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! 🚀🌟
Volatilità
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.
Market Flow Volatility Oscillator (AiBitcoinTrend)The Market Flow Volatility Oscillator (AiBitcoinTrend) is a cutting-edge technical analysis tool designed to evaluate and classify market volatility regimes. By leveraging Gaussian filtering and clustering techniques, this indicator provides traders with clear insights into periods of high and low volatility, helping them adapt their strategies to evolving market conditions. Built for precision and clarity, it combines advanced mathematical models with intuitive visual feedback to identify trends and volatility shifts effectively.
👽 How the Indicator Works
👾 Volatility Classification with Gaussian Filtering
The indicator detects volatility levels by applying Gaussian filters to the price series. Gaussian filters smooth out noise while preserving significant price movements. Traders can adjust the smoothing levels using sigma parameters, enabling greater flexibility:
Low Sigma: Emphasizes short-term volatility.
High Sigma: Captures broader trends with reduced sensitivity to small fluctuations.
👾 Clustering Algorithm for Regime Detection
The core of this indicator is its clustering model, which classifies market conditions into two distinct regimes:
Low Volatility Regime: Calm periods with reduced market activity.
High Volatility Regime: Intense periods with heightened price movements.
The clustering process works as follows:
A rolling window of data is analyzed to calculate the standard deviation of price returns.
Two cluster centers are initialized using the 25th and 75th percentiles of the data distribution.
Each price volatility value is assigned to the nearest cluster based on its distance to the centers.
The cluster centers are refined iteratively, providing an accurate and adaptive classification.
👾 Oscillator Generation with Slope R-Values
The indicator computes Gaussian filter slopes to generate oscillators that visualize trends:
Oscillator Low: Captures low-frequency market behavior.
Oscillator High: Tracks high-frequency, faster-changing trends.
The slope is measured using the R-value of the linear regression fit, scaled and adjusted for easier interpretation.
👽 Applications
👾 Trend Trading
When the oscillator rises above 0.5, it signals potential bullish momentum, while dips below 0.5 suggest bearish sentiment.
👾 Pullback Detection
When the oscillator peaks, especially in overbought or oversold zones, provide early warnings of potential reversals.
👽 Indicator Settings
👾 Oscillator Settings
Sigma Low/High: Controls the smoothness of the oscillators.
Smaller Values: React faster to price changes but introduce more noise.
Larger Values: Provide smoother signals with longer-term insights.
👾 Window Size and Refit Interval
Window Size: Defines the rolling period for cluster and volatility calculations.
Shorter windows: adapt faster to market changes.
Longer windows: produce stable, reliable classifications.
Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
EGARCH Volatility Estimator
EGARCH Volatility Estimator (EVE)
Overview:
The EGARCH Volatility Estimator (EVE) is a Pine Script indicator designed to quantify market volatility using the Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model. This model captures both symmetric and asymmetric volatility dynamics and provides a robust tool for analyzing market risk and trends.
Key Features:
Core EGARCH Formula:
ln(σ t 2 )=ω+α(∣ϵ t−1 ∣+γ⋅ϵ t−1 )+β⋅ln(σ t−1 2 )
ω (Omega): Captures long-term baseline volatility.
α (Alpha): Measures sensitivity to recent shocks.
γ (Gamma): Incorporates asymmetric effects (e.g., higher volatility during market drops).
β (Beta): Reflects the persistence of historical volatility.
The formula computes log-volatility, which is then converted to actual volatility for interpretation.
Standardized Returns:
The script calculates daily log-returns and standardizes them to measure deviations from expected price changes.
Percentile-Based Volatility Analysis:
Tracks the percentile rank of current volatility over a historical lookback period.
Highlights high, medium, or low volatility zones using dynamic background colors.
Dynamic Normalization:
Maps volatility into a normalized range ( ) for better visual interpretation.
Uses color gradients (green to red) to reflect changing volatility levels.
SMA Integration:
Adds a Simple Moving Average (SMA) of either EGARCH volatility or its percentile for trend analysis.
Interactive Display:
Displays current volatility and its percentile rank in a table for quick reference.
Includes high (75%) and low (25%) volatility threshold lines for actionable insights.
Applications:
Market Risk Assessment: Evaluate current and historical volatility to assess market risk levels.
Quantitative Strategy Development: Incorporate volatility dynamics into trading strategies, particularly for options or risk-managed portfolios.
Trend and Momentum Analysis: Use normalized or smoothed volatility trends to identify potential reversals or breakouts.
Asymmetric Volatility Detection: Highlight periods where downside or upside volatility dominates.
Visualization Enhancements:
Dynamic colors and thresholds make it intuitive to interpret market conditions.
Percentile views provide relative volatility context for historical comparison.
