Drawdown from 22-Day High (Daily Anchored)This Pine Script indicator, titled "Drawdown from 22-Day High (Daily Anchored)," is designed to plot various drawdown levels from the highest high over the past 22 days. This helps traders visualize the performance and potential risk of the security in terms of its recent high points.
Key Features:
Daily High Data:
Fetches daily high prices using the request.security function with a daily timeframe.
Highest High Calculation:
Calculates the highest high over the last 22 days using daily data. This represents the highest price the security has reached in this period.
Drawdown Levels:
Computes various drawdown levels from the highest high:
2% Drawdown
5% Drawdown
10% Drawdown
15% Drawdown
25% Drawdown
45% Drawdown
50% Drawdown
Dynamic Line Coloring:
The color of the 2% drawdown line changes dynamically based on the current closing price:
Green (#02ff0b) if the close is above the 2% drawdown level.
Red (#ff0000) if the close is below the 2% drawdown level.
Plotting Drawdown Levels:
Plots each drawdown level on the chart with specific colors and line widths for easy visual distinction:
2% Drawdown: Green or Red, depending on the closing price.
5% Drawdown: Orange.
10% Drawdown: Blue.
15% Drawdown: Maroon.
25% Drawdown: Purple.
45% Drawdown: Yellow.
50% Drawdown: Black.
Labels for Drawdown Levels:
Adds labels at the end of each drawdown line to indicate the percentage drawdown:
Labels display "2% WVF," "5% WVF," "10% WVF," "15% WVF," "25% WVF," "45% WVF," and "50% WVF" respectively.
The labels are positioned dynamically at the latest bar index to ensure they are always visible.
Explanation of Williams VIX Fix (WVF)
The Williams VIX Fix (WVF) is a volatility indicator designed to replicate the behavior of the VIX (Volatility Index) using price data instead of options prices. It helps traders identify market bottoms and volatility spikes.
Key Aspects of WVF:
Calculation:
The WVF measures the highest high over a specified period (typically 22 days) and compares it to the current closing price.
It is calculated as:
WVF
=
highest high over period
−
current close
highest high over period
×
100
This formula provides a percentage measure of how far the price has fallen from its recent high.
Interpretation:
High WVF Values: Indicate increased volatility and potential market bottoms, suggesting oversold conditions.
Low WVF Values: Suggest lower volatility and potentially overbought conditions.
Usage:
WVF can be used in conjunction with other indicators (e.g., moving averages, RSI) to confirm signals.
It is particularly useful for identifying periods of significant price declines and potential reversals.
In the script, the WVF concept is incorporated into the drawdown levels, providing a visual representation of how far the price has fallen from its 22-day high.
Example Use Cases:
Risk Management: Quickly identify significant drawdown levels to assess the risk of current positions.
Volatility Monitoring: Use the WVF-based drawdown levels to gauge market volatility.
Support Levels: Utilize drawdown levels as potential support levels where price might find buying interest.
This script offers traders and analysts an efficient way to visualize and track important drawdown levels from recent highs, helping in better risk management and decision-making. The dynamic color and label features enhance the readability and usability of the indicator.
Ketidakstabilan
ATH DrawdownThis Pine Script indicator, titled "ATH Drawdown," is designed to help traders and analysts visualize various drawdown levels from the all-time high (ATH) of a security over the past 365 days. This indicator plots several key drawdown levels on the chart and dynamically updates their color and labels to reflect market conditions.
Key Features:
Daily High Calculation:
Fetches the daily high prices for the security using the request.security function.
Highest High Calculation:
Calculates the highest high over the last 365 days using daily data. This represents the all-time high (ATH) for the specified period.
Drawdown Levels:
Computes various drawdown levels from the ATH:
2% Drawdown
5% Drawdown
10% Drawdown
15% Drawdown
25% Drawdown
45% Drawdown
50% Drawdown
Dynamic Line Coloring:
The color of the 2% drawdown line changes dynamically based on the current closing price:
Red if the close is below the 2% drawdown level.
Green if the close is above the 2% drawdown level.
Plotting Drawdown Levels:
Plots each drawdown level on the chart with specific colors and line widths for easy visual distinction:
2% Drawdown: Green or Red, depending on the closing price.
5% Drawdown: Orange.
10% Drawdown: Blue.
15% Drawdown: Maroon.
25% Drawdown: Purple.
45% Drawdown: Yellow.
50% Drawdown: Black.
Labels for Drawdown Levels:
Adds labels at the end of each drawdown line to indicate the percentage drawdown:
Labels display "2%", "5%", "10%", "15%", "25%", "45%", and "50%" respectively.
The labels are positioned dynamically at the latest bar index to ensure they are always visible.
Example Use Cases:
Risk Management: Quickly identify significant drawdown levels to assess the risk of current positions.
Support Levels: Use drawdown levels as potential support levels where price might find buying interest.
Performance Tracking: Monitor how far the price has retraced from its all-time high to understand market sentiment and performance.
This script offers traders and analysts an efficient way to visualize and track important drawdown levels from the ATH, helping in better risk management and decision-making. The dynamic color and label features enhance the readability and usability of the indicator.
Squeeze Momentum Indicator [CHE] Squeeze Momentum Indicator
The Squeeze Momentum Indicator is an improved and simplified version of the classic Squeeze Momentum Indicator by LazyBear. It focuses on precise detection of squeeze phases without relying on Keltner Channels (KC) or complex momentum calculations. Instead, it emphasizes the dynamic analysis of Bollinger Band widths and their distance changes to provide clear and intuitive signals.
What is the Squeeze Momentum Indicator ?
This indicator helps you identify periods of low volatility (squeeze phases) when the market is often poised for significant moves. With its clear visualization and innovative methods, it enables traders to spot breakout opportunities early and trade strategically.
Differences from the Original LazyBear Indicator
1. Use of Bollinger Bands (BB):
- LazyBear Indicator combines Bollinger Bands with Keltner Channels. A squeeze is detected when the Bollinger Bands fall inside the Keltner Channels.
- CHE Indicator relies solely on Bollinger Bands and an additional analysis of their width (distance between the upper and lower bands). This makes the calculation more straightforward and reduces dependency on multiple indicator families.
2. Squeeze Detection:
- LazyBear: A squeeze is defined based on the relationship between Bollinger Bands and Keltner Channels. It has three states: “Squeeze On,” “Squeeze Off,” and “No Squeeze.”
- CHE: A squeeze is detected when the width of the Bollinger Bands falls below the lower "Distance Bollinger Bands." It only has two states: Squeeze Active and No Squeeze.
3. Momentum Calculation:
- LazyBear: Uses linear regression (LinReg) to calculate momentum and displays it as color-coded histograms.
- CHE: Does not include momentum calculations. The focus is entirely on volatility visualization and squeeze detection.
4. Visualization:
- LazyBear: Displays momentum histograms and horizontal lines to signal different states.
- CHE: Visualizes the width of the Bollinger Bands and their Distance Bollinger Bands as lines on the chart. The chart background turns green when a squeeze is detected, simplifying interpretation.
What Is Plotted?
1. Bollinger Band Width:
- A line representing the distance between the upper and lower Bollinger Bands, measuring market volatility.
2. Distance Bollinger Bands:
- Two additional lines (upper and lower Distance Bollinger Bands) based on the Bollinger Band width, defining thresholds for squeeze conditions.
3. Session-Specific Box:
- A dynamic box is drawn on the chart during a squeeze phase. The box marks the high and low of the market for the squeeze duration. It visually frames the range, helping traders monitor breakouts beyond these levels.
4. Max/Min Markers:
- The indicator dynamically updates and marks the maximum and minimum price levels during a squeeze. These levels can serve as breakout thresholds or critical reference points for price action.
5. Background Color:
- The chart background turns green when a squeeze is active (Bollinger Band width falls below the lower Distance Bollinger Bands). This highlights potential breakout conditions.
