ATR (Average True Range) mit relative/absolute Zahlen GERMAN:
Schnelle Zusammenfassung:
Dieses Skript basiert auf dem ATR-Indikator und wurde so angepasst, dass sowohl relative (%) als auch absolute Zahlen angezeigt werden. Es bietet eine Darstellung des ATR in absoluten und prozentualen Werten sowie multipliziert mit den Faktoren x2, x2.5 und x3. Diese Darstellung erleichtert die Festlegung von Stop-Kursen, insbesondere für Trailing Stops und Trailing Abstände.
Periode:
Die Periode ist einstellbar und definiert die Länge der Berechnung des ATR (Standardwert: 14).
Glättung: Es stehen verschiedene Methoden zur Auswahl, um die Daten zu glätten (RMA, SMA, EMA, WMA).
Berechnungen:
ATR (Absolute Zahl): Berechnung der durchschnittlichen wahren Reichweite (ATR) unter Verwendung der ausgewählten Glättungsmethode und Periode.
ATR (Prozentualer Wert): Berechnung des ATR als Prozentsatz des aktuellen Schlusskurses.
Multiplikation des ATR: Berechnung des ATR multipliziert mit den Faktoren 2, 2.5 und 3 zur Einschätzung verschiedener Handelsszenarien.
Darstellung:
Absoluter ATR-Wert: Darstellung der absoluten ATR-Werte in Blau.
Relative ATR-Werte (%): Darstellung der prozentualen ATR-Werte, ohne Linie in der Grafik (transparent).
Multiplizierte ATR-Werte (x2, x2.5, x3): Darstellung der multiplizierten ATR-Werte in den Farben Grün (x2), Orange (x2.5) und Lila (x3).
Textbeschriftungen: Für jeden absoluten ATR-Wert und seine Multiplikationen werden Textbeschriftungen links im Chart angezeigt.
Verwendung des Indikators:
Dieser Indikator unterstützt Trader und Analysten dabei, die durchschnittliche wahre Reichweite (ATR) eines Finanzinstruments zu verstehen und zu visualisieren. Die verschiedenen Multiplikationen des ATR ermöglichen es, potenzielle Preisbewegungen zu analysieren und Handelsstrategien zu entwickeln, die auf der Volatilität basieren.
Hinweis:
Dies ist meine persönliche Meinung und Einstellung. Dieses Skript stellt keine Bankberatung oder Anlageempfehlung dar. Die Nutzung erfolgt auf eigenes Risiko und Verantwortung des Nutzers.
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ENGLISH:
Quick Summary:
This script is based on the ATR (Average True Range) indicator and has been modified to display both relative (%) and absolute values. It provides a representation of ATR in absolute and percentage terms, as well as multiplied by factors x2, x2.5, and x3. This visualization aids in setting stop-loss levels, especially for trailing stops and trailing distances.
Period:
The period is adjustable and defines the length of the ATR calculation (default: 14).
Smoothing: Various methods are available to smooth the data (RMA, SMA, EMA, WMA).
Calculations:
ATR (Absolute Value): Computes the Average True Range using the selected smoothing method and period.
ATR (Percentage Value): Calculates the ATR as a percentage of the current closing price.
Multiplication of ATR: Computes the ATR multiplied by factors 2, 2.5, and 3 to assess different trading scenarios.
Visualization:
Absolute ATR Value: Displays the absolute ATR values in blue.
Relative ATR Values (%): Shows the ATR values as percentages, without lines in the chart (transparent).
Multiplied ATR Values (x2, x2.5, x3): Presents the multiplied ATR values in green (x2), orange (x2.5), and purple (x3).
Text Labels: Text labels are shown on the left side of the chart for each absolute ATR value and its multiples.
Use of the Indicator:
This indicator helps traders and analysts understand and visualize the Average True Range (ATR) of a financial instrument. The different multipliers of ATR allow for the analysis of potential price movements and the development of trading strategies based on volatility.
Disclaimer:
This represents my personal opinion and viewpoint. This script does not constitute bank advice or investment recommendations. Use it at your own risk and responsibility.
תנודתיות
ALT - ATR Percent Rank🔵 Description
The "ALT - ATR Percent Rank" indicator is a financial analysis tool designed to assess the volatility of an asset relative to its historical behavior, using the Average True Range (ATR) metric.
🔵 Purpose
The indicator aims to provide traders with insights into how the current volatility of an asset compares to its past levels. By evaluating the Percent Rank of the ATR, traders can determine if the current ATR value is high or low in the context of a specified historical period.
🔵 Functionality
• Asset and Timeframe Flexibility
Selectable Asset: Users can choose to apply the indicator to a different asset than the one currently displayed on the chart. This is particularly useful for comparing the volatility of multiple assets without switching charts.
Customizable Timeframe: The indicator can be set to analyze the ATR on different timeframes, regardless of the chart's current timeframe. This allows for multi-timeframe analysis without changing the view of the current chart.
• ATR Calculation
The Average True Range (ATR) is calculated over a user-defined number of bars (ATR Length). ATR is a commonly used measure of volatility that captures the degree of price movement per bar.
REF: Average True Range (ATR) Calculation
• Percent Rank Analysis
The indicator computes the Percent Rank of the current ATR value based on a specified lookback period (Percent Rank Lookback). This tells users how the current ATR compares to ATR values over the recent past, expressed as a percentile. For example, a Percent Rank of 90% indicates that the current ATR is higher than 90% of its values over the chosen lookback period, suggesting higher volatility.
• Visualization
The result is plotted as a line on a separate panel below the main trading chart, making it easy to view changes in volatility relative to historical levels.
🔵 Use Cases
• Trend Confirmation
Traders might use the indicator to confirm if a price movement is backed by significant volatility changes, which could validate the strength of a trend.
• Risk Management
Understanding when an asset is experiencing unusually high or low volatility could help in adjusting trading strategies, such as altering position sizes or setting stop-loss orders.
• Comparative Analysis
By enabling the analysis of different assets or timeframes, traders can perform comparative volatility studies, which can be essential in portfolio management or when seeking diversification opportunities.
This indicator is a valuable tool for traders who rely on volatility analysis to make informed trading decisions, providing a clear, quantifiable measure of how current market conditions compare to historical data.
Wyckoff Springs [QuantVue]The Wyckoff Springs indicator is designed to identify potential bullish reversal patterns known as "springs" in the Wyckoff Method. A Wyckoff spring occurs when the price temporarily dips below a support level, then quickly rebounds, suggesting a false breakdown and a
potential buying opportunity.
How it works:
Pivot detection:
The indicator identifies pivot lows based on the specified pivot length.
These pivot points are stored and analyzed for potential spring patterns.
Volume and Range Checks:
If volume confirmation is enabled, the indicator checks if the current volume exceeds a threshold based on the average volume over the specified period.
The indicator ensures that the price undercuts the defined trading range before confirming a spring pattern.
Spring Identification
The indicator checks for price conditions indicative of a Wyckoff spring: a temporary dip below a pivot low followed by a close above it. The recovery must take place within 3 bars.
If these conditions are met, a spring label is placed below the bar.
Features:
Pivot Length:
The user can set the pivot length to match any style of trading.
Volume Confirmation:
An optional feature where the user can specify if volume confirmation is required for a spring signal.
Volume threshold can be set to determine what constitutes significant volume compared to the average volume over a specified period. By default it is set to 1.5
How to Trade a Spring:
Give this indicator a BOOST and COMMENT your thoughts below!
We hope you enjoy.
Cheers!
MA MACD BB BackTesterOverview:
This Pine Script™ code provides a comprehensive backtesting tool that combines Moving Average (MA), Moving Average Convergence Divergence (MACD), and Bollinger Bands (BB). It is designed to help traders analyze market trends and make informed trading decisions by testing various strategies over historical data.
Key Features:
1. Customizable Indicators:
Moving Average (MA): Smooths out price data for clearer trend direction.
MACD: Measures trend momentum through MACD Line, Signal Line, and Histogram.
Bollinger Bands (BB): Identifies overbought or oversold conditions with upper and lower bands.
2. Flexible Trading Direction: Choose between long or short positions to adapt to different market conditions.
3. Risk Management: Efficiently allocate your capital with customizable position sizes.
4. Signal Generation:
Buy Signals: Triggered by crossovers for MACD, MA, and BB.
