represent zones where Bitcoin's price is overextended (upper band) or undervalued (lower band) relative to its historical growth trajectory. When the price touches or exceeds the upper band, it may indicate a speculative bubble, while prices near the lower band may suggest a buying opportunity.
Unlike most Bitcoin growth curve indicators, this one includes a logarithmic growth curve optimized using the latest 2024 price data, making it, in our view, superior to previous models. Additionally, it features statistical confidence intervals derived from linear regression, compatible across all timeframes, and extrapolates the data far into the future. Finally, this model allows users the flexibility to manually adjust the function parameters to suit their preferences.
The Bitcoin logarithmic growth curve has the following function:
y = 10^(a * log10(x) - b)
In the context of this formula, the y value represents the Bitcoin price, while the x value corresponds to the time, specifically indicated by the weekly bar number on the chart.
How is it made (You can skip this section if you’re not a fan of math):
To optimize the fit of this function and determine the optimal values of a and b, the previous weekly cycle peak values were analyzed. The corresponding x and y values were recorded as follows:
113, 18.55
240, 1004.42
451, 19128.27
655, 65502.47
The same process was applied to the bear market low values:
103, 2.48
267, 211.03
471, 3192.87
676, 16255.15
Next, these values were converted to their linear form by applying the base-10 logarithm. This transformation allows the function to be expressed in a linear state: y = a * x − b. This step is essential for enabling linear regression on these values.
For the cycle peak (x,y) values:
2.053, 1.268
2.380, 3.002
2.654, 4.282
2.816, 4.816
And for the bear market low (x,y) values:
2.013, 0.394
2.427, 2.324
2.673, 3.504
2.830, 4.211
Next, linear regression was performed on both these datasets. (Numerous tools are available online for linear regression calculations, making manual computations unnecessary).
Linear regression is a method used to find a straight line that best represents the relationship between two variables. It looks at how changes in one variable affect another and tries to predict values based on that relationship.
The goal is to minimize the differences between the actual data points and the points predicted by the line. Essentially, it aims to optimize for the highest R-Square value.
Below are the results:
It is important to note that both the slope (a-value) and the y-intercept (b-value) have associated standard errors. These standard errors can be used to calculate confidence intervals by multiplying them by the t-values (two degrees of freedom) from the linear regression.
These t-values can be found in a t-distribution table. For the top cycle confidence intervals, we used t10% (0.133), t25% (0.323), and t33% (0.414). For the bottom cycle confidence intervals, the t-values used were t10% (0.133), t25% (0.323), t33% (0.414), t50% (0.765), and t67% (1.063).
The final bull cycle function is:
y = 10^(4.058 ± 0.133 * log10(x) – 6.44 ± 0.324)
The final bear cycle function is:
y = 10^(4.684 ± 0.025 * log10(x) – -9.034 ± 0.063)
The main Criticisms of growth curve models:
The Bitcoin logarithmic growth curve model faces several general criticisms that we’d like to highlight briefly. The most significant, in our view, is its heavy reliance on past price data, which may not accurately forecast future trends. For instance, previous growth curve models from 2020 on TradingView were overly optimistic in predicting the last cycle’s peak.
This is why we aimed to present our process for deriving the final functions in a transparent, step-by-step scientific manner, including statistical confidence intervals. It's important to note that the bull cycle function is less reliable than the bear cycle function, as the top band is significantly wider than the bottom band.
Even so, we still believe that the Bitcoin logarithmic growth curve presented in this script is overly optimistic since it goes parly against the concept of diminishing returns which we discussed in this post:
This is why we also propose alternative parameter settings that align more closely with the theory of diminishing returns.
Our recommendations:
Drawing on the concept of diminishing returns, we propose alternative settings for this model that we believe provide a more realistic forecast aligned with this theory. The adjusted parameters apply only to the top band: a-value: 3.637 ± 0.2343 and b-parameter: -5.369 ± 0.6264. However, please note that these values are highly subjective, and you should be aware of the model's limitations.
Conservative bull cycle model:
y = 10^(3.637 ± 0.2343 * log10(x) - 5.369 ± 0.6264)
Abnormal value check1. indicator settings
BB Length: Sets the period used for the Bollinger Band calculation. The default is 20 periods.
BB Multiplier: Sets the multiplier to be used in the Bollinger Band calculation. The default is 2.5 multiplier.
Equilibrium volume reset: Selects whether or not the volume should be reset if it is out of equilibrium. The default setting is reset. 2.
2. bollinger band calculation
This indicator calculates Bollinger Bands (upper and lower bands and a reference line) from price and volume data.
Bollinger Bands are indicators used to measure price and volume volatility and are identified as anomalies when prices break through the bands.
