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!
스크립트에서 "band"에 대해 찾기
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.
SufinBDThis TradingView script combines RSI, Stochastic RSI, MACD, and Bollinger Bands to generate Buy and Sell signals on two different timeframes: 4-hour (4H) and Daily (1D). The strategy aims to provide entry and exit points based on a multi-indicator confirmation approach, helping traders make more informed decisions.
Features:
RSI (Relative Strength Index):
Measures the speed and change of price movements.
The script looks for oversold conditions (RSI below 30) for buy signals and overbought conditions (RSI above 70) for sell signals.
Stochastic RSI:
Measures the level of RSI relative to its high-low range over a given period.
A Stochastic RSI below 0.2 indicates oversold conditions, and a value above 0.8 indicates overbought conditions.
It helps identify overbought and oversold conditions in a more precise manner than regular RSI.
MACD (Moving Average Convergence Divergence):
A trend-following momentum indicator that shows the relationship between two moving averages of a security's price.
The MACD line crossing above the Signal line generates bullish signals, and vice versa for bearish signals.
Bollinger Bands:
A volatility indicator that consists of a middle band (SMA of price), an upper band, and a lower band.
When the price is below the lower band, it signals potential buy opportunities, while prices above the upper band signal potential sell opportunities.
Timeframe Usage:
The script calculates indicators for both the 4-hour (4H) and Daily (1D) timeframes.
The combined signals from these two timeframes are used to generate Buy and Sell alerts.
Buy Signal:
A Buy signal is generated when all of the following conditions are met:
RSI on both 4H and 1D is below 30 (oversold conditions).
Stochastic RSI on both timeframes is below 0.2.
The MACD line is above the Signal line on both timeframes.
The price is below the lower Bollinger Band on both the 4H and 1D charts.
Sell Signal:
A Sell signal is generated when all of the following conditions are met:
RSI on both 4H and 1D is above 70 (overbought conditions).
Stochastic RSI on both timeframes is above 0.8.
The MACD line is below the Signal line on both timeframes.
The price is above the upper Bollinger Band on both the 4H and 1D charts.
Visuals:
Buy signals are marked with green labels below the bars.
Sell signals are marked with red labels above the bars.
Bollinger Bands are displayed on the chart with the upper and lower bands marked in blue (for 4H) and orange (for 1D).
Purpose:
This script aims to provide more reliable buy/sell signals by combining indicators across multiple timeframes. It is ideal for traders who want to use multiple confirmation points before entering or exiting a trade.
How to Use:
Apply the script to any chart on TradingView.
Look for Buy and Sell signals that meet the conditions above.
You can adjust the timeframe (e.g., 4H or 1D) based on your trading strategy.
This script can be used for intraday trading, swing trading, or position trading depending on your preferred timeframes.
Example of Signal Interpretation:
Buy Signal:
If all conditions are met (e.g., RSI is under 30, Stochastic RSI is under 0.2, MACD is bullish, and price is below the lower Bollinger Band on both the 4-hour and daily charts), the script will show a green "BUY" label below the price bar.
Sell Signal:
If all conditions are met (e.g., RSI is over 70, Stochastic RSI is over 0.8, MACD is bearish, and price is above the upper Bollinger Band on both timeframes), the script will show a red "SELL" label above the price bar.
This combination of indicators offers a multi-layered confirmation approach, which aims to reduce the risk of false signals and increase the reliability of your trading decisions.
Volatility Signaling 50SMAOverview of the Script:
The script implements a volatility signaling indicator using a 50-period Simple Moving Average (SMA). It incorporates Bollinger Bands and the Average True Range (ATR) to dynamically adjust the SMA's color based on volatility conditions. Here's a detailed breakdown:
Components of the Script:
1. Inputs:
The script allows the user to customize key parameters for flexibility:
Bollinger Bands Length (length): Determines the period for calculating the Bollinger Bands.
Source (src): The price data to use, defaulting to the closing price.
Standard Deviation Multiplier (mult): Scales the Bollinger Bands' width.
ATR Length (atrLength): Sets the period for calculating the ATR.
The 50-period SMA length (smaLength) is fixed at 50.