Sell Signals: Triggered by crossunders for MACD, MA, and BB.
5. Automated Trading: Automatically enter and exit trades based on signal conditions and strategy parameters.
How It Works:
1. Indicator Selection: Select your preferred indicator (MA, MACD, BB) and trading direction (Long/Short).
2. Risk Management Configuration: Set the percentage of capital to allocate per position to manage risk effectively.
3.Signal Detection: The algorithm identifies and plots buy/sell signals directly on the chart based on the chosen indicator.
4. Trade Execution: The strategy automatically enters and exits trades based on signal conditions and configured strategy parameters.
Use Cases:
- Backtesting: Evaluate the effectiveness of trading strategies using historical data to understand potential performance.
- Strategy Development: Customize and expand the strategy to incorporate additional indicators or conditions to fit specific trading styles.
ADDONS That Affect Strategy:
1. Indicator Parameters:
Adjustments to the settings of MACD (e.g., fast length, slow length), MA (e.g., length), and BB (e.g., length, multiplier) will directly impact the detection of signals and the strategy's performance.
2. Trading Direction:
Changing the trading direction (Long/Short) will alter the entry and exit conditions based on the detected signals.
3. Risk Management Settings:
Modifying the position size percentage affects capital allocation and overall risk exposure per trade.
ADDONS That Do Not Affect Strategy:
1. Visual Customizations:
Changes to the color, shape, and style of the plotted lines and signals do not impact the core functionality of the strategy but enhance visual clarity.
2. Text and Labels:
Modifying text labels for the signals (such as renaming "Buy MACD" to "MACD Buy Signal") is purely cosmetic and does not influence the strategy’s logic or outcomes.
Notes:
- Customization: The indicator is highly customizable to fit various trading styles and market conditions.
- Risk Management: Adjust position sizes and risk parameters according to your risk tolerance and account size.
- Optimization: Regularly backtest and optimize parameters to adapt to changing market dynamics for better performance.
Getting Started:
-Add the script to your chart.
-Adjust the input parameters to suit your analysis preferences.
-Observe the marked buy and sell signals on your chart to make informed trading decisions.
Quantum Duality Predictive Ranges### Quantum Duality Predictive Ranges v1.0
This Pine Script is designed to help traders predict price ranges and manage risk dynamically using ATR (Average True Range) calculations. It offers customizable settings, visual indicators, and alerts to assist in identifying trading opportunities and managing risk.
#### Key Features
- **Dynamic Risk Management**: Adjusts risk based on signals and cumulative risk.
- **Predictive Ranges**: Calculates predictive ranges based on ATR and user-defined multipliers.
- **Visual Indicators**: Plots lines and labels for easy visualization of trading signals and risk levels.
- **Alerts and Table**: Provides alerts for trading signals and displays a table with relevant trading data.
#### User Inputs
**EA Account Settings**
- **Initial Risk fixed in USD $**: Sets the initial risk amount in USD (default: 18).
- **Signal Multiply Factor for Risk**: Multiplier for signal risk (default: 1.257).
- **Pair Decimals**: Decimal places for pair pricing (default: 2).
**Trade Settings**
- **ATR Length**: Length for ATR calculation (default: 198).
- **ATR Factor**: Multiplier for ATR (default: 6.0).
- **ATR Source**: Source for ATR calculation (default: close).
- **ATR Multiplier**: Multiplier for defining RANGE Top/Bottom Levels (default: 0.45).
- **Inner Range Multiplier**: Multiplier for defining TP1 (default: 2.01).
- **Outer Range Multiplier**: Multiplier for defining TP2 (default: 3.0).
- **Spans Multiplier**: Multiplier for defining SL (default: 0.36).
**Display Options**
- **Display Table**: Option to display a table (default: true).
- **Display Labels for potential Gain and Loss**: Option to display gain/loss labels (default: true).
- **Display Labels for Bar counts since current Range**: Option to display bar counts (default: true).
- **Display Labels for Signals**: Option to display signal labels (default: true).
- **Line Width**: Width of the lines plotted (default: 1).
- **Line Transparency**: Transparency of the lines (default: 10).
- **Fill Transparency**: Transparency of the fill between lines (default: 75).
#### How It Works
1. **Predictive Ranges Calculation**:
- Calculates predictive ranges based on ATR, holds ATR values, and updates average values when price crosses defined levels.
2. **Risk Management and Signal Logic**:
- Counts the number of signals.
- Calculates cumulative and total risk based on signals.
- Resets signals and risk when price crosses predictive ranges.
3. **Entry Points and Potential Gains/Losses**:
- Determines buy and sell entry points.
- Calculates potential gains and losses for both buy and sell signals.
- Resets values when a new average range is established.
4. **Plotting and Alerts**:
- Plots lines for predictive ranges, spans, and stop loss levels.
- Displays labels for signals and potential gains/losses.
- Provides alerts for buy and sell signals with defined take profit and stop loss levels.
5. **Custom Ticker**:
- Renames tickers based on predefined rules (e.g., SPX500USD to SPX500).
#### Usage
1. **Set Up**:
- Adjust the input parameters in the settings menu to match your trading preferences and risk management strategy.
2. **Visualize**:
- View the plotted lines and labels on the chart to identify potential trading signals and manage risk.
3. **Alerts**:
- Enable alerts to receive notifications for buy and sell signals.
4. **Table**:
- Use the table to see a summary of important trading data, such as total risk and target levels.
This script provides a robust framework for managing risk and identifying trading opportunities using predictive ranges based on ATR. Happy trading!
[KVA] KATRThe KATR indicator enhances the traditional ATR by leveraging the most common candle body percentage range, tailoring volatility measurement to specific market contexts. This advanced tool provides more relevant insights tailored to current market conditions.
Key Features:
Configurable ATR Length : Allows users to set the period for the ATR calculation, providing flexibility to adapt to different trading strategies and timeframes.
Multiple Smoothing Options : Offers a choice of RMA, SMA, EMA, and WMA for smoothing the ATR, enabling traders to select the method that best suits their analysis style.
Histogram Visualization for ATR Differences: The histogram visually represents the difference between the ATR and its moving average. This difference, or "dif," is calculated and smoothed, then multiplied by a user-defined factor. The histogram color indicates market conditions:
Light Red: Increasing but below zero, signaling potential weakening.
Light Green: Increasing and above zero, indicating strengthening.
Dark Green: Decreasing but above zero, showing potential weakening.
Dark Red: Decreasing and below zero, indicating strong weakening.
Ideal for Traders:
This indicator is perfect for traders seeking precise, context-sensitive volatility assessments to optimize trade timing and risk management strategies. Integrated seamlessly with other technical indicators, the KATR enhances your trading dashboard by adding depth to volatility analysis.
Detailed Explanation:
ATR Calculation: The ATR is derived by taking the average true range over a specified period, multiplied by the most common body percentage found in historical data.
Smoothing: Users can smooth the ATR using different methods, adding flexibility and customization to suit various trading styles.
Histogram: The histogram's primary function is to visualize the difference between the current ATR and its smoothed average. This provides clear, visual signals for potential volatility expansions or contractions, aiding in better decision-making.
Whether you're a day trader or a long-term investor, the KATR helps you stay ahead of market trends with reliable and easy-to-interpret insights. Elevate your trading strategy with the KATR's innovative approach to volatility measurement.
Bollinger Bands Fast Trend Indicator [DCD]Description:
The Bollinger Bands Fast Trend Detector indicator is an advanced tool designed to provide traders with more precise trend detection and clearer entry and exit signals. This script builds upon the traditional Bollinger Bands indicator by adding customizable standard deviations and incorporating multiple moving averages to enhance the accuracy of the signals.
Main Features:
1. **Customizable Bollinger Bands**:
- Each Bollinger Band has its own standard deviation setting, allowing for more granular control and better trend detection.
- The short Bollinger Band is set to a 10-period SMA for faster trend recognition.
2. **Multiple Moving Averages**:
- The indicator includes several types of moving averages (SMA, EMA, LSMA, HMA, WMA) applied to the Bollinger Trend value, giving traders flexibility to choose the best fit for their strategy.