3. display of abnormal prices
Abnormal Buying Price (ABP): The background color changes when the price significantly exceeds the upper limit of the Bollinger Band. The color is green.
Abnormal Selling Price (ASP): The background color changes when the price is significantly below the lower limit of the Bollinger Band. The color is red.
Abnormal High Volume (AHV): The background color changes when the volume is significantly above the upper Bollinger Band. The color is white.
Abnormal Low Volume (ALV): The background color changes when the volume is significantly below the lower limit of the Bollinger Band. The color is yellow. 4.
4. display of signals
Abnormal Price Signal: A triangle signal is displayed when the price rises or falls compared to the previous data. The color is orange for an increase and purple for a decrease.
Volume Abnormal Signal: A triangle signal is displayed when volume is up or down compared to the previous data. Rises are colored orange and falls are colored purple. 5.
5. price and volume history display
RSAB_P: Displays price anomaly history. Rising prices are displayed in green, and falling prices in red.
RSAB_V: Displays the volume anomaly history. Green indicates an increase and red indicates a decrease. 6.
6. display of equilibrium
PPE: Displays a line indicating the state of volume balance. A positive volume balance is displayed in orange, and a negative volume balance is displayed in purple.
Summary of usage
Add indicator to chart: Add this Pine Script™ code as an indicator in TradingView.
Set parameters: Based on the settings above, adjust the values to suit your trading strategy and analysis.
See signals and color changes on the chart: Visually identify price and volume anomalies to help you make trading decisions.
This indicator uses Bollinger Bands to identify abnormal price and volume movements to help you improve your trading timing and strategies.
BBTrend w SuperTrend decision - Strategy [presentTrading]This strategy aims to improve upon the performance of Traidngview's newly published "BB Trend" indicator by incorporating the SuperTrend for better trade execution and risk management. Enjoy :)
█Introduction and How it is Different
The "BBTrend w SuperTrend decision - Strategy " is a trading strategy designed to identify market trends using Bollinger Bands and SuperTrend indicators. What sets this strategy apart is its use of two Bollinger Bands with different lengths to capture both short-term and long-term market trends, providing a more comprehensive view of market dynamics. Additionally, the strategy includes customizable take profit (TP) and stop loss (SL) settings, allowing traders to tailor their risk management according to their preferences.
BTCUSD 4h Long Performance
█ Strategy, How It Works: Detailed Explanation
The BBTrend strategy employs two key indicators: Bollinger Bands and SuperTrend.
🔶 Bollinger Bands Calculation:
- Short Bollinger Bands**: Calculated using a shorter period (default 20).
- Long Bollinger Bands**: Calculated using a longer period (default 50).
- Bollinger Bands use the standard deviation of price data to create upper and lower bands around a moving average.
Upper Band = Middle Band + (k * Standard Deviation)
Lower Band = Middle Band - (k * Standard Deviation)
🔶 BBTrend Indicator:
- The BBTrend indicator is derived from the absolute differences between the short and long Bollinger Bands' lower and upper values.
BBTrend = (|Short Lower - Long Lower| - |Short Upper - Long Upper|) / Short Middle * 100
🔶 SuperTrend Indicator:
- The SuperTrend indicator is calculated using the average true range (ATR) and a multiplier. It helps identify the market trend direction by plotting levels above and below the price, which act as dynamic support and resistance levels. * @EliCobra makes the SuperTrend Toolkit. He is GOAT.
SuperTrend Upper = HL2 + (Factor * ATR)
SuperTrend Lower = HL2 - (Factor * ATR)
The strategy determines market trends by checking if the close price is above or below the SuperTrend values:
- Uptrend: Close price is above the SuperTrend lower band.
- Downtrend: Close price is below the SuperTrend upper band.
Short: 10 Long: 20 std 2
Short: 20 Long: 40 std 2
Short: 20 Long: 40 std 4
█ Trade Direction
The strategy allows traders to choose their trading direction:
- Long: Enter long positions only.
- Short: Enter short positions only.
- Both: Enter both long and short positions based on market conditions.
█ Usage
To use the "BBTrend - Strategy " effectively:
1. Configure Inputs: Adjust the Bollinger Bands lengths, standard deviation multiplier, and SuperTrend settings.
2. Set TPSL Conditions: Choose the take profit and stop loss percentages to manage risk.
3. Choose Trade Direction: Decide whether to trade long, short, or both directions.
4. Apply Strategy: Apply the strategy to your chart and monitor the signals for potential trades.
█ Default Settings
The default settings are designed to provide a balance between sensitivity and stability:
- Short BB Length (20): Captures short-term market trends.
- Long BB Length (50): Captures long-term market trends.
- StdDev (2.0): Determines the width of the Bollinger Bands.
- SuperTrend Length (10): Period for calculating the ATR.