This indicator is a versatile tool for traders and analysts seeking deeper insights into market behavior, particularly in volatility-driven trading strategies.
RSI BB StdDev SignalOverview
The RSI BB StdDev Signal Indicator is a powerful tool designed to enhance your trading strategy by combining the Relative Strength Index (RSI) with Bollinger Bands (BB). This unique combination allows traders to identify potential buy and sell signals more accurately by leveraging the strengths of both indicators. The RSI helps in identifying overbought and oversold conditions, while the Bollinger Bands provide a dynamic range to assess volatility and potential price reversals.
Key Features
— RSI Calculation: The indicator calculates the RSI based on user-defined parameters, allowing for customization to fit different trading styles.
— Bollinger Bands Integration: The RSI values are smoothed using a moving average, and Bollinger Bands are applied to this smoothed RSI to generate buy and sell signals.
— Divergence Detection: The indicator includes an optional feature to detect and alert on bullish and bearish divergences between the RSI and price action.
— Customizable Alerts: Users can set up alerts for buy and sell signals, as well as for divergences, ensuring they never miss a trading opportunity.
— Visual Aids: The indicator plots the RSI, Bollinger Bands, and signals on the chart, making it easy to visualize and interpret the data.
How It Works
1. RSI Calculation:
— The RSI is calculated using the change in the source input (default is close price) over a specified period.
— The RSI values are then plotted on the chart with customizable overbought and oversold levels.
2. Smoothing and Bollinger Bands:
— The RSI values are smoothed using a moving average (SMA, EMA, SMMA, WMA, VWMA) selected by the user.
— Bollinger Bands are applied to the smoothed RSI to create dynamic upper and lower bands.
3. Signal Generation:
—Buy signals are generated when the RSI crosses above the lower Bollinger Band.
—Sell signals are generated when the RSI crosses below the upper Bollinger Band.
—These signals are plotted on both the RSI pane and the main price chart for easy reference.
4. Divergence Detection:
— The indicator can detect and alert on regular bullish and bearish divergences between the RSI and price action.
— Bullish divergences occur when the price makes a lower low, but the RSI makes a higher low.
— Bearish divergences occur when the price makes a higher high, but the RSI makes a lower high.
Usage
1. Setting Up:
— Add the indicator to your TradingView chart.
— Customize the RSI length, source, and other parameters in the settings panel.
— Enable or disable the divergence detection based on your trading strategy.
2. Interpreting Signals:
— Use the buy and sell signals generated by the RSI crossing the Bollinger Bands as potential entry and exit points.
— Pay attention to divergences for additional confirmation of trend reversals.
3. Alerts:
— Set up alerts for buy and sell signals to receive notifications in real-time.
— Enable divergence alerts to be notified of potential trend reversals.
Conclusion
The RSI BB StdDev Signal Indicator is a comprehensive tool that combines the strengths of the RSI and Bollinger Bands to provide traders with more accurate and reliable signals. Whether you are a beginner or an experienced trader, this indicator can enhance your trading strategy by offering clear visual cues and customizable alerts.
Note
This indicator is provided with open-source code, allowing users to understand its logic and customize it further if needed. The detailed description and customizable settings ensure that traders of all levels can benefit from its unique features.
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.
DT Bollinger BandsIndicator Overview
Purpose: The script calculates and plots Bollinger Bands, a technical analysis tool that shows price volatility by plotting:
A central moving average (basis line).
Upper and lower bands representing price deviation from the moving average.
Additional bands for a higher deviation threshold (3 standard deviations).
Customization: Users can customize:
The length of the moving average.
The type of moving average (e.g., SMA, EMA).
The price source (e.g., close price).
Standard deviation multipliers for the bands.
Fixed Time Frame: The script can use a fixed time frame (e.g., daily) for calculations, regardless of the chart's time frame.
Key Features
Moving Average Selection:
The user can select the type of moving average for the basis line:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Smoothed Moving Average (SMMA/RMA)
Weighted Moving Average (WMA)
Volume Weighted Moving Average (VWMA)
Standard Deviation Multipliers:
Two multipliers are used:
Standard (default = 2.0): For the original Bollinger Bands.
Larger (default = 3.0): For additional bands.
Bands Calculation:
Basis Line: The selected moving average.
Upper Band: Basis + Standard Deviation.
Lower Band: Basis - Standard Deviation.
Additional Bands: Representing ±3 Standard Deviations.
Plots:
Plots the basis, upper, and lower bands.
Fills the area between the bands for visual clarity.
Plots and fills additional bands for ±3 Standard Deviations with lighter colors.
Alerts:
Generates an alert when the price enters the range between the 2nd and 3rd standard deviation bands.
The alert can be used to notify when price volatility increases significantly.