3. **Crossover and Crossdown Detection**:
- The script identifies crossover and crossdown points between the Bollinger Trend value and the selected moving average, marking potential buy and sell signals with green and red circles, respectively.
4. **Color-Coded Histogram**:
- The histogram bars are color-coded to indicate the strength and direction of the trend, making it easy to visualize market conditions at a glance.
Instructions:
1. **Adding the Script to Your Chart**:
- Open your TradingView chart and add the Bollinger Bands Fast Trend Detector indicator.
2. **Adjusting Parameters**:
- Customize the Bollinger Bands and moving average settings according to your trading preferences:
- `Short BB Length` (default: 10): Adjusts the length of the short Bollinger Band.
- `Long BB Length` (default: 50): Adjusts the length of the long Bollinger Band.
- `StdDev` (for both bands): Sets the standard deviation multiplier.
- `Moving Average Type`: Choose between SMA, EMA, LSMA, HMA, and WMA.
- `Moving Average Length` (default: 14): Sets the length of the moving average.
3. **Interpreting the Output**:
- Observe the BBTrend and moving average plots on your chart.
- Look for green circles indicating crossover points (potential buy signals) and red circles indicating crossdown points (potential sell signals).
- Use the color-coded histogram bars to assess the strength and direction of the trend.
Configurable Parameters:
- `shortLengthInput` (default: 10): Length of the short Bollinger Band.
- `longLengthInput` (default: 50): Length of the long Bollinger Band.
- `shortDevMultInput` (default: 1.0): Standard deviation multiplier for the short Bollinger Band.
- `longDevMultInput` (default: 2.0): Standard deviation multiplier for the long Bollinger Band.
- `maTypeInput` (default: SMA): Type of moving average (options: SMA, EMA, LSMA, HMA, WMA).
- `maLengthInput` (default: 14): Length of the moving average.
Code Explanation:
The script calculates two sets of Bollinger Bands with distinct lengths and standard deviations. The difference between the lower bands and upper bands is normalized by the short middle band to compute the BBTrend value. A selected moving average is then applied to this BBTrend value. The script plots the BBTrend, the moving average, and uses color-coded histogram bars to represent trend strength and direction. It also identifies and marks crossover and crossdown points to provide potential trading signals.
Disclaimer:
This script is for educational purposes only and should not be considered financial advice. Always perform your own analysis before making any trading decisions.
Volatility Volume IndicatorIntroducing the Volatility Volume Indicator (𝓥𝓥𝓘) , a sophisticated tool designed to provide traders and investors with deeper insights into market dynamics by analyzing the interplay between price movements and trading volume. This indicator, built with the latest Pine Script version 5, leverages advanced calculations to deliver a clear, visual representation of market volatility and volume trends. Whether you are a day trader looking for intraday opportunities or a long-term investor seeking to understand market behavior, the 𝓥𝓥𝓘 is an invaluable addition to your trading arsenal.
Explanation of the Logic
The Volatility Volume Indicator (𝓥𝓥𝓘) is constructed on a foundation of key market metrics: high, low, open, and close prices, along with volume data. It begins by breaking down each price bar into its upper, lower, and body components, which are then used to calculate the proportional contributions of these segments to the overall price movement. This analysis allows the indicator to distinguish between different types of price action, whether bullish or bearish.
Volume normalization is a crucial aspect of the 𝓥𝓥𝓘, where the current volume is compared against its exponential moving average to gauge relative volume strength. This normalized volume is then used to compute bullish and bearish volumes separately, providing a granular view of market sentiment. These volumes are smoothed over a specified period to reduce noise and highlight significant trends.
The volatility component of the 𝓥𝓥𝓘 is integrated by analyzing the relationship between price range and volume. The indicator calculates the range of each price bar (the difference between the high and low) and breaks it down into upper and lower segments relative to the open and close prices. By examining how much of the total price movement is due to the body of the candlestick versus the wicks, the 𝓥𝓥𝓘 can determine periods of high and low volatility. When combined with volume data, this approach provides a comprehensive view of how volatile price movements are supported or contradicted by trading volume.
The final output is a visual plot that color-codes the combined volume difference, offering clear signals based on the balance between bullish and bearish pressures. The bar coloring adds another layer of interpretation:
Bright Blue: Indicates strong volume and volatility to the upside, signaling robust bullish activity.
Dark Blue: Indicates weak volume and volatility to the upside, suggesting less intense bullish movements.
Dark Red: Indicates weak volume and volatility to the downside, pointing to subdued bearish activity.
Bright Red: Indicates strong volume and volatility to the downside, highlighting significant bearish pressure.
Use Cases for This Indicator in Trading and Investing
The 𝓥𝓥𝓘 is versatile and can be applied in various trading and investing scenarios. Day traders can use it to identify periods of high volatility and volume, which are often associated with potential breakout or breakdown points. By understanding the underlying volume dynamics, traders can make more informed decisions about entry and exit points, improving their chances of capturing significant price moves.
For swing traders and long-term investors, the 𝓥𝓥𝓘 helps in spotting sustained trends and potential reversals. By analyzing the cumulative bullish and bearish volumes, investors can better gauge market sentiment and the strength of ongoing trends. This can aid in confirming the viability of trend-following strategies or in identifying overbought or oversold conditions, thus enhancing risk management and strategic planning.
Main flaw :
Why Do I Keep It Closed Source
The decision to keep the Volatility Volume Indicator (𝓥𝓥𝓘) closed source stems from several important considerations. First and foremost, this indicator encapsulates a unique methodology and proprietary calculations that differentiate it from other tools available in the market. By keeping the source code private, we protect the intellectual property and maintain the competitive edge that this sophisticated analysis provides.
Additionally, a closed-source approach ensures that the integrity of the indicator remains intact. Users can trust that the 𝓥𝓥𝓘 they are using is free from unauthorized modifications or errors introduced by third-party alterations. This guarantees consistent performance and reliability, which is critical for making accurate trading and investing decisions. Finally, keeping the code closed source allows for controlled updates and enhancements, ensuring that users always have access to the most refined and effective version of the indicator.
Dynamic Bollinger Bands with Momentum and Volume (DBBMV)Overview
The Dynamic Bollinger Bands with Momentum and Volume (DBBMV) indicator enhances the traditional Bollinger Bands by dynamically adjusting their width and position based on momentum and volume. This provides a more responsive and context-aware indication of price volatility and potential reversals.
Key Features
Momentum Adjusted Bands: Adjusts the bands' width based on the momentum indicator, reflecting the rate of change in price.
Volume Weighted Bands: Further adjusts the bands based on trading volume to reflect market activity and price volatility.
Signal Alerts: Provides buy and sell signals based on price action relative to the dynamic bands, helping traders identify entry and exit points.
Customizable Parameters: Allows users to adjust the lookback period, momentum sensitivity, and volume weighting for personalized analysis.
How It Works
The DBBMV indicator starts with the traditional Bollinger Bands, which are calculated using a moving average and standard deviation of the selected price source. The width of these bands is then adjusted based on the momentum of the price, making them more sensitive to price changes. Further adjustments are made based on trading volume, which ensures that the bands accurately reflect current market conditions. This results in a set of dynamic Bollinger Bands that provide more nuanced insights into price volatility and potential reversals.
Usage Instructions
Identify Volatile Periods: Use the dynamically adjusted bands to identify periods of high and low volatility in the market.
Spot Reversals: Look for buy signals when the price crosses above the lower band and sell signals when the price crosses below the upper band.
Adjust Sensitivity: Customize the lookback period, momentum sensitivity, and volume weighting to fine-tune the indicator to your specific trading strategy and market conditions.
Enhance Analysis: Combine the DBBMV indicator with other technical analysis tools for a more comprehensive market analysis.
Volume Confirmation: Use the volume-weighted adjustments to confirm the strength of price movements and potential breakouts.
The Dynamic Bollinger Bands with Momentum and Volume (DBBMV) indicator provides traders with a powerful tool to understand market dynamics better and make informed trading decisions based on adjusted volatility and market activity.
Average Session Range [QuantVue]The Average Session Range or ASR is a tool designed to find the average range of a user defined session over a user defined lookback period.