- SuperTrend Factor (12): Multiplier for the ATR to adjust the SuperTrend sensitivity.
- Take Profit (30%): Sets the level at which profits are taken.
- Stop Loss (20%): Sets the level at which losses are cut to manage risk.
Effect on Performance
- Short BB Length: A shorter length makes the strategy more responsive to recent price changes but can generate more false signals.
- Long BB Length: A longer length provides smoother trend signals but may be slower to react to price changes.
- StdDev: Higher values create wider bands, reducing the frequency of signals but increasing their reliability.
- SuperTrend Length and Factor: Shorter lengths and higher factors make the SuperTrend more sensitive, providing quicker signals but potentially more noise.
- Take Profit and Stop Loss: Adjusting these levels affects the risk-reward ratio. Higher take profit percentages can increase gains but may result in fewer closed trades, while higher stop loss percentages can decrease the likelihood of being stopped out but increase potential losses.
Extreme Entry with Mean Reversion and Trend FilterThis non-repainting indicator is an improved version of my previous work, a more versatile tool designed to provide traders with dynamic and adaptive entry signals while incorporating a mean reversion and trend filtering mechanism. By combining RSI overbought/oversold, regular divergence and confirmatory momentum oscillator such as CCI or MOM, this indicator generates more precise and timely signals for entering trades.
The indicator offers a comprehensive set of entry conditions for both Buy and Sell entries:
• For Buy entries, it checks for oversold conditions based on RSI levels, and detects bullish divergence patterns while oversold and it identifies upward crossovers in the selected entry signal source (CCI or Momentum).
• Similarly, for Sell entries, it identifies downward crossovers of the CCI or Mom, after the recent overbought conditions, and bearish divergence patterns inside the overbought RSI.
To refine the entry signals even further, the indicator utilizes a mean reversion filter. Traders can choose to display signals that occur inside or outside the upper and lower mean reversion bands:
• Range Entries are indicating potential buying opportunities near the lower band and selling opportunities near the upper band. This is based on the concept of mean reversion, which suggests that prices tend to return to the average when they reach the upper or lower bands. By focusing on these signals, traders can take advantage of price movements that have a higher probability of reversing towards the mean.
• Extreme Entries, on the other hand, represent signals that occur outside of the bands, signaling potential pullbacks during strong trends. By entering positions only at extreme highs or lows, traders can avoid getting caught in the middle of the trend. This approach helps traders capitalize more favorable trading opportunities which have a high reward-risk ratio.
Trend Filter acts as a directional bias for the entry signals. When enabled, long and short entry conditions are filtered based on the relationship between the closing price and the EMA.
Traders have the flexibility to customize, tweak the indicator filter and values in the settings according to their preferences strategies and traded assets, tailoring the signals to their specific needs. The script sets alert conditions to trigger alerts for buy, sell, or both entry signals. This indicator can be used in conjunction with price action or other technical analysis tools for confirmation and better trading decisions.
I created this indicator for my own use, and I share this for informational purposes only. It does not constitute financial advice so use at your own risk and consider your financial situation before making any trading decisions. The indicator's accuracy is not guaranteed, and past performance is not indicative of future results.
I appreciate your feedback on this indicator. As I am new to script development, I am open to comments and suggestions to improve it. If you encounter any issues while using this indicator, please let me know in the comments section. If you find it helpful, I kindly ask for your support in boosting it. Thank you for your cooperation.
Stochastic Momentum Channel with Volume Filter [IkkeOmar]A stochastic version of my momentum channel volume filter
The "Stochastic Momentum" indicator combines the concepts of Stochastic and Bollinger Bands to provide insights into price momentum and potential trend reversals. It can be used to identify overbought and oversold conditions, as well as potential bullish and bearish signals.
The indicator calculates a Stochastic RSI using the RSI (Relative Strength Index) of a given price source. It applies smoothing to the Stochastic RSI values using moving averages to generate two lines: the %K line and the %D line. The %K line represents the current momentum, while the %D line represents a filtered version of the momentum.
Additionally, the indicator plots Bollinger Bands around the moving average of the Stochastic RSI. The upper and lower bands represent levels where the price is considered relatively high or low compared to its recent volatility. The distance between the bands reflects the current market volatility.
Here's how the indicator can be interpreted:
Stochastic Momentum (%K and %D lines):
When the %K line crosses above the %D line, it suggests a potential upward move or bullish momentum.
When the %K line crosses below the %D line, it indicates a potential downward move or bearish momentum.
The color of the plot changes based on the relationship between the %K and %D lines. Green indicates %K > %D, while red indicates %K < %D.
Bollinger Bands (Upper and Lower Bands):
When the price crosses above the upper band, it suggests an overbought condition, indicating a potential reversal or pullback.