2. Bollinger Bands Calculation:
Basis: Calculated as the SMA of the selected price source over the specified length.
Upper and Lower Bands: Determined by adding/subtracting a scaled standard deviation (dev) from the basis.
3. ATR Calculation:
Computes the Average True Range over the user-defined atrLength.
4. Volatility-Based Conditions:
The script establishes thresholds for Bollinger Band width relative to ATR:
Yellow Condition: When the band width (upper - lower) is less than 1.25 times the ATR.
Orange Condition: When the band width is less than 1.5 times the ATR.
Red Condition: When the band width is less than 1.75 times the ATR.
5. Dynamic SMA Coloring:
The 50-period SMA is colored based on the above conditions:
Yellow: Indicates relatively low volatility.
Orange: Indicates moderate volatility.
Red: Indicates higher volatility.
White: Default color when no conditions are met.
6. Plotting the 50-Period SMA:
The script plots the SMA (sma50) with a dynamically assigned color, enabling visual analysis of market conditions.
Use Case:
This script is ideal for traders seeking to assess market volatility and identify changes using Bollinger Bands and ATR. The colored SMA provides an intuitive way to gauge market dynamics directly on the chart.
Example Visualization:
Yellow SMA: The market is in a low-volatility phase.
Orange SMA: Volatility is picking up but remains moderate.
Red SMA: Higher volatility, potentially signaling significant market activity.
White SMA: Neutral/default state.
Enhanced Kaufman Adaptive Moving Average (KAMA) with Bollinger B# Enhanced Kaufman Adaptive Moving Average (KAMA) with Bollinger Bands
## Overview
This indicator combines the Kaufman Adaptive Moving Average (KAMA) with Bollinger Bands to create a comprehensive trading system. It provides adaptive trend following capabilities while measuring market volatility and potential reversal points.
## Key Features
- Adaptive moving average that adjusts to market conditions
- Dynamic Bollinger Bands for volatility measurement
- Color-coded KAMA line indicating trend direction
- Integrated buy/sell signals based on multiple confirmations
- Customizable parameters for both KAMA and Bollinger Bands
- Optional bar confirmation wait feature
- Built-in alert conditions for trade signals
## Main Components
### 1. Kaufman Adaptive Moving Average (KAMA)
- Adapts to market volatility using an efficiency ratio
- Changes color based on trend direction (green for uptrend, red for downtrend)
- Adjustable parameters for fine-tuning:
- Base Length: Controls the main calculation period (default: 10)
- Fast EMA Length: For rapid market response (default: 2)
- Slow EMA Length: For stable market conditions (default: 30)
### 2. Bollinger Bands
- Standard deviation-based volatility bands
- Customizable length and standard deviation multiplier
- Includes expansion threshold for volatility measurement
- Components:
- Upper Band: Upper volatility threshold
- Middle Band: Simple moving average
- Lower Band: Lower volatility threshold
## Signal Generation
### Buy Signals
Generated when:
1. KAMA color changes from red to green
2. Price closes above KAMA
3. Price closes above the middle Bollinger Band
4. Signals are marked with:
- Green triangles below the candles
- "B" labels for easy identification
### Sell Signals
Generated when:
1. KAMA color changes from green to red
2. Price closes below KAMA
3. Price closes below the middle Bollinger Band
4. Signals are marked with:
- Red triangles above the candles
- "S" labels for easy identification
## Customizable Parameters
### KAMA Settings
- Base Length (1-50)
- Fast EMA Length (1-10)
- Slow EMA Length (10-50)
- Source Price Selection
- Direction Highlight Toggle
- Bar Confirmation Option
### Bollinger Bands Settings
- Length (default: 20)
- Standard Deviation Multiplier (default: 2.0)
- Expansion Threshold (0.1-3.0)
## Alert Functionality
Built-in alerts for:
- Buy signals with customizable messages
- Sell signals with customizable messages
## Best Practices
### Timeframe Selection
- Works well on multiple timeframes
- Recommended for 15m to 4h charts for optimal signal generation
- Higher timeframes provide more reliable trend signals
### Parameter Optimization
- Adjust KAMA lengths based on trading style:
- Shorter lengths for day trading
- Longer lengths for swing trading
- Fine-tune BB multiplier based on market volatility
- Consider waiting for bar confirmation in volatile markets
### Risk Management
- Use in conjunction with other indicators for confirmation
- Consider market conditions and volatility when trading signals
- Implement proper position sizing and stop-loss levels
## Technical Notes
- Written in Pine Script™ v6
- Overlay indicator (displays on price chart)
- Compatible with all TradingView-supported markets
- Resource-efficient implementation for smooth performance
## Disclaimer
This indicator is provided under the Mozilla Public License 2.0. While it can be a valuable tool for technical analysis, it should not be used as the sole basis for trading decisions. Always combine with proper risk management and additional analysis methods.