Not only is this indicator is useful for understanding volatility and price movement tendencies within sessions, but it also plots dynamic support and resistance levels based on the ASR.
The average session range is calculated over a specific period (default 14 sessions) by averaging the range (high - low) for each session.
Knowing what the ASR is allows the user to determine if current price action is normal or abnormal.
When a new session begins, potential support and resistance levels are calculated by breaking the ASR into quartiles which are then added and subtracted from the sessions opening price.
The indicator also shows an ASR label so traders can know what the ASR is in terms of dollars.
Session Time Configuration:
The indicator allows users to define the session time, with default timing set from 13:00 to 22:00.
ASR Calculation:
The ASR is calculated over a specified period (default 14 sessions) by averaging the range (high - low) of each session.
Various levels based on the ASR are computed: 0.25 ASR, 0.5 ASR, 0.75 ASR, 1 ASR, 1.25 ASR, 1.5 ASR, 1.75 ASR, and 2 ASR.
Visual Representation:
The indicator plots lines on the chart representing different ASR levels.
Customize the visibility, color, width, and style (Solid, Dashed, Dotted) of these lines for better visualization.
Labels for these lines can also be displayed, with customizable positions and text properties.
Give this indicator a BOOST and COMMENT your thoughts!
We hope you enjoy.
Cheers!
Returns Since PivotReturns Since Pivot (RSP) helps to analyze the trend and seasonality.
This indicator draws 2 separate lines
green - upward movement
red - downward movement
Unlike other trend indicators, it's important that even while uptrend you can still see the power of downward moves that occurred during move up.
Hints and setups:
1) Helps to identify clear up trend from the noisy/mixed one: clearly growing non-interrupted green line, without significant negative red lines.
2) Helps to see potential trend reversal: for example, clear strong green line was interrupted for a brief price drop. Then the uptrend continues, you see clear green line again. But -- it's visible that new green line is way less strong, so the price might have exhausted.
3) While trading on 5 min chart, you can set RSP to 1 hour, or 4 hours to get a clear picture of price action on macro timeframe.
4) Indicator is normalized, so you can compare different coins. For example, after the big drop and rebound, you can use RSP to understand which coin had more powerful rebound, thus potentially will be a best gainer in case if the market continues go up.
MACD BB v2.00 Indicator CryptoPotato748The MACD BB v2.00 CryptoPotato748 is a custom technical analysis indicator for TradingView that combines the Moving Average Convergence Divergence (MACD) with Bollinger Bands to provide a powerful tool for identifying trend strength and potential trading signals. This indicator is designed to automatically adapt its parameters based on the selected time frame, making it versatile and suitable for various trading strategies and time horizons.
Features
MACD Calculation:
The MACD line is calculated using the difference between the 12-period and 26-period Exponential Moving Averages (EMAs).
The Signal line is the 9-period EMA of the MACD line.
These parameters automatically adjust based on the selected time frame to optimize performance.
Bollinger Bands:
Bollinger Bands are calculated based on the MACD line to identify overbought and oversold conditions.
The bands consist of a 20-period Simple Moving Average (SMA) of the MACD line, with upper and lower bands set 2 standard deviations away.
These parameters also adjust based on the selected time frame for better alignment with market conditions.
Adaptive Time Frames:
The indicator automatically adjusts its MACD and Bollinger Bands parameters based on the selected chart time frame, including 1 minute, 3 minutes, 5 minutes, 15 minutes, 30 minutes, 1 hour, 2 hours, 4 hours, 12 hours, 1 day, 3 days, 1 week, and 1 month.
This ensures the indicator remains effective across various time frames without manual reconfiguration.
Visual Elements:
The upper and lower Bollinger Bands are plotted in gray, with a blue fill between them for easy visualization.
The MACD line is plotted with circle markers, colored lime when above the upper band and red when below the lower band.
A zero line is plotted in orange for reference.
Bar colors change to yellow when the MACD line is above the upper band (indicating a potential buy signal) and aqua when below the lower band (indicating a potential sell signal).
How to Use
Adding to Chart:
Copy and paste the script into the Pine Editor on TradingView.
Click "Add to Chart" to see the indicator in action.
Interpreting Signals:
MACD Above Upper Band (Lime): Indicates strong bullish momentum, potential buy signal.
MACD Below Lower Band (Red): Indicates strong bearish momentum, potential sell signal.
Yellow Bars: Suggest a potential buy condition.
Aqua Bars: Suggest a potential sell condition.
Adaptive Parameters:
The indicator automatically adjusts its parameters based on the selected time frame, ensuring optimal performance across different trading environments.
Sharpe and Sortino Ratios█ OVERVIEW
This indicator calculates the Sharpe and Sortino ratios using a chart symbol's periodic price returns, offering insights into the symbol's risk-adjusted performance. It features the option to calculate these ratios by comparing the periodic returns to a fixed annual rate of return or the returns from another selected symbol's context.
█ CONCEPTS
Returns, risk, and volatility
The return on an investment is the relative gain or loss over a period, often expressed as a percentage. Investment returns can originate from several sources, including capital gains, dividends, and interest income. Many investors seek the highest returns possible in the quest for profit. However, prudent investing and trading entails evaluating such returns against the associated risks (i.e., the uncertainty of returns and the potential for financial losses) for a clearer perspective on overall performance and sustainability.
The profitability of an investment typically comes at the cost of enduring market swings, noise, and general uncertainty. To navigate these turbulent waters, investors and portfolio managers often utilize volatility , a measure of the statistical dispersion of historical returns, as a foundational element in their risk assessments because it provides a tangible way to gauge the uncertainty in returns. High volatility suggests increased uncertainty and, consequently, higher risk, whereas low volatility suggests more stable returns with minimal fluctuations, implying lower risk. These concepts are integral components in several risk-adjusted performance metrics, including the Sharpe and Sortino ratios calculated by this indicator.
Risk-free rate
The risk-free rate represents the rate of return on a hypothetical investment carrying no risk of financial loss. This theoretical rate provides a benchmark for comparing the returns on a risky investment and evaluating whether its excess returns justify the risks. If an investment's returns are at or below the theoretical risk-free rate or the risk premium is below a desired amount, it may suggest that the returns do not compensate for the extra risk, which might be a call to reassess the investment.
Since the risk-free rate is a theoretical concept, investors often utilize proxies for the rate in practice, such as Treasury bills and other government bonds. Conventionally, analysts consider such instruments "risk-free" for a domestic holder, as they are a form of government obligation with a low perceived likelihood of default.
The average yield on short-term Treasury bills, influenced by economic conditions, monetary policies, and inflation expectations, has historically hovered around 2-3% over the long term. This range also aligns with central banks' inflation targets. As such, one may interpret a value within this range as a minimum proxy for the risk-free rate, as it may correspond to the minimum rate required to maintain purchasing power over time. This indicator uses a default value of 2% as the risk-free rate in its Sharpe and Sortino ratio calculations. Users can adjust this value from the "Risk-free rate of return" input in the "Settings/Inputs" tab.
Sharpe and Sortino ratios
The Sharpe and Sortino ratios are two of the most widely used metrics that offer insight into an investment's risk-adjusted performance . They provide a standardized framework to compare the effectiveness of investments relative to their perceived risks. These metrics can help investors determine whether the returns justify the risks taken to achieve them, promoting more informed investment decisions.
Both metrics measure risk-adjusted performance similarly. However, they have some differences in their formulas and their interpretation:
1. Sharpe ratio
The Sharpe ratio , developed by Nobel laureate William F. Sharpe, measures the performance of an investment compared to a theoretically risk-free asset, adjusted for the investment risk. The ratio uses the following formula:
Sharpe Ratio = (𝑅𝑎 − 𝑅𝑓) / 𝜎𝑎
Where:
• 𝑅𝑎 = Average return of the investment
• 𝑅𝑓 = Theoretical risk-free rate of return
• 𝜎𝑎 = Standard deviation of the investment's returns (volatility)
A higher Sharpe ratio indicates a more favorable risk-adjusted return, as it signifies that the investment produced higher excess returns per unit of increase in total perceived risk.