When the price crosses below the lower band, it suggests an oversold condition, indicating a potential reversal or bounce.
To identify potential upward moves, consider the following conditions:
If the price is not in a contraction phase (the bands are not narrowing), and the price crosses above the lower band, it may signal a potential upward move or bounce.
If the %K line crosses above the %D line while the %K line is below the upper band, it may indicate a potential upward move.
To identify potential downward moves, consider the following conditions:
If the price is not in a contraction phase (the bands are not narrowing), and the price crosses below the upper band, it may signal a potential downward move or pullback.
If the %K line crosses below the %D line while the %K line is above the lower band, it may indicate a potential downward move.
Code explanation
Input Variables:
The input function is used to create customizable input variables that can be adjusted by the user.
smoothK and smoothD are inputs for the smoothing periods of the %K and %D lines, respectively.
lengthRSI represents the length of the RSI calculation.
lengthStoch is the length parameter for the stochastic calculation.
volumeFilterLength determines the length of the volume filter used to filter the RSI.
Source Definition:
The src variable is an input that defines the price source used for the calculations.
By default, the close price is used, but the user can choose a different price source.
RSI Calculation:
The rsi1 variable calculates the RSI using the ta.rsi function.
The RSI is a popular oscillator that measures the strength and speed of price movements.
It is calculated based on the average gain and average loss over a specified period.
In this case, the RSI is calculated using the src price source and the lengthRSI parameter.
Volume Filter:
The code calculates a volume filter to filter the RSI values based on the average volume.
The volumeAvg variable calculates the simple moving average of the volume over a specified period (volumeFilterLength).
The filteredRsi variable stores the RSI values that meet the condition of having a volume greater than or equal to the average volume (volume >= volumeAvg).
Stochastic Calculation:
The k variable calculates the %K line of the Stochastic RSI using the ta.stoch function.
The ta.stoch function takes the filtered RSI values (filteredRsi) as inputs and calculates the %K line based on the length parameter (lengthStoch).
The smoothK parameter is used to smooth the %K line by applying a moving average.
The d variable represents the %D line, which is a smoothed version of the %K line obtained by applying another moving average with a period defined by smoothD.
Momentum Calculation:
The kd variable calculates the average of the %K and %D lines, representing the momentum of the Stochastic RSI.
Bollinger Bands Calculation:
The ma variable calculates the moving average of the momentum values (kd) using the ta.sma function with a period defined by bandLength.
The offs variable calculates the offset by multiplying the standard deviation of the momentum values with a factor of 1.6185.
The up and dn variables represent the upper and lower bands, respectively, by adding and subtracting the offset from the moving average.
The Bollinger Bands provide a measure of volatility and can indicate potential overbought and oversold conditions.
Color Assignments:
The colors for the plot and Bollinger Bands are assigned based on certain conditions.
If the %K line is greater than the %D line, the plotCol variable is set to green. Otherwise, it is set to red.
The upCol and dnCol variables are set to different colors based on whether the fast moving average (fastMA) is above or below the upper and lower bands, respectively.
Plotting:
The Stochastic Momentum (%K) is plotted using the plot function with the assigned color (plotCol).
The upper and lower Bollinger Bands are plotted using the plot function with the respective colors (upCol and dnCol).
The fast moving average (fastMA) is plotted in black color to distinguish it from the bands.
The hline function is used to plot horizontal lines representing the upper and lower bands of the Stochastic Momentum.
The code combines the Stochastic RSI, Bollinger Bands, and color logic to provide visual representations of momentum and potential trend reversals. It allows traders to observe the interaction between the Stochastic Momentum lines, the Bollinger Bands, and price movements, enabling them to make informed trading decisions.
ORB + Session VWAP Pro (London & NY) — fixedORB + Session VWAP Pro (London & NY) — Listing copy (EN)
What it is
A clean, non-repainting intraday tool that fuses the classic Opening Range Breakout (ORB) with a session-anchored VWAP filter for London and New York. It highlights only the higher-quality breakouts (above/below session VWAP), adds an optional retest confirmation, and scores each signal with an intuitive Confidence metric (0–100).
Why it works
• ORB provides the day’s first actionable structure (range high/low).
• Session VWAP filters “cheap” breaks and favors flows aligned with session value.
• Optional retest reduces first-tick whipsaws.
• Confidence blends breakout depth (vs ATR), VWAP slope and band distance.
Key visuals
• LDN/NY OR High/Low (line break style) + optional OR boxes.
• Active Session VWAP (resets per signal window; falls back to daily VWAP outside).
• Optional VWAP bands (stdev or %).
• Session shading (London/NY windows).
• Signal markers (LDN BUY/SELL, NY BUY/SELL) fired with cooldown.
Signals
• London Long / Short: Break of LDN OR High/Low ± ATR buffer, aligned with VWAP side.