Background Highlighting:
Colors the chart background based on alert conditions:
Green if the price is above the basis line.
Red if the price is below the basis line.
Offset:
Adds an optional horizontal offset to the plots for fine-tuning their alignment.
How It Works
Input Parameters:
The user specifies settings such as moving average type, length, multipliers, and fixed time frame.
Calculations:
The script computes the basis (moving average) and standard deviations on the fixed time frame.
Bands are calculated using the basis and multipliers.
Plotting:
The basis line and upper/lower bands are plotted with distinct colors.
Additional 3 StdDev bands are plotted with lighter colors.
Alerts:
An alert condition is created when the price moves between the 2nd and 3rd standard deviation bands.
Visual Enhancements:
Chart background changes color dynamically based on the price’s position relative to the basis line and alert conditions.
Usage
This script is useful for traders who:
Want a detailed visualization of price volatility.
Use Bollinger Bands to identify breakout or mean-reversion trading opportunities.
Need alerts when the price enters specific volatility thresholds.
Crypto Price Volatility Range# Cryptocurrency Price Volatility Range Indicator
This TradingView indicator is a visualization tool for tracking historical volatility across multiple major cryptocurrencies.
## Features
- Real-time volatility tracking for 14 major cryptocurrencies
- Customizable period and standard deviation multiplier
- Individual color coding for each currency pair
- Optional labels showing current volatility values in percentage
## Supported Cryptocurrencies
- Bitcoin (BTC)
- Ethereum (ETH)
- Avalanche (AVAX)
- Dogecoin (DOGE)
- Hype (HYPE)
- Ripple (XRP)
- Binance Coin (BNB)
- Cardano (ADA)
- Tron (TRX)
- Chainlink (LINK)
- Shiba Inu (SHIB)
- Toncoin (TON)
- Sui (SUI)
- Stellar (XLM)
## Settings
- **Period**: Timeframe for volatility calculation (default: 20)
- **Standard Deviation Multiplier**: Multiplier for standard deviation (default: 1.0)
- **Show Labels**: Toggle label display on/off
## Calculation Method
The indicator calculates volatility using the following method:
1. Calculate daily logarithmic returns
2. Compute standard deviation over the specified period
3. Annualize (multiply by √252)
4. Convert to percentage (×100)
## Usage
1. Add the indicator to your TradingView chart
2. Adjust parameters as needed
3. Monitor volatility lines for each cryptocurrency
4. Enable labels to see precise current volatility values
## Notes
- This indicator displays in a separate window, not as an overlay
- Volatility values are annualized
- Data for each currency pair is sourced from USD pairs
Adaptive Volatility-Scaled Oscillator [AVSO] (Zeiierman)█ Overview
The Adaptive Volatility-Scaled Oscillator (AVSO) is a dynamic trading indicator that measures and visualizes volatility-adjusted market behavior. By scaling various metrics (such as volume, price changes, standard deviation, ATR, and Yang-Zhang volatility) and applying adaptive smoothing, AVSO helps traders identify market conditions where volatility deviates significantly from the norm.
This indicator uses standardized scaling (Z-Score logic) to highlight periods of abnormally high or low volatility relative to recent history. With gradient coloring and clear volatility zones, AVSO provides a visually intuitive way to analyze market volatility and adapt trading strategies accordingly.
█ How It Works
⚪ Scaling Metrics: The indicator scales user-selected metrics (e.g., volume, ATR, standard deviation) relative to the market and price, providing a standardized volatility measure.
⚪ Z-Score Standardization: The scaled metric is normalized using a Z-Score to measure how far current volatility deviates from its recent mean.
Positive Z-Score: Above-average volatility.
Negative Z-Score: Below-average volatility.
⚪ Adaptive Smoothing: An Adaptive EMA smooths the Z-Score, dynamically adjusting its length based on the strength of the volatility. Stronger deviations result in shorter smoothing, increasing responsiveness.
█ Unique Feature: Yang-Zhang Volatility
The Yang-Zhang volatility estimator sets this indicator apart by providing a more robust and accurate measure of volatility compared to traditional methods like ATR or standard deviation.
⚪ What Makes Yang-Zhang Volatility Unique?
Comprehensive Calculation: It combines overnight price gaps (log returns from the previous close to the current open) and intraday price movements (high, low, and close).
Accurate for Gapped Markets: Traditional volatility measures can misrepresent price movement when significant gaps occur between sessions. Yang-Zhang accounts for these gaps, making it highly reliable for assets prone to overnight price jumps, such as stocks, cryptocurrencies, and futures.
Adaptable to Real Market Conditions : By including both close-to-open returns and intraday volatility, it provides a balanced and adaptive measure that captures the full volatility picture.