2. Sortino ratio
The Sortino ratio is a modified form of the Sharpe ratio that only considers downside volatility , i.e., the volatility of returns below the theoretical risk-free benchmark. Although it shares close similarities with the Sharpe ratio, it can produce very different values, especially when the returns do not have a symmetrical distribution, since it does not penalize upside and downside volatility equally. The ratio uses the following formula:
Sortino Ratio = (𝑅𝑎 − 𝑅𝑓) / 𝜎𝑑
Where:
• 𝑅𝑎 = Average return of the investment
• 𝑅𝑓 = Theoretical risk-free rate of return
• 𝜎𝑑 = Downside deviation (standard deviation of negative excess returns, or downside volatility)
The Sortino ratio offers an alternative perspective on an investment's return-generating efficiency since it does not consider upside volatility in its calculation. A higher Sortino ratio signifies that the investment produced higher excess returns per unit of increase in perceived downside risk.
The risk-free rate (𝑅𝑓) in the numerator of both ratio formulas acts as a baseline for comparing an investment's performance to a theoretical risk-free alternative. By subtracting the risk-free rate from the expected return (𝑅𝑎−𝑅𝑓), the numerator essentially represents the risk premium of the investment.
Comparison with another symbol
In addition to the conventional Sharpe and Sortino ratios, which compare an instrument's returns to a risk-free rate, this indicator can also compare returns to a user-specified benchmark symbol , allowing the calculation of Information ratios .
An Information ratio is a generalized form of the Sharpe ratio that compares an investment's returns to a risky benchmark , such as SPY, rather than a risk-free rate. It measures the investment's active return (the difference between its returns and the benchmark returns) relative to its tracking error (i.e., the volatility of the active return) using the following formula:
𝐼𝑅 = (𝑅𝑝 − 𝑅𝑏) / 𝑇𝐸
Where:
• 𝑅𝑝 = Average return on the portfolio or investment
• 𝑅𝑏 = Average return from the benchmark instrument
• 𝑇𝐸 = Tracking error (volatility of 𝑅𝑝 − 𝑅𝑏)
Comparing returns to a benchmark instrument rather than a theoretical risk-free rate offers unique insights into risk-adjusted performance. Higher Information ratios signify that the investment produced higher active returns per unit of increase in risk relative to the benchmark. Conventional choices for non-risk-free benchmarks include major composite indices like the S&P 500 and DJIA, as the resulting ratios can provide insight into the effectiveness of an investment relative to the broader market.
Users can enable this generalized calculation for both the Sharpe and Sortino ratios by selecting the "Benchmark symbol returns" option from the "Benchmark type" dropdown in the "Settings/Inputs" tab.
It's crucial to note that this indicator compares the charts symbol's rate of change (return) to the rate of change in the benchmark symbol. Consequently, not all symbols available on TradingView are suitable for use with these ratios due to the nature of what their values represent. For instance, using a bond as a benchmark will produce distorted results since each bar's values represent yields rather than prices, meaning it compares the rate of change in the yield. To maintain consistency and relevance in the calculated ratios, ensure the values from the compared symbols strictly represent price information.
█ FEATURES
This indicator provides traders with two widely used metrics for assessing risk-adjusted performance, generalized to allow users to compare the chart symbol's price returns to a fixed risk-free rate or the returns from another risky symbol. Below are the key features of this indicator:
Timeframe selection
The "Returns timeframe" input determines the timeframe of the calculated price returns. Users can select any value greater than or equal to the chart's timeframe. The default timeframe is "1M".
Periodic returns tracking
This indicator compounds and collects requested price returns from the selected timeframe over monthly or daily periods, similar to how the Broker Emulator works when calculating strategy performance metrics on trade data. It employs the following logic:
• Track returns over monthly periods if the chart's data spans at least two months.
• Track returns over daily periods if the chart's data spans at least two days but not two months.
• Do not track or collect returns if the data spans less than two days, as the amount of data is insufficient for meaningful ratio calculations.
The indicator uses the returns collected from up to a specified number of periods to calculate the Sharpe and Sortino ratios, depending on the available historical data. It also uses these periodic returns to calculate the average returns it displays in the Data Window.
Users can control the maximum number of periods the indicator analyzes with the "Max no. of periods used" input in the "Settings/Inputs" tab. The default value is 60 periods.
Benchmark specification
The "Benchmark return type" input specifies the benchmark type the indicator compares to the chart symbol's returns in the ratio calculations. It features the following two options:
• "Risk-free rate of return (%)": Compares the price returns to a user-specified annual rate of return representing a theoretical risk-free rate (e.g., 2%).
• "Benchmark symbol return": Compares the price returns to a selected benchmark symbol (e.g., "AMEX:SPY) to calculate Information ratios.
When comparing a chart symbol's returns to a specified benchmark symbol, this indicator aligns the times of data points from the benchmark with the times of data points from the chart's symbol to facilitate a fair comparison between symbols with different active sessions.
Visualization and display
• The indicator displays the periodic returns requested from the specified "Returns timeframe" in a separate pane. The plot includes dynamic colors to signify positive and negative returns.
• When the "Returns timeframe" value represents a higher timeframe, the indicator displays background highlights on the main chart pane to signify when a new value is available and whether the return is positive or negative.
• When the specified benchmark return type is a benchmark symbol, the indicator displays the requested symbol's returns in the separate pane as a gray line for visual comparison.
• Within the separate pane, the indicator displays a single-cell table that shows the base period it uses for periodic returns, the number of periods it uses in the calculation, the timeframe of the requested data, and the calculated Sharpe and Sortino ratios.
• The Data Window displays the chart symbol and benchmark returns, their periodic averages, and the Sharpe and Sortino ratios.
█ FOR Pine Script™ CODERS
• This script utilizes the functions from our RiskMetrics library to determine the size of the periods, calculate and collect periodic returns, and compute the Sharpe and Sortino ratios.
• The `getAlignedPrices()` function in this script requests price data for the chart's symbol and a benchmark symbol with consistent time alignment by utilizing spread symbols , which helps facilitate a fair comparison between different symbol types. Retrieving prices from spreads avoids potential information loss and data misalignment that can otherwise occur when using separate requests from each symbol's context when those symbols have different sessions or data times.
• For consistency, the `getAlignedPrices()` function includes extended hours and dividend adjustment modifiers in its data requests. Additionally, it includes other settings inherited from the chart's context, such as "settlement-as-close" preferences for fair comparison between futures instruments.
• This script uses the `changePercent()` function from our ta library to calculate the percentage changes of the requested data.
• The newly released `force_overlay` parameter in display-related functions allows indicators to display visuals on the main chart and a separate pane simultaneously. We use the parameter in this script's bgcolor() call to display background highlights on the main chart.
Look first. Then leap.
Historical Volatility (adjustable time period)Historical Volatility with Adjustable Time Period and Moving Average
This indicator calculates the historical volatility of an asset within a user-defined date range. Volatility is a measure of the dispersion of returns and is commonly used to assess the risk and potential price fluctuations of an asset.
How It Works
User-Defined Date Range: You can specify the start and end dates to focus on a particular period for volatility calculation. This is useful for analyzing specific historical events or trends within a defined timeframe.
Daily Returns Calculation: The script calculates the daily returns as the percentage change between the current close price and the previous close price. This percentage change is essential for determining the asset's volatility.
Volatility Calculation: The historical volatility is computed as the standard deviation of the daily returns over a specified period. The standard deviation is a statistical measure that quantifies the amount of variation or dispersion in a set of values.
Moving Average: An optional feature allows you to plot a moving average of the volatility. You can customize the type (SMA, EMA, WMA, VWMA) and the period of the moving average, helping to smooth out the volatility data and identify trends.
Indicator Settings
Start Date: Select the beginning date of the period for which you want to calculate volatility.
End Date: Select the end date of the period.
Period: Set the number of bars (days) over which to calculate the average volatility.
Show Moving Average: Toggle to display the moving average of the volatility.
Moving Average Period: Define the length of the moving average.
Moving Average Type: Choose the type of moving average: Simple (SMA), Exponential (EMA), Weighted (WMA), or Volume-Weighted (VWMA).
How to Use
Configure Date Range: Set the start and end dates to focus on the specific historical period you are interested in.