• NY Long / Short: Same logic during NY window.
• Retest (optional): Requires a tag back to the OR level ± tolerance before confirmation.
• Confidence: 0–100; gate via Min Confidence (default 55).
Inputs that matter
• Open Range Length (min): Default 15.
• London/NY times & timezones.
• ATR buffer & retest tolerance.
• Bands mode: Stdev (with lookback) or % (e.g., 1%).
• Signal cooldown: Avoids clutter on fast moves.
Non-repaint policy
• OR lines build within fixed time windows using the current bar’s timestamp.
• VWAP is cumulative within the session window; no lookahead.
• All ta.crossover/ta.crossunder are precomputed every bar (no conditional execution).
• Signals are based on live bar values, not future bars.
⸻
Quick start (examples)
1) EURUSD, London momentum
• Chart: 5m or 15m.
• OR: 15 min starting 08:00 Europe/London.
• Signals: Use defaults; keep ATR buffer = 0.2 and Retest = ON, Min Confidence ≥ 55.
• Play:
• BUY when price breaks LDN OR High + buffer and stays above VWAP; retest confirms.
• Trail behind VWAP or band #1; partials into band #2.
2) NAS100, New York breakout & run
• Chart: 5m.
• NY window: 09:30 America/New_York, OR = 15 min.
• Retest OFF on high momentum days; Min Confidence ≥ 60.
• Use band mode Stdev, bandLen=50, show ±1/±2.
• Momentum continuation: add on pullbacks that hold above VWAP after the breakout.
3) XAUUSD, London fake & VWAP fade
• Chart: 5m.
• Keep Retest ON; accept only shorts that break OR Low but retest fails back under VWAP.
• Confidence gate ≥ 50 to allow more mean-reversion setups.
⸻
Pro tips
• Adjust ATR buffer to the instrument: FX 0.15–0.25, indices 0.20–0.35, metals 0.20–0.30.
• Retest ON for choppy conditions; OFF for news momentum.
• Use VWAP bands: take partials at ±1; stretch targets at ±2/±3.
• Session timezones are explicit (London/New York). Ensure they match your instrument’s behavior.
• Pair with a higher-TF bias (e.g., 1H/4H trend) for directional filtering.
⸻
Alerts (ready to use)
• ORB+SVWAP — LDN Long, LDN Short, NY Long, NY Short
(Respect your cooldown; alerts fire only after confirmation and confidence gate.)
⸻
Known limits & notes
• Designed for intraday. On 1D+ charts, session windows compress.
• If your broker session differs from London/NY clocks on a holiday, adjust input times.
• Session-anchored VWAP uses the script’s signal window, not exchange sessions, by design.
S/R Clouds Overview
The S/R Clouds Indicator is a sophisticated TradingView tool designed to visualize support and resistance levels through dynamic cloud formations. Built on the principles of Keltner Channels, it employs a central moving average enveloped by volatility-based bands to highlight potential price reversal zones. This indicator enhances chart analysis with customizable aesthetics and practical alerts, making it suitable for traders across various strategies and timeframes.
Key Features
Dynamic Bands: Calculates upper and lower bands using a configurable moving average (SMA or EMA) offset by multiples of the average true range (derived from high-low ranges), capturing volatility deviations for precise S/R identification.
Cloud Visualization: Renders semi-transparent clouds between primary and extended bands, providing a clear, layered view of support (lower) and resistance (upper) areas.
Trend Detection: Incorporates a trend state logic based on price position relative to bands and moving average direction, aiding in bullish/bearish market assessments.
Customization Options:
Select from multiple color themes (e.g., Neon, Grayscale) or use custom colors for bands.
Enable glow effects for enhanced visual depth and adjust opacity for chart clarity.
Volatility Insights: Monitors band width to detect squeezes (low volatility) and expansions (high volatility), signaling potential breakouts.
Alerts System: Triggers notifications for price crossings of bands, trend changes, and other key events to support timely decision-making.
How It Works
At its core, the indicator centers on a user-defined period moving average. Volatility is measured via an exponential moving average of the high-low range, multiplied by adjustable factors to form the bands. This setup creates adaptive clouds that expand/contract with market volatility, offering a more responsive alternative to static S/R lines. The result is a clean, professional overlay that integrates seamlessly with other technical tools.
This high-quality indicator prioritizes usability and visual appeal, ensuring traders can focus on analysis without distraction.
GCM Volatility-Adaptive Trend ChannelScript Description
Name: GCM Volatility-Adaptive Trend Channel (GCM VATC)
Overview
The GCM Volatility-Adaptive Trend Channel (VATC) is a comprehensive trading tool that merges the low-lag, smooth-trending capabilities of the Jurik Moving Average (JMA) with the classic volatility analysis of Bollinger Bands (BB).