How to Use the CHE Indicator
1. Add the Indicator:
- Add the indicator to your chart and customize settings such as Bollinger Band length (`sqz_length`) and multiplier (`sqz_multiplier`) to fit your strategy.
2. Identify Squeeze Conditions:
- Watch for the green background, which signals a squeeze—indicating a period of low volatility where significant market moves often follow.
3. Monitor the Box and Max/Min Levels:
- During a squeeze, the box outlines the trading range, and the maximum and minimum levels are updated in real time. Use these as breakout triggers or support/resistance zones.
4. Session-Specific Analysis:
- The indicator can highlight squeezes during specific trading sessions (e.g., market open), allowing you to focus on key time frames.
5. Additional Confirmation:
- Combine the CHE Indicator with price action analysis or momentum tools to determine the direction of potential breakouts.
Why Use the Squeeze Momentum Indicator ?
- Simplicity: Clear visualization and reduced complexity by eliminating Keltner Channels and momentum calculations.
- Flexibility: Suitable for all markets—stocks, forex, crypto, and more.
- Enhanced Visualization: The box and max/min markers provide real-time visual cues for range-bound trading and breakout strategies.
- Efficiency: Focuses on what matters most—identifying volatility and squeeze phases.
With the Squeeze Momentum Indicator , you can take your trading strategy to the next level. Thanks to its clear design, dynamic range visualization, and innovative methods, you’ll recognize breakout opportunities earlier and trade with greater precision. Try it out and experience its user-friendliness and effectiveness for yourself!
Z-Score Indicator by RafIf the z-score goes above 2, this may indicate overbought and If the z-score goes below -2, this may indicate oversold
Volume & Range Spike DiamondVolume & Range Spike Diamond
Detect significant volume and price range breakouts directly on your chart with this intuitive indicator.
This TradingView indicator highlights bullish and bearish breakout opportunities by analyzing both volume and price range spikes. Perfect for identifying strong market movements in real-time.
Key Features:
Volume Increase Threshold (%): Customize the percentage increase in volume required to trigger a spike.
Price Range Increase Threshold (%): Define the percentage increase in the price range for additional precision.
Volume Lookback Period: Set the number of bars to calculate the average volume for comparison.
Bullish and Bearish Signals: Highlights bullish spikes below bars and bearish spikes above bars using colored diamonds.
Detailed Labels: Optionally display labels with percentage increases for volume and range.
Alerts Integration: Receive notifications for bullish and bearish breakout conditions.
How It Works:
The indicator compares the current bar's volume to the average volume of previous bars over the specified lookback period.
It also evaluates the price range (high - low) of the current bar against the previous bar.
If both volume and price range exceed their respective thresholds, a breakout condition is flagged.
Bullish spikes are displayed with upward-pointing diamonds below the bars, while bearish spikes use downward-pointing diamonds above the bars.
Optional labels show detailed percentage increases for both metrics.
Customization Options:
// Inputs
volumeIncreaseThreshold = input.float(50, "Volume Increase Threshold (%)", minval=0, step=5)
rangeIncreaseThreshold = input.float(200, "Price Range Increase Threshold (%)", minval=0, step=5)
lookbackPeriod = input.int(5, "Volume Lookback Period", minval=1, maxval=50)
showLastLabel = input.bool(false, "Show Only Last Label")
Alerts Configuration:
Bullish Volume Breakout: Triggered when a bullish spike is detected.
Bearish Volume Breakout: Triggered when a bearish spike is detected.
Enhance your trading strategy by detecting high-probability breakout opportunities with this reliable indicator!
ATR ReadoutDisplays a readout on the bottom right corner of the screen displaying ATR average (not of the individual candlestick, but of the current rolling period, including the candlestick in question).
Due to restrictions with Pine Script (or my knowledge thereof) only the current and previous candlestick data is shown, rather than the one currently hovered over.
The data is derived via the standard calculation for ATR.
Using this, one can quickly and easily get the proper data needed to calculate one's stop loss, rather than having to analyze the line graph of the basic ATR indicator.
Settings are implemented to change certain variables to your liking.
Waddah Attar Explosion V6 [Enhanced]Modified from the original @LazyBear code, with the following improvements:
* updated for Pine Script v6
* added customization for input values, including bar color
* added normalisation for all values to provide scale consistency
* added signal markers
* added alert code
The Waddah Attar Explosion (WAE), second panel from top, is a technical analysis indicator that combines trend detection, momentum, and volatility to identify potential trading opportunities. The main components of this indicator are:
1. Trend Component (t1):
Calculated using the difference between two EMAs (fast and slow)
Shows trend direction and strength
Positive values indicate uptrend, negative values indicate downtrend
The sensitivity multiplier amplifies these movements
2. Explosion Component (e1):
Based on Bollinger Bands width (difference between upper and lower bands)
Measures market volatility
Wider bands indicate higher volatility
Used to gauge potential for significant price movements
3. Dead Zone:
Calculated using moving average of True Range
Acts as a noise filter
Helps eliminate false signals in low-volatility periods
The visual elements are explained as follows:
A. Green/Red Columns:
Green columns: Upward trend movement (t1 > 0)
Red columns: Downward trend movement (t1 < 0)
Height indicates strength of the movement
B. Yellow Line (Explosion Line):
Shows the volatility component (e1)
Higher values suggest increased market volatility
Used to confirm signal strength
C. Blue Cross (Dead Zone):
Filters out weak signals
Signals should exceed this level to be considered valid
Buy Signals occur when:
* Green column is increasing
* Movement exceeds dead zone
* Momentum strength is above threshold
* Indicates potential upward price movement
Sell Signals occur when:
* Red column is increasing
* Movement exceeds dead zone
* Momentum strength is above threshold
* Indicates potential downward price movement
Key Features of this Version compared to the @LazyBear code:
Normalization Options:
Can normalize values between 0-1
Helps compare across different timeframes/instruments
Option for fixed or adaptive maximum values
Momentum Calculation:
Based on trend strength relative to volatility
Scaled based on explosion line range
Helps confirm signal strength
Signal Visualization:
Triangle markers for buy/sell signals
Labels showing momentum strength
Helps identify key trading opportunities
Usage Tips:
Signal Confirmation:
Wait for columns to exceed dead zone
Check explosion line for volatility confirmation
Verify momentum strength
Consider multiple timeframe analysis
Parameter Adjustment:
Adjust sensitivity based on trading style
Modify EMA lengths for different timeframes
Fine-tune dead zone multiplier for noise filtering
Risk Management:
Use with other indicators for confirmation
Consider market conditions and volatility
Don't rely solely on indicator signals
The WAE indicator is particularly useful for:
* Identifying trend reversals
* Measuring trend strength
* Filtering out noise
* Confirming breakout movements
* Gauging market volatility
Williams BBDiv Signal [trade_lexx]📈 Williams BBDiv Signal — Improve your trading strategy with accurate signals!
Introducing Williams BBDiv Signal , an advanced trading indicator designed for a comprehensive analysis of market conditions. This indicator combines Williams%R with Bollinger Bands, providing traders with a powerful tool for generating buy and sell signals, as well as detecting divergences. It is ideal for traders who need an advantage in detecting changing trends and market conditions.
🔍 How signals work
— A buy signal is generated when the Williams %R line crosses the lower Bollinger Bands band from bottom to top. This indicates that the market may be oversold and ready for a rebound. They are displayed as green triangles located under the Williams %R graph. On the main chart, buy signals are displayed as green triangles labeled "Buy" under candlesticks.
— A sell signal is generated when the Williams %R line crosses the upper Bollinger Bands band from top to bottom. This indicates that the market may be overbought and ready for a correction. They are displayed as red triangles located above the Williams %R chart. On the main chart, the sell signals are displayed as red triangles with the word "Sell" above the candlesticks.
— Minimum Bars Between Signals
The user can adjust the minimum number of bars between the signals to avoid false signals. This helps to filter out noise and improve signal quality.
— Mode "Wait for Opposite Signal"
In this mode, buy and sell signals are generated only after receiving the opposite signal. This adds an additional level of filtering and helps to avoid false alarms.