Adjust Period for Volatility Calculation: Select the period over which you want to calculate the average volatility. A shorter period will be more sensitive to recent price changes, while a longer period will provide a more smoothed view.
Enable and Configure Moving Average: If desired, enable the moving average and select the type and period that best fits your analysis style.
Example Use Cases
Market Analysis: Identify periods of high or low volatility to assess market conditions.
Risk Management: Use historical volatility to evaluate the risk associated with a particular asset.
Event Impact: Analyze how specific events within the selected date range affected the asset's volatility.
By providing these functionalities, this indicator is a valuable tool for traders looking to understand and analyze the volatility of assets over custom time periods with the flexibility of adding a moving average for trend analysis.
LBR-S310ROC @shrilssOriginally made by Linda Raschke, The S310ROC Indicator combines the Rate of Change (ROC) indicator with the 3-10 Oscillator (Modified MACD) and plots to capture rapid price movements and gauge market momentum.
- Rate of Change (ROC): This component of the indicator measures the percentage change in price over a specified short interval, which can be set by the user (default is 2 days). It is calculated by subtracting the closing price from 'X' days ago from the current close.
- 3-10 Oscillator (MACD; 3,10,16): This is a specialized version of the Moving Average Convergence Divergence (MACD) but uses simple moving averages instead of exponential. Using a fast moving average of 3 days and a slow moving average of 10 days with a smoothing period of 16.
- ROC Dots: A great feature based on the oscillator's readings. Dots are displayed directly on the oscillator or the price chart to provide visual momentum cues:
- Aqua Dots: Appear when all lines (ROC, MACD, Slowline) are sloping downwards, indicating bearish momentum and potentially signaling a sell opportunity.
- White Dots: Appear when all lines are sloping upwards, suggesting bullish momentum and possibly a buy signal.
Absolute Move BandsOverview:
The Absolute Move Bands indicator calculates the absolute value of the expected return, also known as "momentum" by some traders, and then displays it with standard deviation bands. The indicator also shows a moving average and a Kalman filter of the absolute move. If you take the expected return, you get what many traders commonly call "momentum." Now, if you turn the negative values into positive values by getting the magnitude of the expected return, it shows the "strength or intensity of the expected return." A low value of the absolute value of the expected return shows that the expected return is close to 0, which means that there is no significant trending behavior. The higher the value, the higher the deviation is from the mean, indicating stronger trend moves in the expected return itself. This indicator then gets the standard score of the absolute value of the expected return and then gets the moving average and Kalman Filter.
This indicator is not a directional indicator, but it can help you time moves and determine the "strength" of the expected returns (also known as momentum).
Interpreting the Magnitude:
Low Values: A low absolute value of the expected return indicates that the expected return is close to 0, suggesting no significant trending behavior in the market.
High Values: A high absolute value indicates a strong deviation from the mean, reflecting stronger trend moves in the expected return itself.
Standard Score Calculation:
This indicator computes the standard score (z-score) of the absolute value of the expected return. The value shows how many standard deviations the absolute return is from the mean. This helps in identifying periods of extreme magnitude.
Moving Average and Kalman Filter:
Moving Average: The indicator calculates the moving average of the standard score to smooth out the short-term fluctuations and show the longer-term trends in the absolute returns.
Kalman Filter: Applied to further reduce noise and provide a clearer signal, it enhances the indicator's effectiveness in determining the strength of the expected returns.
Standard Deviation Bands
Purpose: The standard deviation bands help determine if the standard score is at an extreme low or high.
High Standard Score (+2 Standard Deviation Band): Indicates that the absolute value of the expected return is at a high level, suggesting a strong trend. This could mean that the trend is at its peak and might be nearing completion.
Low Standard Score (-2 Standard Deviation Band): Indicates that the absolute value of the expected return is at a low level, suggesting minimal or no trending behavior. This could imply that the expected return is around 0, and a new trend (in any direction) may start soon.
How to interpret and use this indicator
Two ways will be discussed on how you can use this indicator. First of all lets go back over the interpretation of the standard score and bands.
High Standard Score: Indicates that the absolute value is significantly higher than usual, which suggest a strong trend which may be nearing its peak. Some traders who entered a trade at a low standard score value might want to consider taking profits or preparing for a potential reversal.
Low Standard Score: Indicates that the absolute value is significantly low, close to 0, which suggest minimal trending behavior and a new trend or move may soon start.
This indicator shouldn't be used alone; you may need an indicator that shows you the trend with an expected return indicator or a "momentum" indicator, because all this shows you is the strength of the trend or "momentum." So let's say that if you see that the standard score is low and the Kalman filter is increasing, then this shows that a trend may start soon, so you can use the "momentum" indicator and enter with whatever the trend is on.
Another way to use the indicator is to trade extreme occurrences. If on an indicator that shows the expected returns, or "momentum," and its at an extreme standard deviation occurrence level like -2 standard deviation from the mean, and the standard score is at 2 standard deviation (the top band), and the Kalman filter starts decreasing, then the downtrend may be over and you could place a long.
ROC [CHE] with Kernel SelectionIntroduction:
The script titled "ROC with Kernel Selection" utilizes Rate of Change (ROC) to analyze price momentum in financial markets. It incorporates a kernel selection mechanism to smooth ROC values, enhancing clarity in trend identification.
Middle Part:
The script begins by calculating ROC over a specified period using the formula:
roc = (close - close ) / close * 100
The period length determined by the user. The result is plotted alongside a zero line for reference.
The kernel selection aspect allows users to choose from various smoothing techniques:
Linear
Exponential
Epanechnikov
Triangular
Cosine
Each kernel applies a different weighting function to ROC values, influencing the sensitivity and smoothness of the plotted line. Users can customize parameters such as bandwidth and color preferences for up and down movements, facilitating visual interpretation.
The main logic of the script involves iterating through historical data to compute weighted averages of ROC values based on the selected kernel. It adjusts graphical elements dynamically, highlighting changes in momentum direction with color-coded lines and directional symbols (▲ or ▼).
Conclusion:
In conclusion, "ROC with Kernel Selection" offers a flexible toolset for traders and analysts to assess price momentum robustly. By integrating kernel-based smoothing techniques, it enhances the clarity of ROC signals, aiding in the identification of trends and potential reversals in financial markets.
Implied Volatility LevelsOverview:
The Implied Volatility Levels Indicator is a powerful tool designed to visualize different levels of implied volatility on your trading chart. This indicator calculates various implied volatility levels based on historical price data and plots them as dynamic dotted lines, helping traders identify significant market thresholds and potential reversal points.
Features:
Multi-Level Implied Volatility: The indicator calculates and plots multiple levels of implied volatility, including the mean and both positive and negative standard deviation multiples.
Dynamic Updates: The levels update in real-time, reflecting the latest market conditions without cluttering your chart with outdated information.
Customizable Parameters: Users can adjust the lookback period and the standard deviation multiplier to tailor the indicator to their trading strategy.
Visual Clarity: Implied volatility levels are displayed using distinct colors and dotted lines, providing clear visual cues without obstructing the view of price action.
Support for Multiple Levels: Includes additional levels (up to ±5 standard deviations) for in-depth market analysis.
How It Works:
The indicator computes the standard deviation of the closing prices over a user-defined lookback period. It then calculates various implied volatility levels by adding and subtracting multiples of this standard deviation from the mean price. These levels are plotted as dotted lines on the chart, offering traders a clear view of the current market's volatility landscape.
Usage:
Identify Key Levels: Use the plotted lines to spot potential support and resistance levels based on implied volatility.
Analyze Market Volatility: Understand how volatile the market is relative to historical data.
Plan Entry and Exit Points: Make informed trading decisions by observing where the price is in relation to the implied volatility levels.
Parameters:
Lookback Period (Days): The number of days to consider for calculating historical volatility (default is 252 days).
Standard Deviation Multiplier: A multiplier to adjust the distance of the levels from the mean (default is 1.0).
This indicator is ideal for traders looking to incorporate volatility analysis into their technical strategy, providing a robust framework for anticipating market movements and potential reversals.