By displaying both trend and volatility in a single, intuitive interface, this indicator aims to help traders see when a trend is stable versus when it's becoming volatile and might be poised for a change.
Core Components:
JMA Trend System: At its core are three dynamically colored JMA lines (Baseline, Fast, and Slow) that provide a clear view of trend direction. The lines change color based on their slope, offering immediate visual feedback on momentum. A colored ribbon between the Baseline and Fast JMA visualizes shorter-term momentum shifts.
Standard Bollinger Bands: Layered on top are standard Bollinger Bands. Calculated from the price, these bands serve as a classic measure of market volatility. They help identify periods where the market is expanding (high volatility) or contracting (low volatility).
How to Use It
By combining these two powerful concepts, this indicator provides a unified view of both trend and volatility. It can help traders to:
Identify the primary trend direction using the smooth JMA lines.
Gauge the strength and stability of that trend.
See when the market is becoming volatile (bands widening) or consolidating (bands contracting), which can often precede a significant price move or a change in trend.
A Note on Originality & House Rules Compliance
This indicator does not introduce a new mathematical formula. Instead, its strength lies in the thoughtful combination of two well-respected, publicly available concepts: the Jurik Moving Average and Bollinger Bands. The JMA implementation is a standard public version. The goal was to create a practical, all-in-one tool for trend and volatility analysis.
This script is published as fully open-source in compliance with TradingView's House Rules. It utilizes standard, publicly available algorithms and does not contain any protected or hidden code.
Settings
All lengths, sources, and colors for the JMA lines and Bollinger Bands are fully customizable in the settings menu, allowing you to tailor the indicator to your specific trading style and asset.
I hope with this indicator Traders even Beginner can can control their emotions which increase the probabilities of the winning rates and cutting the losing strength
Purposely I Didn't plant the High low or Buy Sell signals in the chart. Because everything is in the chart where volatility Signal with the Bollinger Band and Buy Sell Signal in the JMA Dynamic colors. and that's enough to decide when to take trade and when not to.
Thank You and Happy Trading
Zone Shift [ChartPrime]⯁ OVERVIEW
Zone Shift is a dynamic trend detection tool that uses EMA/HMA-based bands to determine trend shifts and plot key reaction levels. It highlights trend direction through colored candles and marks important retests with visual cues to help traders stay aligned with momentum.
⯁ KEY FEATURES
Dynamic EMA-HMA Band:
Creates a three-line channel using the average of an EMA and HMA for the midline, and expands it using average candle range to form upper and lower bounds. This band visually adapts to market volatility.
float ema = ta.ema(close, length)
float hma = ta.hma(close, length-40)
float dist = ta.sma(high-low, 200)
float mid = math.avg(ema, hma)
float top = mid + dist
float bot = mid - dist
Trend Detection (Band Cross Logic):
Detects an uptrend when the Low crosses above the top band.
Detects a downtrend when the High crosses below the bottom band.
Bars change color to lime for uptrends and blue for downtrends.
Trend Initiation Level:
At the start of a new trend, the indicator locks in the extreme point (low for uptrend, high for downtrend) and plots a dashed horizontal level, serving as a potential retest zone.
Trend Retest Signal:
If price crosses back over the Trend Initiation level in the direction of the trend, a diamond label (⯁) is plotted at the retest point — confirming that price is revisiting a key shift level.
Visual Band Layout:
Midline: Dashed line shows the average of EMA and HMA.
Top/Bottom: Solid lines showing dynamic thresholds above/below the midline.
These help visualize compression, expansion, and possible breakout zones.
Color-Based Candle Plotting:
Candles are recolored in real time according to the current trend, allowing instant visual alignment with the market’s directional bias.
Noise-Filtered Retests:
To avoid repetitive signals, retests are only marked if they occur more than 5 bars after the previous one — filtering out minor fluctuations.
⯁ USAGE
Use colored candles to align trades with the dominant trend.
Treat dashed trendStart levels as important support/resistance zones.
Watch for ⯁ diamond labels as confirmation of retests for continuation or entry.
Use band boundaries to assess trend strength and volatility expansion.
Combine with your existing setups to validate momentum and zone shifts.
⯁ CONCLUSION
Zone Shift helps traders visually capture trend changes and key reaction points with precision. By combining band breakouts with real-time retest signals and trend-colored candles, this tool simplifies the process of reading market structure shifts and identifying high-confluence entry areas.
Money NoodleMoney Noodle Indicator - How It Works
The Money Noodle indicator is a trend-following and support/resistance tool that combines multiple exponential moving averages (EMAs) with dynamic volatility-based bands to create a comprehensive trading system.