— Mode "Overbought and Oversold Zones"
A buy signal is generated only when Williams %R is below the -80 level (Lower Band). A sell signal is generated only when Williams %R is above -20 (Upper Band).
📊 Divergences
— Bullish divergence occurs when Williams%R shows a higher low while price shows a lower low. This indicates a possible upward reversal. They are displayed as green lines and labels labeled "Bull" on the Williams %R chart. On the main chart, bullish divergences are displayed as green triangles labeled "Bull" under candlesticks.
— A bearish divergence occurs when Williams %R shows a lower high, while the price shows a higher high. This indicates a possible downward reversal. They are displayed as red lines and labels labeled "Bear" on the Williams %R chart. On the main chart, bearish divergences are displayed as red triangles with the word "Bear" above the candlesticks.
— 🔌Connector Signal🔌 and 🔌Connector Divergence🔌
It allows you to connect the indicator to trading strategies and test signals throughout the trading history. This makes the indicator an even more powerful tool for traders who want to test the effectiveness of their strategies on historical data.
🔔 Alerts
The indicator provides the ability to set up alerts for buy and sell signals, as well as for divergences. This allows traders to keep abreast of important market developments without having to constantly monitor the chart.
🎨 Customizable Appearance
Customize the appearance of Williams BBDiv Signal according to your preferences to make the analysis more convenient and visually pleasing. In the indicator settings section, you can change the colors of the buy and sell signals, as well as divergences, so that they stand out on the chart and are easily visible.
🔧 How it works
— The indicator starts by calculating the Williams %R and Bollinger Bands values for a certain period to assess market conditions. Initial assumptions are introduced for overbought and oversold levels, as well as for the standard deviation of the Bollinger Bands. The indicator then analyzes these values to generate buy and sell signals. This classification helps to determine the appropriate level of volatility for signal calculation. As the market evolves, the indicator dynamically adjusts, providing information about the trend and volatility in real time.
Quick Guide to Using Williams BBDiv Signal
— Add the indicator to your favorites by clicking on the star icon. Adjust the parameters, such as the period length for Williams %R, the type of moving average and the standard deviation for Bollinger Bands, according to your trading style. Or leave all the default settings.
— Adjust the signal filters to improve the quality of the signals and avoid false alarms, adjust the filters in the "Signal Settings" section.
— Turn on alerts so that you don't miss important trading opportunities and don't constantly sit at the chart, set up alerts for buy and sell signals, as well as for divergences. This will allow you to keep abreast of all key market developments and respond to them in a timely manner, without being distracted from other business.
— Use signals. They will help you determine the optimal entry and exit points for your positions. Also, pay attention to bullish and bearish divergences, which may indicate possible market reversals and provide additional trading opportunities.
— Use the 🔌Connector🔌 for deeper analysis and verification of the effectiveness of signals, connect it to your trading strategies. This will allow you to test signals throughout the trading history and evaluate their accuracy based on historical data. Include the indicator in your trading strategy and run testing to see how buy and sell signals have worked in the past. Analyze the test results to determine how reliable the signals are and how they can improve your trading strategy. This will help you make better informed decisions and increase your trading efficiency.
Kalman Step Signals [AlgoAlpha]Take your trading to the next level with the Kalman Step Signals indicator by AlgoAlpha! This advanced tool combines the power of Kalman Filtering and the Supertrend indicator, offering a unique perspective on market trends and price movements. Designed for traders who seek clarity and precision in identifying trend shifts and potential trade entries, this indicator is packed with customizable features to suit your trading style.
Key Features
🔍 Kalman Filter Smoothing : Dynamically smooths price data with user-defined parameters for Alpha, Beta, and Period, optimizing responsiveness and trend clarity.
📊 Supertrend Overlay : Incorporates a classic Supertrend indicator to provide clear visual cues for trend direction and potential reversals.
🎨 Customizable Appearance : Adjust colors for bullish and bearish trends, along with optional exit bands for more nuanced analysis.
🔔 Smart Alerts : Detect key moments like trend changes or rejection entries for timely trading decisions.
📈 Advanced Visualization : Includes optional entry signals, exit bands, and rejection markers to pinpoint optimal trading opportunities.
How to Use
Add the Indicator : Add the script to your TradingView favorites. Customize inputs like Kalman parameters (Alpha, Beta, Period) and Supertrend settings (Factor, ATR Period) based on your trading strategy.
Interpret the Signals : Watch for trend direction changes using Supertrend lines and directional markers. Utilize rejection entries to identify price rejections at trendlines for precision entry points.
Set Alerts : Enable the built-in alert conditions for trend changes or rejection entries to act swiftly on trading opportunities without constant chart monitoring.
How It Works
The indicator leverages a Kalman Filter to smooth raw price data, balancing responsiveness and noise reduction using user-controlled parameters. This refined price data is then fed into a Supertrend calculation, combining ATR-based volatility analysis with dynamic upper and lower bands. The result is a clear and reliable trend-detection system. Additionally, it features rejection markers for bullish and bearish reversals when prices reject the trendline, along with exit bands to visualize potential price targets. The integration of customizable alerts ensures traders never miss critical market moves.
Add the Kalman Step Signals to your TradingView charts today and enjoy a smarter, more efficient trading experience! 🚀🌟
Kernel Regression Envelope with SMI OscillatorThis script combines the predictive capabilities of the **Nadaraya-Watson estimator**, implemented by the esteemed jdehorty (credit to him for his excellent work on the `KernelFunctions` library and the original Nadaraya-Watson Envelope indicator), with the confirmation strength of the **Stochastic Momentum Index (SMI)** to create a dynamic trend reversal strategy. The core idea is to identify potential overbought and oversold conditions using the Nadaraya-Watson Envelope and then confirm these signals with the SMI before entering a trade.
**Understanding the Nadaraya-Watson Envelope:**
The Nadaraya-Watson estimator is a non-parametric regression technique that essentially calculates a weighted average of past price data to estimate the current underlying trend. Unlike simple moving averages that give equal weight to all past data within a defined period, the Nadaraya-Watson estimator uses a **kernel function** (in this case, the Rational Quadratic Kernel) to assign weights. The key parameters influencing this estimation are:
* **Lookback Window (h):** This determines how many historical bars are considered for the estimation. A larger window results in a smoother estimation, while a smaller window makes it more reactive to recent price changes.
* **Relative Weighting (alpha):** This parameter controls the influence of different time frames in the estimation. Lower values emphasize longer-term price action, while higher values make the estimator more sensitive to shorter-term movements.
* **Start Regression at Bar (x\_0):** This allows you to exclude the potentially volatile initial bars of a chart from the calculation, leading to a more stable estimation.
The script calculates the Nadaraya-Watson estimation for the closing price (`yhat_close`), as well as the highs (`yhat_high`) and lows (`yhat_low`). The `yhat_close` is then used as the central trend line.
**Dynamic Envelope Bands with ATR:**
To identify potential entry and exit points around the Nadaraya-Watson estimation, the script uses **Average True Range (ATR)** to create dynamic envelope bands. ATR measures the volatility of the price. By multiplying the ATR by different factors (`nearFactor` and `farFactor`), we create multiple bands:
* **Near Bands:** These are closer to the Nadaraya-Watson estimation and are intended to identify potential immediate overbought or oversold zones.
* **Far Bands:** These are further away and can act as potential take-profit or stop-loss levels, representing more extreme price extensions.
The script calculates both near and far upper and lower bands, as well as an average between the near and far bands. This provides a nuanced view of potential support and resistance levels around the estimated trend.
**Confirming Reversals with the Stochastic Momentum Index (SMI):**
While the Nadaraya-Watson Envelope identifies potential overextended conditions, the **Stochastic Momentum Index (SMI)** is used to confirm a potential trend reversal. The SMI, unlike a traditional stochastic oscillator, oscillates around a zero line. It measures the location of the current closing price relative to the median of the high/low range over a specified period.