Bitcoin wave modelBitcoin wave model is based on the logarithmic regression model and the sinusoidal waves, induced by the halving events.
This chart presents the outcome of an in-depth analysis of the complete set of Bitcoin price data available from October 2009 to August 2023.
The central concept is that the logarithm of the Bitcoin price closely adheres to the logarithmic regression model. If we plot the logarithm of the price against the logarithm of time, it forms a nearly straight line.
The parameters of this model are provided in the script as follows: log (BTCUSD) = 1.48 + 5.44log(h).
The secondary concept involves employing the inherent time unit of Bitcoin instead of days:
'h' denotes a slightly adjusted time measurement intrinsic to the Bitcoin blockchain. It can be approximated as (days since the genesis block) * 0.0007. Precisely, 'h' is defined as follows: h = 0 at the genesis block, h = 1 at the first halving block, and so forth. In general, h = block height / 210,000.
Adjustments are made to account for variations in block creation time.
The third concept revolves around investigating halving waves triggered by supply shock events resulting from the halvings. These halvings occur at regular intervals in Bitcoin's native time 'h'. All halvings transpire when 'h' is an integer. These events induce waves with intervals denoted as h = 1.
Consequently, we can model these waves using a sin(2pih - a) function. The parameter determining the time shift is assessed as 'a = 0.4', aligning with earlier expectations for halving events and their subsequent outcomes.
The fourth concept introduces the notion that the waves gradually diminish in amplitude over the progression of "time h," diminishing at a rate of 0.7^h.
Lastly, we can create bands around the modeled sinusoidal waves. The upper band is derived by multiplying the sine wave by a factor of 3.1*(1-0.16)^h, while the lower band is obtained by dividing the sine wave by the same factor, 3.1*(1-0.16)^h.
The current bandwidth is 2.5x. That means that the upper band is 2.5 times the lower band. These bands are forming an exceptionally narrow predictive channel for Bitcoin. Consequently, a highly accurate estimation of the peak of the next cycle can be derived.
The prediction indicates that the zenith past the fourth halving, expected around the summer of 2025, could result in prices ranging between 200,000 and 240,000 USD.
Enjoy the mathematical insights!
Nadaraya-Watson non repainting [LPWN]// ENGLISH
The problem of the wonderfuls Nadaraya-Watson indicators is that they repainting, @jdehorty made an aproximation of the Nadaraya-Watson Estimator using raational Quadratic Kernel so i used this indicator as inspiration i just added the Upper and lower band using ATR with this we get an aproximation of Nadaraya-Watson Envelope without repainting
Settings:
Bandwidth. This is the number of bars that the indicator will use as a lookback window.
Relative Weighting Parameter. The alpha parameter for the Rational Quadratic Kernel function. This is a hyperparameter that controls the smoothness of the curve. A lower value of alpha will result in a smoother, more stretched-out curve, while a lower value will result in a more wiggly curve with a tighter fit to the data. As this parameter approaches 0, the longer time frames will exert more influence on the estimation, and as it approaches infinity, the curve will become identical to the one produced by the Gaussian Kernel.
Color Smoothing. Toggles the mechanism for coloring the estimation plot between rate of change and cross over modes.