Dickey-Fuller Test for Mean Reversion and Stationarity **IF YOU NEED EXTRA SPECIAL HELP UNDERSTANDING THIS INDICATOR, GO TO THE BOTTOM OF THE DESCRIPTION FOR AN EVEN SIMPLER DESCRIPTION**
Dickey Fuller Test:
The Dickey-Fuller test is a statistical test used to determine whether a time series is stationary or has a unit root (a characteristic of a time series that makes it non-stationary), indicating that it is non-stationary. Stationarity means that the statistical properties of a time series, such as mean and variance, are constant over time. The test checks to see if the time series is mean-reverting or not. Many traders falsely assume that raw stock prices are mean-reverting when they are not, as evidenced by many different types of statistical models that show how stock prices are almost always positively autocorrelated or statistical tests like this one, which show that stock prices are not stationary.
Note: This indicator uses past results, and the results will always be changing as new data comes in. Just because it's stationary during a rare occurrence doesn't mean it will always be stationary. Especially in price, where this would be a rare occurrence on this test. (The Test Statistic is below the critical value.)
The indicator also shows the option to either choose Raw Price, Simple Returns, or Log Returns for the test.
Raw Prices:
Stock prices are usually non-stationary because they follow some type of random walk, exhibiting positive autocorrelation and trends in the long term.
The Dickey-Fuller test on raw prices will indicate non-stationary most of the time since prices are expected to have a unit root. (If the test statistic is higher than the critical value, it suggests the presence of a unit root, confirming non-stationarity.)
Simple Returns and Log Returns:
Simple and log returns are more stationary than prices, if not completely stationary, because they measure relative changes rather than absolute levels.
This test on simple and log returns may indicate stationary behavior, especially over longer periods. (The test statistic being below the critical value suggests the absence of a unit root, indicating stationarity.)
Null Hypothesis (H0): The time series has a unit root (it is non-stationary).
Alternative Hypothesis (H1): The time series does not have a unit root (it is stationary)
Interpretation: If the test statistic is less than the critical value, we reject the null hypothesis and conclude that the time series is stationary.
Types of Dickey-Fuller Tests:
1. (What this indicator uses) Standard Dickey-Fuller Test:
Tests the null hypothesis that a unit root is present in a simple autoregressive model.
This test is used for simple cases where we just want to check if the series has a consistent statistical property over time without considering any trends or additional complexities.
It examines the relationship between the current value of the series and its previous value to see if the series tends to drift over time or revert to the mean.
2. Augmented Dickey-Fuller (ADF) Test:
Tests for a unit root while accounting for more complex structures like trends and higher-order correlations in the data.
This test is more robust and is used when the time series has trends or other patterns that need to be considered.
It extends the regular test by including additional terms to account for the complexities, and this test may be more reliable than the regular Dickey-Fuller Test.
For things like stock prices, the ADF would be more appropriate because stock prices are almost always trending and positively autocorrelated, while the Dickey-Fuller Test is more appropriate for more simple time series.
Critical Values
This indicator uses the following critical values that are essential for interpreting the Dickey-Fuller test results. The critical values depend on the chosen significance levels:
1% Significance Level: Critical value of -3.43.
5% Significance Level: Critical value of -2.86.
10% Significance Level: Critical value of -2.57.
These critical values are thresholds that help determine whether to reject the null hypothesis of a unit root (non-stationarity). If the test statistic is less than (or more negative than) the critical value, it indicates that the time series is stationary. Conversely, if the test statistic is greater than the critical value, the series is considered non-stationary.
This indicator uses a dotted blue line by default to show the critical value. If the test-static, which is the gray column, goes below the critical value, then the test-static will become yellow, and the test will indicate that the time series is stationary or mean reverting for the current period of time.
What does this mean?
This is the weekly chart of BTCUSD with the Dickey-Fuller Test, with a length of 100 and a critical value of 1%.
So basically, in the long term, mean-reversion strategies that involve raw prices are not a good idea. You don't really need a statistical test either for this; just from seeing the chart itself, you can see that prices in the long term are trending and no mean reversion is present.
For the people who can't understand that the gray column being above the blue dotted line means price doesn't mean revert, here is a more simple description (you know you are):
Average (I have to include the meaning because they may not know what average is): The middle number is when you add up all the numbers and then divide by how many numbers there are. EX: If you have the numbers 2, 4, and 6, you add them up to get 12, and then divide by 3 (because there are 3 numbers), so the average is 4. It tells you what a typical number is in a group of numbers.
This indicator checks if a time series (like stock prices) tends to return to its average value or time.
Raw prices, which is just the regular price chart, are usually not mean-reverting (It's "always" positively autocorrelating but this group of people doesn't like that word). Price follows trends.
Simple returns and log returns are more likely to have periods of mean reversion.
How to use it:
Gray Column (the gray bars) Above the Blue Dotted Line: The price does not mean revert (non-stationary).
Gray Column Below Blue Line: The time series mean reverts (stationary)
So, if the test statistic (gray column) is below the critical value, which is the blue dotted line, then the series is stationary and mean reverting, but if it is above the blue dotted line, then the time series is not stationary or mean reverting, and strategies involving mean reversion will most likely result in a loss given enough occurrences.
[SGM GARCH Volatility]I'm excited to share with you a Pine Script™ that I developed to analyze GARCH (Generalized Autoregressive Conditional Heteroskedasticity) volatility. This script allows you to calculate and plot GARCH volatility on TradingView. Let's see together how it works!
Introduction
Volatility is a key concept in finance that measures the variation in prices of a financial asset. The GARCH model is a statistical method that predicts future volatility based on past volatilities and prediction residuals (errors).
Indicator settings
We define several parameters for our indicator:
length = input.int(20, title="Length")
p = input.int(1, title="Lag order (p)")
q = input.int(1, title="Degree of moving average (q)")
cluster_value = input(0.2,title="cluster value")
length: The period used for the calculations, default 20.
p: The order of the delay for the GARCH model.
q: The degree of the moving average for the GARCH model.
cluster_value: A threshold value used to color the graph.
Calculation of logarithmic returns
We calculate logarithmic returns to capture price changes:
logReturns = math.log(close) - math.log(close )
Initializing arrays
We initialize arrays to store residuals and volatilities:
var float residuals = array.new_float(length, 0)
var float volatilities = array.new_float(length, 0)
We add the new logarithmic returns to the tables and keep their size constant:
array.unshift(residuals, logReturns)
if (array.size(residuals) > length)
array.pop(residuals)
We then calculate the mean and variance of the residuals:
meanResidual = array.avg(residuals)
varianceResidual = array.stdev(residuals, meanResidual)
volatility = math.sqrt(varianceResidual)
We update the volatility table with the new value:
array.unshift(volatilities, volatility)
if (array.size(volatilities) > length)
array.pop(volatilities)
GARCH volatility is calculated from accumulated data:
var float garchVolatility = na
if (array.size(volatilities) >= length and array.size(residuals) >= length)
alpha = 0.1 // Alpha coefficient
beta = 0.85 // Beta coefficient
omega = 0.01 // Omega constant
sumVolatility = 0.0
for i = 0 to p-1
sumVolatility := sumVolatility + beta * math.pow(array.get(volatilities, i), 2)
sumResiduals = 0.0
for j = 0 to q-1
sumResiduals := sumResiduals + alpha * math.pow(array.get(residuals, j), 2)
garchVolatility := math.sqrt(omega + sumVolatility + sumResiduals)
Plot GARCH volatility
We finally plot the GARCH volatility on the chart and add horizontal lines for easier visual analysis:
plt = plot(garchVolatility, title="GARCH Volatility", color=color.rgb(33, 149, 243, 100))
h1 = hline(0.1)
h2 = plot(cluster_value)
h3 = hline(0.3)
colorGarch = garchVolatility > cluster_value ? color.red: color.green
fill(plt, h2, color = colorGarch)
colorGarch: Determines the fill color based on the comparison between garchVolatility and cluster_value.
Using the script in your trading
Incorporating this Pine Script™ into your trading strategy can provide you with a better understanding of market volatility and help you make more informed decisions. Here are some ways to use this script:
Identification of periods of high volatility:
When the GARCH volatility is greater than the cluster value (cluster_value), it indicates a period of high volatility. Traders can use this information to avoid taking large positions or to adjust their risk management strategies.
Anticipation of price movements:
An increase in volatility can often precede significant price movements. By monitoring GARCH volatility spikes, traders can prepare for potential market reversals or accelerations.