The script calculates the SMI on a **higher timeframe** (defined by the "Timeframe" input) to gain a broader perspective on the market momentum. This helps to filter out potential whipsaws and false signals that might occur on the current chart's timeframe. The SMI calculation involves:
* **%K Length:** The lookback period for calculating the highest high and lowest low.
* **%D Length:** The period for smoothing the relative range.
* **EMA Length:** The period for smoothing the SMI itself.
The script uses a double EMA for smoothing within the SMI calculation for added smoothness.
**How the Indicators Work Together in the Strategy:**
The strategy enters a long position when:
1. The closing price crosses below the **near lower band** of the Nadaraya-Watson Envelope, suggesting a potential oversold condition.
2. The SMI crosses above its EMA, indicating positive momentum.
3. The SMI value is below -50, further supporting the oversold idea on the higher timeframe.
Conversely, the strategy enters a short position when:
1. The closing price crosses above the **near upper band** of the Nadaraya-Watson Envelope, suggesting a potential overbought condition.
2. The SMI crosses below its EMA, indicating negative momentum.
3. The SMI value is above 50, further supporting the overbought idea on the higher timeframe.
Trades are closed when the price crosses the **far band** in the opposite direction of the trade. A stop-loss is also implemented based on a fixed value.
**In essence:** The Nadaraya-Watson Envelope identifies areas where the price might be deviating significantly from its estimated trend. The SMI, calculated on a higher timeframe, then acts as a confirmation signal, suggesting that the momentum is shifting in the direction of a potential reversal. The ATR-based bands provide dynamic entry and exit points based on the current volatility.
**How to Use the Script:**
1. **Apply the script to your chart.**
2. **Adjust the "Kernel Settings":**
* **Lookback Window (h):** Experiment with different values to find the smoothness that best suits the asset and timeframe you are trading. Lower values make the envelope more reactive, while higher values make it smoother.
* **Relative Weighting (alpha):** Adjust to control the influence of different timeframes on the Nadaraya-Watson estimation.
* **Start Regression at Bar (x\_0):** Increase this value if you want to exclude the initial, potentially volatile, bars from the calculation.
* **Stoploss:** Set your desired stop-loss value.
3. **Adjust the "SMI" settings:**
* **%K Length, %D Length, EMA Length:** These parameters control the sensitivity and smoothness of the SMI. Experiment to find settings that work well for your trading style.
* **Timeframe:** Select the higher timeframe you want to use for SMI confirmation.
4. **Adjust the "ATR Length" and "Near/Far ATR Factor":** These settings control the width and sensitivity of the envelope bands. Smaller ATR lengths make the bands more reactive to recent volatility.
5. **Customize the "Color Settings"** to your preference.
6. **Observe the plots:**
* The **Nadaraya-Watson Estimation (yhat)** line represents the estimated underlying trend.
* The **near and far upper and lower bands** visualize potential overbought and oversold zones based on the ATR.
* The **fill areas** highlight the regions between the near and far bands.
7. **Look for entry signals:** A long entry is considered when the price touches or crosses below the lower near band and the SMI confirms upward momentum. A short entry is considered when the price touches or crosses above the upper near band and the SMI confirms downward momentum.
8. **Manage your trades:** The script provides exit signals when the price crosses the far band. The fixed stop-loss will also close trades if the price moves against your position.
**Justification for Combining Nadaraya-Watson Envelope and SMI:**
The combination of the Nadaraya-Watson Envelope and the SMI provides a more robust approach to identifying potential trend reversals compared to using either indicator in isolation. The Nadaraya-Watson Envelope excels at identifying potential areas where the price is overextended relative to its recent history. However, relying solely on the envelope can lead to false signals, especially in choppy or volatile markets. By incorporating the SMI as a confirmation tool, we add a momentum filter that helps to validate the potential reversals signaled by the envelope. The higher timeframe SMI further helps to filter out noise and focus on more significant shifts in momentum. The ATR-based bands add a dynamic element to the entry and exit points, adapting to the current market volatility. This mashup aims to leverage the strengths of each indicator to create a more reliable trading strategy.
Uptrick: Smart BoundariesThis script is an indicator that combines the RSI (Relative Strength Index) and Bollinger Bands to highlight potential points where price momentum and volatility may both be at extreme levels. Below is a detailed explanation of its components, how it calculates signals, and why these two indicators have been merged into one tool. This script is intended solely for educational purposes and for traders who want to explore the combined use of momentum and volatility measures. Please remember that no single indicator guarantees profitable results.
Purpose of This Script
This script is designed to serve as a concise, all-in-one tool for traders seeking to track both momentum and volatility extremes in real time. By overlaying RSI signals with Bollinger Band boundaries, it helps users quickly identify points on a chart where price movement may be highly stretched. The goal is to offer a clearer snapshot of potential overbought or oversold conditions without requiring two separate indicators. Additionally, its optional pyramiding feature enables users to manage how many times they initiate trades when signals repeat in the same direction. Through these combined functions, the script aims to streamline technical analysis by consolidating two popular measures—momentum via RSI and volatility via Bollinger Bands—into a single, manageable interface.
1. Why Combine RSI and Bollinger Bands
• RSI (Relative Strength Index): This is a momentum oscillator that measures the speed and magnitude of recent price changes. It typically ranges between 0 and 100. Traders often watch for RSI crossing into “overbought” or “oversold” levels because it may indicate a potential shift in momentum.
• Bollinger Bands: These bands are plotted around a moving average, using a standard deviation multiplier to create an upper and lower boundary. They help illustrate how volatile the price has been relative to its recent average. When price moves outside these boundaries, some traders see it as a sign the price may be overstretched and could revert closer to the average.
Combining these two can be useful because it blends two different perspectives on market movement. RSI attempts to identify momentum extremes, while Bollinger Bands track volatility extremes. By looking for moments when both conditions agree, the script tries to highlight points where price might be unusually stretched in terms of both momentum and volatility.
2. How Signals Are Generated
• Buy Condition:
- RSI dips below a specified “oversold” level (for example, 30 by default).
- Price closes below the lower Bollinger Band.
When these occur together, the script draws a label indicating a potential bullish opportunity. The underlying reasoning is that momentum (RSI) suggests a stronger-than-usual sell-off, and price is also stretched below the lower Bollinger Band.
• Sell Condition:
- RSI rises above a specified “overbought” level (for example, 70 by default).
- Price closes above the upper Bollinger Band.
When these occur together, a label is plotted for a potential bearish opportunity. The rationale is that momentum (RSI) may be overheated, and the price is trading outside the top of its volatility range.
3. Pyramiding Logic and Trade Count Management
• Pyramiding refers to taking multiple positions in the same direction when signals keep firing. While some traders prefer just one position per signal, others like to scale into a trade if the market keeps pushing in their favor.
• This script uses variables that keep track of how many recent buy or sell signals have fired. If the count reaches a user-defined maximum, no more signals of that type will trigger additional labels. This protects traders from over-committing to one direction if the market conditions remain “extreme” for a prolonged period.
• If you disable the pyramiding feature, the script will only plot one label per side until the condition resets (i.e., until RSI and price conditions are no longer met).
4. Labels and Visual Feedback
• Whenever a buy or sell condition appears, the script plots a label directly on the chart:
- Buy labels under the price bar.
- Sell labels above the price bar.
These labels make it easier to review where both RSI and Bollinger Band conditions align. It can be helpful for visually scanning the chart to see if the signals show any patterns related to market reversals or trend continuations.
• The Bollinger Bands themselves are plotted so traders can see when the price is approaching or exceeding the upper or lower band. Watching the RSI and Bollinger Band plots simultaneously can give traders more context for each signal.