Core Components
1. Triple EMA System ("The Noodles")
Fast EMA (12): Most responsive to price changes, shows short-term momentum
Medium EMA (21): Intermediate trend direction
Slow EMA (35): Main trend line that acts as the central reference point
The "noodle" effect comes from how these three EMAs weave around each other and the price action, creating curved, flowing lines that resemble noodles.
2. Dynamic Volatility Bands
Upper Band: Main EMA + (ATR × Band Multiplier)
Lower Band: Main EMA - (ATR × Band Multiplier)
Uses a 20-period ATR (Average True Range) to measure market volatility
Band width automatically adjusts - wider during volatile periods, tighter during consolidation
How It Functions
Trend Identification:
When all three EMAs are aligned (fast > medium > slow), it indicates a strong uptrend
When EMAs are inverted (fast < medium < slow), it signals a downtrend
EMA crossovers provide early trend change signals
Support & Resistance:
The bands act as dynamic support and resistance levels
Price tends to bounce off the bands during trending markets
Band breaks often signal strong momentum moves or trend changes
Volatility Assessment:
Band width indicates market volatility - wider bands = higher volatility
ATR-based calculation makes the bands adaptive to current market conditions
The 0.0125 multiplier provides optimal sensitivity for most timeframes
Trading Applications
Entry Signals:
Buy when price bounces off the lower band with EMA alignment
Sell when price bounces off the upper band against the trend
Breakout trades when price decisively breaks through bands
Trend Following:
Use the main EMA (35) as your trend filter
Trade in the direction of EMA alignment
The "noodles" help identify trend strength - tighter = stronger trend
Risk Management:
Bands provide natural stop-loss levels
Band width helps size positions (wider bands = smaller size due to higher volatility)
The indicator works best on daily timeframes and provides a visual, intuitive way to read market structure, trend direction, and volatility all in one tool.
Mogwai Method with RSI and EMA - BTCUSD 15mThis is a custom TradingView indicator designed for trading Bitcoin (BTCUSD) on a 15-minute timeframe. It’s based on the Mogwai Method—a mean-reversion strategy—enhanced with the Relative Strength Index (RSI) for momentum confirmation. The indicator generates buy and sell signals, visualized as green and red triangle arrows on the chart, to help identify potential entry and exit points in the volatile cryptocurrency market.
Components
Bollinger Bands (BB):
Purpose: Identifies overextended price movements, signaling potential reversions to the mean.
Parameters:
Length: 20 periods (standard for mean-reversion).
Multiplier: 2.2 (slightly wider than the default 2.0 to suit BTCUSD’s volatility).
Role:
Buy signal when price drops below the lower band (oversold).
Sell signal when price rises above the upper band (overbought).
Relative Strength Index (RSI):
Purpose: Confirms momentum to filter out false signals from Bollinger Bands.
Parameters:
Length: 14 periods (classic setting, effective for crypto).
Overbought Level: 70 (price may be overextended upward).
Oversold Level: 30 (price may be overextended downward).
Role:
Buy signal requires RSI < 30 (oversold).
Sell signal requires RSI > 70 (overbought).
Exponential Moving Averages (EMAs) (Plotted but not currently in signal logic):
Purpose: Provides trend context (included in the script for visualization, optional for signal filtering).
Parameters:
Fast EMA: 9 periods (short-term trend).
Slow EMA: 50 periods (longer-term trend).
Role: Can be re-added to filter signals (e.g., buy only when Fast EMA > Slow EMA).
Signals (Triangles):
Buy Signal: Green upward triangle below the bar when price is below the lower Bollinger Band and RSI is below 30.
Sell Signal: Red downward triangle above the bar when price is above the upper Bollinger Band and RSI is above 70.
How It Works
The indicator combines Bollinger Bands and RSI to spot mean-reversion opportunities:
Buy Condition: Price breaks below the lower Bollinger Band (indicating oversold conditions), and RSI confirms this with a reading below 30.
Sell Condition: Price breaks above the upper Bollinger Band (indicating overbought conditions), and RSI confirms this with a reading above 70.
The strategy assumes that extreme price movements in BTCUSD will often revert to the mean, especially in choppy or ranging markets.
Visual Elements
Green Upward Triangles: Appear below the candlestick to indicate a buy signal.
Red Downward Triangles: Appear above the candlestick to indicate a sell signal.
Bollinger Bands: Gray lines (upper, middle, lower) plotted for reference.
EMAs: Blue (Fast) and Orange (Slow) lines for trend visualization.
How to Use the Indicator
Setup
Open TradingView:
Log into TradingView and select a BTCUSD chart from a supported exchange (e.g., Binance, Coinbase, Bitfinex).
Set Timeframe:
Switch the chart to a 15-minute timeframe (15m).
Add the Indicator:
Open the Pine Editor (bottom panel in TradingView).