Optimization of entry and exit points:
By using GARCH volatility, traders can better identify favorable times to enter or exit a position. For example, entering a position when volatility begins to decrease after a peak can be an effective strategy.
Adjustment of stops and objectives:
Since volatility is an indicator of the magnitude of price fluctuations, traders can adjust their stop-loss and take-profit orders accordingly. Periods of high volatility may require wider stops to avoid being exited from a position prematurely.
That's it for the detailed explanation of this Pine Script™ script. Don’t hesitate to use it, adapt it to your needs and share your feedback! Happy analysis and trading everyone!
DeltaDetector PINESCRIPTLABSDescription:
This technical indicator, DeltaDetector PINESCRIPTLABS, is designed to identify significant changes in the price of an asset relative to the previous close. Users can customize the percentage change they want to monitor.
Usage Instructions:
Adjust the desired percentage change using the "Price Change Value (%)" user input.
Observe the green diamonds to identify significant price increases above the specified percentage.
Observe the red diamonds to identify significant price decreases below the specified percentage.
"In the following image, we observe a 4-hour timeframe for EURUSD, where we set a candle change percentage of 0.45%. We can see how the price reacts afterwards to the size of these candles."
"In the pair BTCUSDT.P, we designated a single candle change percentage of 3%, and observed how the price reacted after that candle."
This allows you to easily identify significant price movements within the range specified by the percentage change you have set.
Español:
Descripción:
Este indicador técnico, DeltaDetector PINESCRIPTLABS, está diseñado para identificar cambios significativos en el precio de un activo en relación con el cierre anterior. Los usuarios pueden personalizar el porcentaje de cambio que desean monitorear.
Instrucciones de uso:
Ajuste el porcentaje de cambio deseado utilizando la entrada de usuario "Price Change Value (%)".
Observe los diamantes verdes para identificar aumentos significativos en el precio por encima del porcentaje especificado.
Observe los diamantes rojos para identificar disminuciones significativas en el precio por debajo del porcentaje especificado.
"En la siguiente imagen, observamos un marco de tiempo de 4 horas para EURUSD, donde establecimos un porcentaje de cambio de vela del 0,45%. Podemos ver cómo reacciona el precio después al tamaño de estas velas."
"En el par BTCUSDT.P, designamos un porcentaje de cambio de vela único del 3%, y observamos cómo reaccionó el precio después de esa vela."
Esto te permite identificar fácilmente movimientos significativos en el precio dentro del rango especificado por el porcentaje de cambio que has establecido.
VIX Percentile Rank HistogramVIX Percentile Rank Histogram
The VIX Percentile Rank Histogram provides a visual representation of the CBOE Volatility Index (VIX) percentile rank over a customizable lookback period, helping traders gauge market sentiment and make informed trading decisions.
Overview:
This indicator calculates the percentile rank of the VIX over a specified lookback period and displays it as a histogram. The histogram helps traders understand whether the current VIX level is relatively high or low compared to its recent history. This information is particularly useful for timing entries and exits in the S&P 500 or related ETFs and Mega Caps.
How It Works:
VIX Data Integration: The script fetches daily VIX close prices, regardless of the chart you are viewing, to analyze market volatility.
Percentile Rank Calculation: The indicator calculates the rank percentile of the VIX over the chosen lookback period.
Histogram Visualization: The histogram plots the difference between the flipped VIX percentile rank and 50, showing green bars for ranks below 50 (indicating lower market volatility) and red bars for ranks above 50 (indicating higher market volatility).
Usage:
This indicator is most effective when trading the S&P 500 (SPX, SPY, ES1!) or ETFs and Mega Caps that closely follow the S&P 500. It provides insight into market sentiment, helping traders make more informed decisions.
Timing Entries and Exits: Green histogram readings suggest it's a good time to enter or hold long positions, while red readings suggest considering exits or short positions.
Market Sentiment: A high VIX percentile rank (red bars) indicates market fear and uncertainty, while a low percentile rank (green bars) suggests investor confidence and reduced volatility.
Key Features:
Customizable Lookback Period: The default lookback period is set to 20 days, but can be adjusted based on the trader's average trade duration. For example, if your trades typically last 20 days, a 20-day lookback period helps contextualize the VIX level relative to its recent history.
Histogram Visualization: The histogram provides a clear visual representation of market volatility.
Green Bars: Indicate a lower-than-median VIX percentile rank, suggesting reduced market volatility.
Red Bars: Indicate a higher-than-median VIX percentile rank, suggesting increased market volatility.
Threshold Line: A dashed gray line at the 0 level serves as a visual reference for the median VIX rank.
Important Note:
This indicator always shows readings from the VIX, regardless of the chart you are viewing. For example, if you are looking at Natural Gas futures, this indicator will provide no relevant data. It works best when trading the S&P 500 or related ETFs and Mega Caps.
Supertrend + BB + Consecutive Candles + QQE + EMA [Pineify]Overview
This indicator, developed by Pineify, is a comprehensive tool designed to assist traders in making informed decisions by combining multiple technical analysis methods. It integrates Supertrend, Bollinger Bands (BB), Consecutive Candles, Quantitative Qualitative Estimation (QQE), and Exponential Moving Averages (EMA) into a single, cohesive script. This multi-faceted approach allows traders to analyze market trends, volatility, and potential buy/sell signals with greater accuracy.
Key Features
1. Supertrend: Utilizes the Supertrend indicator to identify the prevailing market trend. It provides clear buy and sell signals based on the direction of the trend.
2. Bollinger Bands (BB): Measures market volatility and identifies overbought or oversold conditions. The script calculates the middle, upper, and lower bands, along with the Bollinger Band Width (BBW) and Bollinger Band %B (BBR).
3. Consecutive Candles: Detects sequences of consecutive bullish or bearish candles, providing signals when a specified number of consecutive candles are detected.
4. Quantitative Qualitative Estimation (QQE): Combines the Relative Strength Index (RSI) with a smoothing factor to generate buy and sell signals based on the QQE methodology.
5. Exponential Moving Averages (EMA): Includes both fast and slow EMAs to identify potential crossovers, which are used as buy and sell signals.
How It Works
- Supertrend: The Supertrend indicator is calculated using a factor and ATR length. It plots the trend direction and generates buy/sell signals when the trend changes.
- Bollinger Bands: The BB indicator calculates the middle band as a Simple Moving Average (SMA) of the closing prices. The upper and lower bands are derived by adding and subtracting a multiple of the standard deviation from the middle band.
- Consecutive Candles: This feature counts the number of consecutive candles that close higher or lower than the previous candle. When the count reaches a specified threshold, it generates a buy or sell signal.
- QQE: The QQE indicator smooths the RSI values and calculates the QQE Fast and QQE Slow lines. Buy and sell signals are generated based on the crossover of these lines.
- EMA: The script calculates fast and slow EMAs and generates buy/sell signals based on their crossovers.
How to Use
1. Inputs: Customize the indicator settings through the input parameters:
- Supertrend Factor and ATR Length
- BB Length
- Consecutive Candles Counting
- QQE RSI Length
- Fast and Slow EMA Lengths
- Enable/Disable Alerts for various signals
2. Alerts: Set up alerts for Supertrend, Consecutive Candles, and EMA crossovers. Alerts can be enabled or disabled based on user preference.
3. Visualization: The indicator plots the Supertrend, Bollinger Bands, and EMA lines on the chart. It also marks buy and sell signals with arrows and labels for easy identification.
Concepts Underlying Calculations
- Supertrend: Based on the Average True Range (ATR) to determine the trend direction and potential reversal points.
- Bollinger Bands: Utilizes standard deviation to measure market volatility and identify overbought/oversold conditions.
- Consecutive Candles: A method to detect momentum by counting consecutive bullish or bearish candles.
- QQE: Enhances the traditional RSI by smoothing it and using a dynamic threshold to generate signals.
- EMA: A widely used moving average that gives more weight to recent prices, making it responsive to market changes.
This indicator is a powerful tool for traders looking to combine multiple technical analysis methods into a single, easy-to-use script. By integrating these diverse techniques, it provides a comprehensive view of market conditions and potential trading opportunities.