5. Originality and Usefulness
This script provides a distinct approach by merging two well-established concepts—RSI and Bollinger Bands—within a single framework, complemented by optional pyramiding controls. Rather than using each indicator separately, it attempts to uncover moments when momentum signals from RSI align with volatility extremes highlighted by Bollinger Bands. This combined perspective can aid in spotting areas of possible overextension in price. Additionally, the built-in pyramiding mechanism offers a method to manage multiple signals in the same direction, allowing users to adjust how aggressively they scale into trades. By integrating these elements together, the script aims to deliver a tool that caters to diverse trading styles while remaining straightforward to configure and interpret.
6. How to Use the Indicator
• Configure the Inputs:
- RSI Length (the lookback period used for the RSI calculation).
- RSI Overbought and Oversold Levels.
- Bollinger Bands Length and Multiplier (defines the moving average period and the degree of deviation).
- Option to reduce pyramiding.
• Set Alerts (Optional):
- You can create TradingView alerts for when these conditions occur, so you do not have to monitor the chart constantly. Choose the buy or sell alert conditions in your alert settings.
• Integration in a Trading Plan:
- This script alone is not a complete trading system. Consider combining it with other forms of analysis, such as support and resistance, volume profiles, or candlestick patterns. Thorough research, testing on historical data, and risk management are always recommended.
7. No Performance Guarantees
• This script does not promise any specific trading results. It is crucial to remember that no single indicator can accurately predict future market movements all the time. The script simply tries to highlight moments when two well-known indicators both point to an extreme condition.
• Actual trading decisions should factor in a range of market information, including personal risk tolerance and broader market conditions.
8. Purpose and Limitations
• Purpose:
- Provide a combined view of momentum (RSI) and volatility (Bollinger Bands) in a single script.
- Assist in spotting times when price may be at an extreme.
- Offer a configurable system for labeling potential buy or sell points based on these extremes.
• Limitations:
- Overbought and oversold conditions can persist for an extended period in trending markets.
- Bollinger Band breakouts do not always result in immediate reversals. Sometimes price keeps moving in the same direction.
- The script does not include a built-in exit strategy or risk management rules. Traders must handle these themselves.
Additional Disclosures
This script is published open-source and does not rely on any external or private libraries. It does not use lookahead methods or repaint signals; all calculations are performed on the current bar without referencing future data. Furthermore, the script is designed for standard candlestick or bar charts rather than non-standard chart types (e.g., Heikin Ashi, Renko). Traders should keep in mind that while the script can help locate potential momentum and volatility extremes, it does not include an exit strategy or account for factors like slippage or commission. All code comes from built-in Pine Script functions and standard formulas for RSI and Bollinger Bands. Anyone reviewing or modifying this script should exercise caution and incorporate proper risk management when applying it to their own trading.
Calculation Details
The script computes RSI by examining a user-defined number of prior bars (the RSI Length) and determining the average of up-moves relative to the average of down-moves over that period. This ratio is then scaled to a 0–100 range, so lower values typically indicate stronger downward momentum, while higher values suggest stronger upward momentum. In parallel, Bollinger Bands are generated by first calculating a simple moving average (SMA) of the closing price for the user-specified length. The script then measures the standard deviation of closing prices over the same period and multiplies it by the chosen factor (the Bollinger Bands Multiplier) to form the upper and lower boundaries around the SMA. These two measures are checked in tandem: if the RSI dips below a certain oversold threshold and price trades below the lower Bollinger Band, a condition is met that may imply a strong short-term sell-off; similarly, if the RSI surpasses the overbought threshold and price rises above the upper Band, it may indicate an overextended move to the upside. The pyramiding counters track how many of these signals occur in sequence, preventing excessive stacking of labels on the chart if conditions remain extreme for multiple bars.
Conclusion
This indicator aims to provide a more complete view of potential market extremes by overlaying the RSI’s momentum readings on top of Bollinger Band volatility signals. By doing so, it attempts to help traders see when both indicators suggest that the market might be oversold or overbought. The optional reduced pyramiding logic further refines how many signals appear, giving users the choice of a single entry or multiple scaling entries. It does not claim any guaranteed success or predictive power, but rather serves as a tool for those wanting to explore this combined approach. Always be cautious and consider multiple factors before placing any trades.
Dynamic Volatility Heatmap (ATR)How the Script Works
Dynamic Thresholds:
atrLow and atrHigh are calculated as percentiles (20% and 80% by default) of ATR values over the last double the ATR period (28 days if ATR is 14).
This creates thresholds that adapt to recent market conditions.
Background Heatmap:
Green: ATR is below the low threshold, indicating calm markets (options are cheap).
Red: ATR is above the high threshold, signaling elevated volatility (options are expensive).
Yellow: ATR is within the normal range, showing neutral market conditions.
Overlay Lines:
]Dynamic lines for atrLow and atrHigh help visualize thresholds on the chart.
Interpretation for Trading
Green Zone (Low ATR):
Interpretation: The market is calm, and options are likely underpriced.
Trade Setup: Favor buying options (e.g., long straddles or long calls/puts) to profit from potential volatility increases.
Red Zone (High ATR):
Interpretation: The market is volatile, and options are likely overpriced.
Trade Setup: Favor selling options (e.g., credit spreads or iron condors) to benefit from volatility decay.
Yellow Zone (Neutral ATR):
Interpretation: Volatility is within typical levels, offering no strong signal.
Trade Setup: Combine with other indicators, such as gamma levels or Bollinger Bands, for confirmation.
5. Enhancing with Other Indicators
Combine with Bollinger Bands:
Overlay Bollinger Bands to identify price extremes and align them with volatility heatmap signals.
Enhanced Price Z-Score OscillatorThe Enhanced Price Z-Score Oscillator by tkarolak is a powerful tool that transforms raw price data into an easy-to-understand statistical visualization using Z-Score-derived candlesticks. Simply put, it shows how far prices stray from their average in terms of standard deviations (Z-Scores), helping traders identify when prices are unusually high (overbought) or unusually low (oversold).
The indicator’s default feature displays Z-Score Candlesticks, where each candle reflects the statistical “distance” of the open, high, low, and close prices from their average. This creates a visual map of market extremes and potential reversal points. For added flexibility, you can also switch to Z-Score line plots based on either Close prices or OHLC4 averages.
With clear threshold lines (±2σ and ±3σ) marking moderate and extreme price deviations, and color-coded zones to highlight overbought and oversold areas, the oscillator simplifies complex statistical concepts into actionable trading insights.
Santa's Adventure [AlgoAlpha]Introducing "Santa's Adventure," a unique and festive TradingView indicator designed to bring the holiday spirit to your trading charts. With this indicator, watch as Santa, his sleigh, Rudolf the reindeer, and a flurry of snowflakes come to life, creating a cheerful visual experience while you monitor the markets.
Key Features:
🎁 Dynamic Santa Sleigh Visualization : Santa's sleigh, Rudolf, and holiday presents adapt to price movements and chart structure.
🎨 Customizable Holiday Colors : Adjust colors for Santa’s outfit, Rudolf’s nose, sleigh, presents, and more.
❄️ Realistic Snow Animation : A cascade of snowflakes decorates your charts, with density and range adjustable to suit your preferences.
📏 Adaptive Scaling : All visuals scale based on price volatility and market dynamics.
🔄 Rotation by Trend : Santa and his entourage tilt to reflect market trends, making it both functional and fun!
How to Use :
Add the Indicator to Your Chart : Search for "Santa's Adventure" in the TradingView indicator library and add it to your favorites. Use the input menu to adjust snow density, sleigh colors, and other festive elements to match your trading style or holiday mood.
Observe the Market : Watch Santa’s sleigh glide across the chart while Rudolf leads the way, with snowflakes gently falling to enhance the visual charm.
How It Works :
The indicator uses price volatility and market data to dynamically position Santa, his sleigh, Rudolf, and presents on the chart. Santa's Sleigh angle adjusts based on price trends, reflecting market direction. Santa's sleigh and the snowstorm are plotted using advanced polyline arrays for a smooth and interactive display. A festive algorithm powers the snowfall animation, ensuring a consistent and immersive holiday atmosphere. The visuals are built to adapt seamlessly to any market environment, combining holiday cheer with market insights.