Copy and paste the script provided.
Click “Add to Chart” to apply it.
Verify Display:
You should see Bollinger Bands (gray), Fast EMA (blue), Slow EMA (orange), and buy/sell triangles when conditions are met.
Trading Guidelines
Buy Signal (Green Triangle Below Bar):
What It Means: Price is oversold, potentially ready to bounce back toward the Bollinger Band middle line.
Action:
Enter a long position (buy BTCUSD).
Set a take-profit near the middle Bollinger Band (bb_middle) or a resistance level.
Place a stop-loss 1-2% below the entry (or based on ATR, e.g., ta.atr(14) * 2).
Best Context: Works well in ranging markets; avoid during strong downtrends.
Sell Signal (Red Triangle Above Bar):
What It Means: Price is overbought, potentially ready to drop back toward the middle line.
Action:
Enter a short position (sell BTCUSD) or exit a long position.
Set a take-profit near the middle Bollinger Band or a support level.
Place a stop-loss 1-2% above the entry.
Best Context: Effective in ranging markets; avoid during strong uptrends.
Trend Filter (Optional):
To reduce false signals in trending markets, you can modify the script:
Add and ema_fast > ema_slow to the buy condition (only buy in uptrends).
Add and ema_fast < ema_slow to the sell condition (only sell in downtrends).
Check the Fast EMA (blue) vs. Slow EMA (orange) alignment visually.
Tips for BTCUSD on 15-Minute Charts
Volatility: BTCUSD can be erratic. If signals are too frequent, increase bb_mult (e.g., to 2.5) or adjust RSI levels (e.g., 75/25).
Confirmation: Use volume spikes or candlestick patterns (e.g., doji, engulfing) to confirm signals.
Time of Day: Mean-reversion works best during low-volume periods (e.g., Asian session in crypto).
Backtesting: Use TradingView’s Strategy Tester (convert to a strategy by adding entry/exit logic) to evaluate performance with historical BTCUSD data up to March 13, 2025.
Risk Management
Position Size: Risk no more than 1-2% of your account per trade.
Stop Losses: Always use stops to protect against BTCUSD’s sudden moves.
Avoid Overtrading: Wait for clear signals; don’t force trades in choppy or unclear conditions.
Example Scenario
Chart: BTCUSD, 15-minute timeframe.
Buy Signal: Price drops to $58,000, below the lower Bollinger Band, RSI at 28. A green triangle appears.
Action: Buy at $58,000, target $59,000 (middle BB), stop at $57,500.
Sell Signal: Price rises to $60,500, above the upper Bollinger Band, RSI at 72. A red triangle appears.
Action: Sell at $60,500, target $59,500 (middle BB), stop at $61,000.
This indicator is tailored for mean-reversion trading on BTCUSD. Let me know if you’d like to tweak it further (e.g., add filters, alerts, or alternative indicators)!
GOLDEN RSI by @thejamiulGOLDEN RSI thejamiul is a versatile Relative Strength Index (RSI)-based tool designed to provide enhanced visualization and additional insights into market trends and potential reversal points. This indicator improves upon the traditional RSI by integrating gradient fills for overbought/oversold zones and divergence detection features, making it an excellent choice for traders who seek precise and actionable signals.
Source of this indicator : This indicator is based on @TradingView original RSI indicator with a little bit of customisation to enhance overbought and oversold identification.
Key Features
1. Customizable RSI Settings:
RSI Length: Adjust the RSI calculation period to suit your trading style (default: 14).
Source Selection: Choose the price source (e.g., close, open, high, low) for RSI calculation.
2. Gradient-Filled RSI Zones:
Overbought Zone (80-100): Gradient fill with shades of green to indicate strong bullish conditions.
Oversold Zone (0-20): Gradient fill with shades of red to highlight strong bearish conditions.
3. Support and Resistance Levels:
Upper Band: 80
Middle Bands: 60 (bullish) and 40 (bearish)
Lower Band: 20
These levels help identify overbought, oversold, and neutral zones.
4. Divergence Detection:
Bullish Divergence: Detects lower lows in price with corresponding higher lows in RSI, signaling potential upward reversals.
Bearish Divergence: Detects higher highs in price with corresponding lower highs in RSI, indicating potential downward reversals.
Visual Indicators:
Bullish divergence is marked with green labels and line plots.
Bearish divergence is marked with red labels and line plots.
5. Alert Functionality:
Custom Alerts: Set up alerts for bullish or bearish divergences to stay notified of potential trading opportunities without constant chart monitoring.
6. Enhanced Chart Visualization:
RSI Plot: A smooth and visually appealing RSI curve.
Color Coding: Gradient and fills for better distinction of trading zones.
Pivot Labels: Clear identification of divergence points on the RSI plot.