ATR Period. Period to calculate the ATR (upper and lower bands)
Multiplier. Separation of the bands
// SPANISH
El problema de los maravillosos indicadores de Nadaraya-Watson es que repintan, @jdehorty hizo una aproximación delNadaraya-Watson Estimator usando un Kernel cuadrático racional, así que usé este indicador como inspiración y solo agregamos la banda superior e inferior usando ATR con esto obtenemos una aproximación de Nadaraya-Watson Envelope sin volver a pintar
Configuración:
Banda ancha. Este es el número de barras que el indicador utilizará como ventana retrospectiva.
Parámetro de ponderación relativa. El parámetro alfa para la función Rational Quadratic Kernel. Este es un hiperparámetro que controla la suavidad de la curva. Un valor más bajo de alfa dará como resultado una curva más suave y estirada, mientras que un valor más bajo dará como resultado una curva más ondulada con un ajuste más ajustado a los datos. A medida que este parámetro se acerque a 0, los marcos de tiempo más largos ejercerán más influencia en la estimación y, a medida que se acerque al infinito, la curva será idéntica a la que produce el Gaussian Kernel.
Suavizado de color. Alterna el mecanismo para colorear el gráfico de estimación entre la tasa de cambio y los modos cruzados.
Período ATR. Periodo para calcular el ATR (bandas superior e inferior)
Multiplicador. Separación de las bandas
[CBB] Volatility Squeeze ToyThe main concept and features of this script are adapted from Mark Whistler's book "Volatility Illuminated". I have deviated from the use cases and strategies presented in the book, but the 3 Bollinger Bands use his optimized settings as the default length and standard deviation multiplier. Further insights into Mark's concepts and volatility research were gained by reading and watching some of TV user DadShark's materials (www.tradingview.com).
This script has been through many refinements and feature cycles, and I've added unrelated complimentary features not present in the book. The indicator is better studied than described, and unless you have read the book, any short summary of the material will just make you squint and think about the wrong things.
Here is a limited outline of features and concepts:
1. 3 Bollinger Bands of different length and/or deviation multiplier. Perhaps think of them as representing the various time frames that compression and expansion cycles and events manifest in, and also the expression of range, speed and price distribution within those time frames. You can gain insight into the magnitude of events based on how the three bands interact and stay contained, or not. If volatility is significant enough, all "time frames" represented by the bands will eventually record the event and subsequent price action, but the early signals will come from the spasms of the shortest, most volatile band. Many times the short band will contract again before, or just as it reaches a longer band, but in extreme cases, volatility will explode and all bands at all time frames will erupt in succession. In these cases you will see additional color representing shorter bands (lower time frame volatility in concept) traveling outside of longer bands. It is worth taking a look at the price levels and candles where these volatility bands cross each other.
2. In addition to the mean of the bands, there are a variety of other moving averages available to gauge trend, range, and areas of interest. This is accomplished with variable VWAP, ATR, smoothing, and a special derived loosely from the difference between them.
3. The bands are also used to derive conditions under which volatility is considered compressed, or in "squeeze" . Under these conditions the candles will turn yellow. Depending on your chart settings and indicator settings, these zones can be completely useless or drag on through fairly significant price action. Or, the can give you fantastic levels to watch for breakouts. The point is that volatility is compressed during these conditions, and you should expect the inevitable once this condition ends. Sometimes you can find yourself in a nice fat trend straight away, other times you may blow an account because you gorged your position based on arbitrary bar color. It's not like that. Pay attention to the highest and lowest bars of these squeeze ranges, and carefully observe future price action when it returns to these squeeze ranges. This info is more and more valuable at higher time frames.
The 3 bands, a smoothed long trend VWAP, and the squeeze condition colored bars are all active by default. All features can be shown or hidden on the control panel.
There are some deep market insights to mine if you live with this one for a while. As with any indicator, blunt "buy/sell here" approaches will lead to loss and frustration. however , if you pay attention to squeeze range, band/moving average confluence, high volume and/or large range candles their open/close behavior around these areas and squeeze ranges, you will start to catch the beginning of some powerful momentum moves.
Enjoy!
Blue Dot Red DotInspired by Dr Wish
This script is a confluence indicator designed to identify potential trend reversals or "mean reversion" trade setups. It plots buy (blue) and sell (red) dots directly on your price chart.