Add "Santa's Adventure" to your TradingView charts today and bring the holiday spirit to your trading journey, Merry Christmas! 🎅🎄
Filtered ATR with EMA OverlayFiltered ATR with EMA Overlay is an advanced volatility indicator designed to provide a more accurate representation of market conditions by smoothing the standard Average True Range (ATR). This is achieved by filtering out extreme price movements and abnormal bars that can distort traditional ATR calculations.
The indicator applies an Exponential Moving Average (EMA) to the filtered ATR, creating a dual-layered system that highlights periods of increased or decreased volatility.
Key Features:
Filtered ATR: Filters out extreme bars, reducing noise and making the ATR line more reliable.
EMA Overlay: An EMA (default period of 10) is applied to the filtered ATR, allowing traders to track average volatility trends.
Volatility Signals:
Filtered ATR > EMA(10): Indicates higher-than-average volatility. This often correlates with trend breakouts or strong price movements.
Filtered ATR < EMA(10): Suggests reduced volatility, signaling potential consolidation or sideways price action.
Parameters:
atrLength (Default: 5):
The number of bars used to calculate the ATR. A shorter period (e.g., 3-5) responds faster to price changes, while a longer period (e.g., 10-14) provides smoother results.
multiplier (Default: 1.8):
Controls the sensitivity of the filter. A lower multiplier (e.g., 1.5) filters out more bars, resulting in smoother ATR. Higher values (e.g., 2.0) allow more bars to pass through, retaining more price volatility.
maxIterations (Default: 20):
The maximum number of bars processed to detect abnormal values. Increasing this may improve accuracy at the cost of performance.
ema10Period (Default: 10):
The period for the Exponential Moving Average applied to the filtered ATR. Shorter periods provide faster signals, while longer periods give smoother, lagging signals.
Trading Strategies:
1. Breakout Strategy:
When filtered ATR crosses above EMA(10):
Enter long positions when price breaks above a key resistance level.
Higher volatility suggests strong price action and momentum.
When filtered ATR drops below EMA(10):
Exit positions or tighten stop-loss orders as volatility decreases.
Lower volatility may indicate consolidation or trend exhaustion.
2. Trend Following Strategy:
Use the filtered ATR line to track overall volatility.
If filtered ATR consistently stays above EMA: Hold positions or add to trades.
If filtered ATR remains below EMA: Reduce position size or stay out of trades.
3. Mean Reversion Strategy:
When filtered ATR spikes significantly above EMA, it may indicate market overreaction.
Look for price to revert to the mean once ATR returns below the EMA.
4. Stop-Loss Adjustment:
As volatility increases (ATR above EMA), widen stop-loss levels to avoid being stopped out by random fluctuations.
In low volatility (ATR below EMA), tighten stop-losses to minimize losses during low activity periods.
Benefits:
Reduced Noise: By filtering abnormal bars, the indicator provides cleaner signals.
Better Trend Detection: EMA smoothing highlights volatility trends.
Adaptable: The indicator can be customized for scalping, day trading, or swing trading.
Intuitive Visualization: Traders can visually see volatility shifts and adjust strategies in real-time.
Best Practices:
Timeframes: Works effectively on all timeframes, but higher timeframes (e.g., 1H, 4H, Daily) yield more reliable signals.
Markets: Suitable for forex, crypto, stocks, and commodities.
Combining Indicators: Use in combination with RSI, Moving Averages, Bollinger Bands, or price action analysis for stronger signals.
How It Works (Under the Hood):
The script calculates the Daily Range (High - Low) for each bar.
The largest and smallest bars are filtered out if their difference exceeds the multiplier (default 1.8).
The remaining bars are averaged to generate the filtered ATR.
An EMA(10) is then applied to the filtered ATR for smoother visualization.
Breadth of Volatility The Breadth of Volatility (BoV) is an indicator designed to help traders understand the activity and volatility of the market. It focuses on analyzing how fast prices are moving and how much trading volume is driving those movements. By combining these two factors—price speed and volume strength—the BoV provides a single value that reflects the current level of market activity. This can help traders identify when the market is particularly active or calm, which is useful for planning trading strategies.
The speed component of the BoV measures how quickly prices are moving compared to their recent average. This is done by using a metric called the Average True Range (ATR), which calculates the typical size of price movements over a specific period. The BoV compares the current price change to this average, showing whether the market is moving faster or slower than usual. Faster price movements generally indicate higher volatility, which might signal opportunities for active traders.
The strength component focuses on the role of trading volume in price changes. It multiplies the trading volume by the size of the price movement to create a value called volume strength. This value is then compared to the highest volume strength seen over a recent period, which helps gauge whether the current price action is being strongly supported by trading activity. When the strength value is high, it suggests that market participants are actively trading and supporting the price movement.
These two components—speed and strength—are averaged to calculate the Breadth of Volatility value. While the formula also includes a placeholder for a third component (related to fundamental analysis), it is currently inactive and does not influence the final value. The BoV is displayed as a line on a chart, with a zero line for reference. Positive BoV values indicate heightened market activity and volatility, while values near zero suggest a quieter market. This indicator is particularly helpful for new traders to monitor market conditions and adjust their strategies accordingly, whether they’re focusing on trend-following or waiting for calmer periods for more conservative trades.
Important Notice:
Trading financial markets involves significant risk and may not be suitable for all investors. The use of technical indicators like this one does not guarantee profitable results. This indicator should not be used as a standalone analysis tool. It is essential to combine it with other forms of analysis, such as fundamental analysis, risk management strategies, and awareness of current market conditions. Always conduct thorough research or consult with a qualified financial advisor before making trading decisions. Past performance is not indicative of future results.
Disclaimer:
Trading financial instruments involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. This indicator is provided for informational and educational purposes only and should not be considered investment advice. Always conduct your own research and consult with a licensed financial professional before making any trading decisions.
Note: The effectiveness of any technical indicator can vary based on market conditions and individual trading styles. It's crucial to test indicators thoroughly using historical data and possibly paper trading before applying them in live trading scenarios.
Abnormal Delta Volume HistogramThis indicator can help traders spot potential turning points or heightened volatility and provides a dynamic measure of unusual market behavior by focusing on shifts in “delta volume.” Delta volume is approximated by assigning all of a bar’s volume to the bullish side if the close is higher than the open and to the bearish side if the close is lower. The result is a net volume measure that can hint at which side—buyers or sellers—has the upper hand. By comparing this delta volume to its historical averages and measuring how far current readings deviate in terms of standard deviations, the indicator can highlight bars that reflect significantly stronger than normal buying or selling pressure.
A histogram visualizes these delta volume values on a bar-by-bar basis, while additional reference lines for the mean and threshold boundaries allow traders to quickly identify abnormal conditions. When the histogram bars extend beyond the threshold lines, and are colored differently to signal abnormality, it can draw the trader’s eye to periods when market participation or sentiment may be shifting rapidly. This can be used as an early warning signal, prompting further investigation into price action, external news, or significant events that may be driving unusual volume patterns.
Important Notice:
Trading financial markets involves significant risk and may not be suitable for all investors. The use of technical indicators like this one does not guarantee profitable results. This indicator should not be used as a standalone analysis tool. It is essential to combine it with other forms of analysis, such as fundamental analysis, risk management strategies, and awareness of current market conditions. Always conduct thorough research or consult with a qualified financial advisor before making trading decisions. Past performance is not indicative of future results.
Disclaimer:
Trading financial instruments involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. This indicator is provided for informational and educational purposes only and should not be considered investment advice. Always conduct your own research and consult with a licensed financial professional before making any trading decisions.
Note: The effectiveness of any technical indicator can vary based on market conditions and individual trading styles. It's crucial to test indicators thoroughly using historical data and possibly paper trading before applying them in live trading scenarios.
Z-Strike RecoveryThis strategy utilizes the Z-Score of daily changes in the VIX (Volatility Index) to identify moments of extreme market panic and initiate long entries. Scientific research highlights that extreme volatility levels often signal oversold markets, providing opportunities for mean-reversion strategies.