⚪ Why This Matters to Traders
Better Volatility Insights: Yang-Zhang offers a clearer view of true market volatility, especially in markets with price gaps or uneven trading sessions.
Improved Trade Timing: By identifying volatility spikes and calm periods more effectively, traders can time their entries and exits with greater confidence.
█ How to Use
Identify High and Low Volatility
A high Z-Score (>2) indicates significant market volatility. This can signal momentum-driven moves, breakouts, or areas of increased risk.
A low Z-Score (<-2) suggests low volatility or a calm market environment. This often occurs before a potential breakout or reversal.
Trade Signals
High Volatility Zones (background highlight): Monitor for potential breakouts, trend continuations, or reversals.
Low Volatility Zones: Anticipate range-bound conditions or upcoming volatility spikes.
█ Settings
Source: Select the price source for scaling calculations (close, high, low, open).
Metric Measure: Choose the volatility measure:
Volume: Scales raw volume.
Close: Uses closing price changes.
Standard Deviation: Price dispersion.
ATR: Average True Range.
Yang: Yang-Zhang volatility estimate.
Bars to Analyze: Number of historical bars used to calculate the mean and standard deviation of the scaled metric.
ATR / Standard Deviation Period: Lookback period for ATR or Standard Deviation calculation.
Yang Volatility Period: Period for the Yang-Zhang volatility estimator.
Smoothing Period: Base smoothing length for the adaptive smoothing line.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Crypto Market Cap Momentum Analyzer (AiBitcoinTrend)The Crypto Market Cap Momentum Analyzer (AiBitcoinTrend) is a robust tool designed to uncover trading opportunities by blending market cap analysis and momentum dynamics. Inspired by research-backed quantitative strategies, this indicator helps traders identify trend-following and mean-reversion setups in the cryptocurrency market by evaluating recent performance and market cap size.
This indicator classifies cryptocurrencies into market cap quintiles and ranks them based on their 2-week momentum. It then suggests potential trades—whether to go long, anticipate reversals, or simply hold—based on the crypto's market cap group and momentum trends.
👽 How the Indicator Works
👾 Market Cap Classification
The indicator categorizes cryptocurrencies into one of five market cap groups based on user-defined inputs:
Large Cap: Highest market cap tier
Upper Mid Cap: Second highest group
Mid Cap: Middle-tier market caps
Lower Mid Cap: Slightly below the mid-tier
Small Cap: Lowest market cap tier
This classification dynamically adjusts based on the provided market cap data, ensuring that you’re always working with a representative market structure.
👾 Momentum Calculation
By default, the indicator uses a 2-week momentum measure (e.g., a 14-day lookback when set to daily). It compares a cryptocurrency’s current price to its price 14 bars ago, thereby quantifying its short-term performance. Users can adjust the momentum period and rebalance period to capture shorter or longer-term trends depending on their trading style.
👾 Dynamic Ranking and Trade Suggestions
After assigning cryptos to size quintiles, the indicator sorts them by their momentum within each quintile. This two-step process results in:
Long Trade: For smaller market cap groups (Small, Lower Mid, Mid Cap) that have low (bottom-quintile) momentum, anticipating a trend continuation or breakout.
Reversal Trade: For the largest market cap group (Large Cap) that shows low momentum, expecting a mean-reversion back to equilibrium.
Hold: In scenarios where the coin’s momentum doesn’t present a strong contrarian or trend-following signal.
👽 Applications
👾 Trend-Following in Smaller Caps: Identify small or mid-cap cryptos with low momentum that might be poised for a breakout or sustained trend.
👾 Mean-Reversion in Large Caps: Pinpoint large-cap cryptocurrencies experiencing a temporary lull in performance, potentially ripe for a rebound.
👽 Why It Works in Crypto
The cryptocurrency market is heavily driven by retail investor sentiment and volatility. Research shows that:
Small-Cap Cryptos: Tend to experience higher volatility and speculative trends, making them ideal for momentum trades.
Large-Cap Cryptos: Exhibit more predictable behavior, making them suitable for mean-reversion strategies when momentum is low.
This indicator captures these dynamics to give traders a strategic edge in identifying both momentum and reversal opportunities.
👽 Indicator Settings
👾 Rebalance Period: The frequency at which momentum and trade suggestions are recalculated (Daily, Weekly, Monthly).
Shorter Periods (Daily): Fast updates, suitable for short-term trades, but more noise.
Longer Periods (Weekly/Monthly): Smoother signals, ideal for swing trading and more stable trends.
👾 Momentum Period: The lookback period for momentum calculation (default is 14 bars).
Shorter Periods: More responsive but prone to noise.
Longer Periods : Reflects broader trends, reducing sensitivity to short-term fluctuations.
Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