The core strategy is to find moments where price is overextended (using Bollinger Bands) and momentum is simultaneously reversing (using the Stochastic Oscillator). A signal is only generated when both of these conditions are met.
Core Components
The script combines two classic technical indicators:
Bollinger Bands (BB):
These create a "channel" around the price based on a simple moving average (the basis) and a standard deviation (dev).
Upper Band: Basis + (2.0 * StdDev)
Lower Band: Basis - (2.0 * StdDev)
In this script, the bands are used to identify when the price has moved significantly far from its recent average, suggesting it's "overbought" (at the upper band) or "oversold" (at the lower band) and may be due for a pullback.
Stochastic Oscillator:
This is a momentum oscillator that compares a closing price to its price range over a certain period.
It consists of two lines: %K (the main, faster line) and %D (a moving average of %K, the slower signal line).
It's used to identify overbought and oversold momentum conditions and, more importantly, momentum shifts, which are signaled by the %K and %D lines crossing.
Signal Logic: How the Dots Are Generated
This script's "secret sauce" is that it demands three specific conditions to be true at the same time before plotting a dot.
🔵 Blue Dot (Buy Signal)
A blue dot will appear below a price bar if all three of these conditions are met:
Stochastic Crossover: The faster %K line crosses above the slower %D line (ta.crossover(k, d)). This signals that short-term momentum is starting to turn bullish.
Was Oversold: On the previous bar, the %K line was below the "Oversold Threshold" (was_oversold = k < oversold). This ensures the bullish crossover is happening from an oversold (or at least bearish) momentum state.
Note: The default oversold threshold is set to 50. This is a key detail. It means the script is looking for a bullish crossover that originates from anywhere in the bottom half of the Stochastic range, not just the traditional "extreme" oversold area (like 20).
Price Extension: Within the last 3 bars (the current bar or the two before it), the price's low must have touched or gone below the lower Bollinger Band (bb_touch_lower). This confirms that the price itself is in an "oversold" or overextended area.
In plain English: A blue dot appears when the price has recently dipped to an extreme low (touching the lower BB) and its underlying momentum has just started to turn back up (Stoch cross from the lower half).
🔴 Red Dot (Sell Signal)
A red dot will appear above a price bar if all three of these conditions are met:
Stochastic Crossunder: The faster %K line crosses below the slower %D line (ta.crossunder(k, d)). This signals that short-term momentum is starting to turn bearish.
Was Overbought: On the previous bar, the %K line was above the "Overbought Threshold" (was_overbought = k > overbought). The default for this is 80, which is a traditional overbought level.
Price Extension: Within the last 3 bars (the current bar or the two before it), the price's high must have touched or gone above the upper Bollinger Band (bb_touch_upper). This confirms that the price itself is in an "overbought" or overextended area.
A red dot appears when the price has recently spiked to an extreme high (touching the upper BB) and its underlying momentum has just started to roll over and turn back down (Stoch cross from the overbought zone).
SuperTrendSAP1212This indicator combines Supertrend, VWAP with bands, and an optional RSI filter to generate Buy/Sell signals.
How it works
Supertrend Flip (ATR-based): Detects when trend direction changes (from bearish to bullish, or bullish to bearish).
VWAP Band Filter: Signals only trigger if the candle close is beyond the VWAP bands:
Buy = Supertrend flips up AND close > VWAP Upper Band
Sell = Supertrend flips down AND close < VWAP Lower Band
Optional RSI Filter:
Buy requires RSI < 20
Sell requires RSI > 80
Can be enabled/disabled in settings.
Features
Choice of VWAP band calculation mode: Standard Deviation or ATR.
Adjustable ATR/StDev length and multiplier for VWAP bands.
Toggle Supertrend, VWAP lines, and Buy/Sell labels.
Alerts included: add alerts on BUY or SELL conditions (use Once Per Bar Close to avoid intrabar signals).
Use
Works best on intraday or higher timeframes where VWAP is relevant.
Use the RSI filter for more selective signals.
Can be combined with your own stop-loss and risk management rules.
⚠️ Disclaimer: This script is for educational and research purposes only. It is not financial advice. Always test thoroughly and trade at your own risk.