How the Strategy Works
Calculation of Daily VIX Changes:
The difference between today’s and yesterday’s VIX closing prices is calculated.
Z-Score Calculation:
The Z-Score quantifies how far the current change deviates from the mean (average), expressed in standard deviations:
Z-Score=(Daily VIX Change)−MeanStandard Deviation
Z-Score=Standard Deviation(Daily VIX Change)−Mean
The mean and standard deviation are computed over a rolling period of 16 days (default).
Entry Condition:
A long entry is triggered when the Z-Score exceeds a threshold of 1.3 (adjustable).
A high positive Z-Score indicates a strong overreaction in the market (panic).
Exit Condition:
The position is closed after 10 periods (days), regardless of market behavior.
Visualizations:
The Z-Score is plotted to make extreme values visible.
Horizontal threshold lines mark entry signals.
Bars with entry signals are highlighted with a blue background.
This strategy is particularly suitable for mean-reverting markets, such as the S&P 500.
Scientific Background
Volatility and Market Behavior:
Studies like Whaley (2000) demonstrate that the VIX, known as the "fear gauge," is highly correlated with market panic phases. A spike in the VIX is often interpreted as an oversold signal due to excessive hedging by investors.
Source: Whaley, R. E. (2000). The investor fear gauge. Journal of Portfolio Management, 26(3), 12-17.
Z-Score in Financial Strategies:
The Z-Score is a proven method for detecting statistical outliers and is widely used in mean-reversion strategies.
Source: Chan, E. (2009). Quantitative Trading. Wiley Finance.
Mean-Reversion Approach:
The strategy builds on the mean-reversion principle, which assumes that extreme market movements tend to revert to the mean over time.
Source: Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
MA Deviation Suite [InvestorUnknown]This indicator combines advanced moving average techniques with multiple deviation metrics to offer traders a versatile tool for analyzing market trends and volatility.
Moving Average Types :
SMA, EMA, HMA, DEMA, FRAMA, VWMA: Standard moving averages with different characteristics for smoothing price data.
Corrective MA: This method corrects the MA by considering the variance, providing a more responsive average to price changes.
f_cma(float src, simple int length) =>
ma = ta.sma(src, length)
v1 = ta.variance(src, length)
v2 = math.pow(nz(ma , ma) - ma, 2)
v3 = v1 == 0 or v2 == 0 ? 1 : v2 / (v1 + v2)
var tolerance = math.pow(10, -5)
float err = 1
// Gain Factor
float kPrev = 1
float k = 1
for i = 0 to 5000 by 1
if err > tolerance
k := v3 * kPrev * (2 - kPrev)
err := kPrev - k
kPrev := k
kPrev
ma := nz(ma , src) + k * (ma - nz(ma , src))
Fisher Least Squares MA: Aims to reduce lag by using a Fisher Transform on residuals.
f_flsma(float src, simple int len) =>
ma = src
e = ta.sma(math.abs(src - nz(ma )), len)
z = ta.sma(src - nz(ma , src), len) / e
r = (math.exp(2 * z) - 1) / (math.exp(2 * z) + 1)
a = (bar_index - ta.sma(bar_index, len)) / ta.stdev(bar_index, len) * r
ma := ta.sma(src, len) + a * ta.stdev(src, len)
Sine-Weighted MA & Cosine-Weighted MA: These give more weight to middle bars, creating a smoother curve; Cosine weights are shifted for a different focus.
Deviation Metrics :
Average Absolute Deviation (AAD) and Median Absolute Deviation (MAD): AAD calculates the average of absolute deviations from the MA, offering a measure of volatility. MAD uses the median, which can be less sensitive to outliers.
Standard Deviation (StDev): Measures the dispersion of prices from the mean.
Average True Range (ATR): Reflects market volatility by considering the day's range.
Average Deviation (adev): The average of previous deviations.
// Calculate deviations
float aad = f_aad(src, dev_len, ma) * dev_mul
float mad = f_mad(src, dev_len, ma) * dev_mul
float stdev = ta.stdev(src, dev_len) * dev_mul
float atr = ta.atr(dev_len) * dev_mul
float avg_dev = math.avg(aad, mad, stdev, atr)
// Calculated Median with +dev and -dev
float aad_p = ma + aad
float aad_m = ma - aad
float mad_p = ma + mad
float mad_m = ma - mad
float stdev_p = ma + stdev
float stdev_m = ma - stdev
float atr_p = ma + atr
float atr_m = ma - atr
float adev_p = ma + avg_dev
float adev_m = ma - avg_dev
// upper and lower
float upper = f_max4(aad_p, mad_p, stdev_p, atr_p)
float upper2 = f_min4(aad_p, mad_p, stdev_p, atr_p)
float lower = f_min4(aad_m, mad_m, stdev_m, atr_m)
float lower2 = f_max4(aad_m, mad_m, stdev_m, atr_m)
Determining Trend
The indicator generates trend signals by assessing where price stands relative to these deviation-based lines. It assigns a trend score by summing individual signals from each deviation measure. For instance, if price crosses above the MAD-based upper line, it contributes a bullish point; crossing below an ATR-based lower line contributes a bearish point.
When the aggregated trend score crosses above zero, it suggests a shift towards a bullish environment; crossing below zero indicates a bearish bias.
// Define Trend scores
var int aad_t = 0
if ta.crossover(src, aad_p)
aad_t := 1
if ta.crossunder(src, aad_m)
aad_t := -1
var int mad_t = 0
if ta.crossover(src, mad_p)
mad_t := 1
if ta.crossunder(src, mad_m)
mad_t := -1
var int stdev_t = 0
if ta.crossover(src, stdev_p)
stdev_t := 1
if ta.crossunder(src, stdev_m)
stdev_t := -1
var int atr_t = 0
if ta.crossover(src, atr_p)
atr_t := 1
if ta.crossunder(src, atr_m)
atr_t := -1
var int adev_t = 0
if ta.crossover(src, adev_p)
adev_t := 1
if ta.crossunder(src, adev_m)
adev_t := -1
int upper_t = src > upper ? 3 : 0
int lower_t = src < lower ? 0 : -3
int upper2_t = src > upper2 ? 1 : 0
int lower2_t = src < lower2 ? 0 : -1
float trend = aad_t + mad_t + stdev_t + atr_t + adev_t + upper_t + lower_t + upper2_t + lower2_t
var float sig = 0
if ta.crossover(trend, 0)
sig := 1
else if ta.crossunder(trend, 0)
sig := -1
Backtesting and Performance Metrics
The code integrates with a backtesting library that allows traders to:
Evaluate the strategy historically
Compare the indicator’s signals with a simple buy-and-hold approach
Generate performance metrics (e.g., mean returns, Sharpe Ratio, Sortino Ratio) to assess historical effectiveness.
Practical Usage and Calibration
Default settings are not optimized: The given parameters serve as a starting point for demonstration. Users should adjust:
len: Affects how smooth and lagging the moving average is.
dev_len and dev_mul: Influence the sensitivity of the deviation measures. Larger multipliers widen the bands, potentially reducing false signals but introducing more lag. Smaller multipliers tighten the bands, producing quicker signals but potentially more whipsaws.
This flexibility allows the trader to tailor the indicator for various markets (stocks, forex, crypto) and time frames.
Disclaimer
No guaranteed results: Historical performance does not guarantee future outcomes. Market conditions can vary widely.
User responsibility: Traders should combine this indicator with other forms of analysis, appropriate risk management, and careful calibration of parameters.
Trend Trader-Remastered StrategyOfficial Strategy for Trend Trader - Remastered
Indicator: Trend Trader-Remastered (TTR)
Overview:
The Trend Trader-Remastered is a refined and highly sophisticated implementation of the Parabolic SAR designed to create strategic buy and sell entry signals, alongside precision take profit and re-entry signals based on marked Bill Williams (BW) fractals. Built with a deep emphasis on clarity and accuracy, this indicator ensures that only relevant and meaningful signals are generated, eliminating any unnecessary entries or exits.
Please check the indicator details and updates via the link above.
Important Disclosure:
My primary objective is to provide realistic strategies and a code base for the TradingView Community. Therefore, the default settings of the strategy version of the indicator have been set to reflect realistic world trading scenarios and best practices.
Key Features:
Strategy execution date&time range.
Take Profit Reduction Rate: The percentage of progressive reduction on active position size for take profit signals.
Example:
TP Reduce: 10%
Entry Position Size: 100
TP1: 100 - 10 = 90
TP2: 90 - 9 = 81
Re-Entry When Rate: The percentage of position size on initial entry of the signal to determine re-entry.
Example:
RE When: 50%
Entry Position Size: 100
Re-Entry Condition: Active Position Size < 50
Re-Entry Fill Rate: The percentage of position size on initial entry of the signal to be completed.
Example:
RE Fill: 75%
Entry Position Size: 100
Active Position Size: 50
Re-Entry Order Size: 25
Final Active Position Size:75
Important: Even RE When condition is met, the active position size required to drop below RE Fill rate to trigger re-entry order.
Key Points:
'Process Orders on Close' is enabled as Take Profit and Re-Entry signals must be executed on candle close.
'Calculate on Every Tick' is enabled as entry signals are required to be executed within candle time.
'Initial Capital' has been set to 10,000 USD.
'Default Quantity Type' has been set to 'Percent of Equity'.
'Default Quantity' has been set to 10% as the best practice of investing 10% of the assets.
'Currency' has been set to USD.
'Commission Type' has been set to 'Commission Percent'
'Commission Value' has been set to 0.05% to reflect the most realistic results with a common taker fee value.
ATR Oscillator with Dots and Dynamic Zero LineWhat It Is
The ATR Oscillator with Dots and Dynamic Zero Line is a custom indicator based on the Average True Range (ATR), designed to provide traders with enhanced insights into market volatility and directional bias. Unlike traditional ATR oscillators that plot continuous lines, this version uses distinct dots to display ATR values and includes a dynamic zero line that changes color based on market direction (uptrend, downtrend, or consolidation).
How It Works
ATR Calculation:
The indicator calculates the Average True Range over a user-defined period (default: 14 bars). ATR measures market volatility by considering the range between the high, low, and close of each bar.
Dots for ATR Values:
Instead of plotting ATR values as a continuous line, the indicator represents each value as an individual blue dot. This format highlights changes in volatility without visually connecting them, helping to avoid false trends and clutter.
Dynamic Zero Line:
A horizontal zero line provides additional directional context. The line changes color dynamically:
Green: Indicates an uptrend (price is consistently closing higher over consecutive bars).
Red: Indicates a downtrend (price is consistently closing lower over consecutive bars).
Gray: Indicates market consolidation or sideways movement (no clear trend in price).
The thickness and step-like style of the zero line make it visually prominent, enabling quick interpretation of market direction.
What It Does
Visualizes Market Volatility:
By plotting ATR values as dots, the oscillator emphasizes periods of heightened or reduced market activity, helping traders anticipate breakout opportunities or avoid low-volatility zones.
Provides Trend Context:
The dynamic zero line gives traders a clear signal of the prevailing market trend (uptrend, downtrend, or consolidation), which can be used to align trading strategies with the broader market context.
Avoids Misleading Trends:
Unlike traditional ATR oscillators that use continuous lines, this version eliminates visual artifacts caused by noise, such as false trends during consolidation periods.
Simplifies Interpretation:
The combination of ATR dots and a color-coded zero line creates a straightforward and intuitive tool for assessing both volatility and market direction.
Why It’s More Useful Than a Traditional ATR Oscillator
Enhanced Visibility:
The use of dots instead of a continuous line makes it easier to spot discrete changes in ATR values, avoiding visual clutter and false impressions of smooth trends.
Dynamic Market Context:
Traditional ATR oscillators only measure volatility, offering no indication of market direction. The dynamic zero line in this oscillator adds valuable directional context, helping traders align their strategies with the trend.
Better for Range-Bound Markets:
The zero line’s color-changing feature highlights consolidation periods, enabling traders to identify and avoid trading during sideways, low-volatility conditions where false signals are common.
Quick Decision-Making:
With clear visual cues (dots and color-coded lines), traders can quickly assess market conditions without needing to analyze multiple charts or indicators.
Improved Confluence:
The oscillator’s signals can easily be combined with other tools like VWAP, Volume Profile, or Order Flow indicators for more confident trade decisions.
When to Use It
Trending Markets:
Use the dynamic zero line to confirm the market’s direction and align trades accordingly.
Breakout Opportunities:
Look for periods of increasing ATR (dots moving higher) to anticipate high-volatility breakout scenarios.
Avoiding Noise:
During consolidation (gray zero line), this oscillator warns traders to wait for clearer signals before entering trades.
TS Aggregated Median Absolute DeviationTS Aggregated Median Absolute Deviation (MAD) Indicator Explanation
Overview
The TS Aggregated Median Absolute Deviation (MAD) is a powerful indicator designed for traders looking for momentum-based strategies. By aggregating the Median Absolute Deviation (MAD) across multiple timeframes, it provides a comprehensive view of market dynamics. This indicator helps identify potential reversal points, overbought/oversold conditions, and general market trends by leveraging the concept of MAD, which measures price dispersion from the median.
Signal Generation:
Long Signal: Triggered when the price moves above the aggregated upper band
Short Signal: Triggered when the price moves below the aggregated red band
Alerts:
Real-time alerts are integrated to notify the user of long or short signals when confirmed:
Long Signal Alert: "TS MAD Flipped ⬆LONG⬆"
Short Signal Alert: "TS MAD Flipped ⬇Short⬇"
Optimization:
Adjust thresholds, MAD lengths, and multipliers for each timeframe to suit the specific asset and market conditions.
Experiment with enabling/disabling MAD components to focus on particular timeframes.
VIX Spike StrategyThis script implements a trading strategy based on the Volatility Index (VIX) and its standard deviation. It aims to enter a long position when the VIX exceeds a certain number of standard deviations above its moving average, which is a signal of a volatility spike. The position is then exited after a set number of periods.
VIX Symbol (vix_symbol): The input allows the user to specify the symbol for the VIX index (typically "CBOE:VIX").
Standard Deviation Length (stddev_length): The number of periods used to calculate the standard deviation of the VIX. This can be adjusted by the user.
Standard Deviation Multiplier (stddev_multiple): This multiplier is used to determine how many standard deviations above the moving average the VIX must exceed to trigger a long entry.
Exit Periods (exit_periods): The user specifies how many periods after entering the position the strategy will exit the trade.
Strategy Logic:
Data Loading: The script loads the VIX data, both for the current timeframe and as a rescaled version for calculation purposes.
Standard Deviation Calculation: It calculates both the moving average (SMA) and the standard deviation of the VIX over the specified period (stddev_length).
Entry Condition: A long position is entered when the VIX exceeds the moving average by a specified multiple of its standard deviation (calculated as vix_mean + stddev_multiple * vix_stddev).
Exit Condition: After the position is entered, it will be closed after the user-defined number of periods (exit_periods).
Visualization:
The VIX is plotted in blue.
The moving average of the VIX is plotted in orange.
The threshold for the VIX, which is the moving average plus the standard deviation multiplier, is plotted in red.
The background turns green when the entry condition is met, providing a visual cue.
Sources:
The VIX is often used as a measure of market volatility, with high values indicating increased uncertainty in the market.
Standard deviation is a statistical measure of the variability or dispersion of a set of data points. In financial markets, it is used to measure the volatility of asset prices.
References:
Bollerslev, T. (1986). "Generalized Autoregressive Conditional Heteroskedasticity." Journal of Econometrics.
Black, F., & Scholes, M. (1973). "The Pricing of Options and Corporate Liabilities." Journal of Political Economy.
