EMA GridThe EMA Grid indicator is a powerful tool that calculates the overall market sentiment by comparing the order of 20 different Exponential Moving Averages (EMAs) over various lengths. The indicator assigns a rating based on how well-ordered the EMAs are relative to each other, representing the strength and direction of the market trend. It also smooths out the macro movements using cumulative calculations and visually represents the market sentiment through color-coded bands.
EMA Calculation:
The indicator uses a series of EMAs with different lengths, starting from 5 and going up to 100. Each EMA is calculated either using the exponential moving averages.
The EMAs form the grid that the indicator uses to measure the order and distance between them.
Rating Calculation:
The indicator computes the relative distance between consecutive EMAs and sums these differences.
The cumulative sum is further smoothed using multiple EMAs with different lengths (from 3 to 21). This smooths out short-term fluctuations and helps identify broader trends.
Market Sentiment Rating:
The overall sentiment is calculated by comparing the values of these smoothing EMAs. If the shorter-term EMA is above the longer-term EMA, it contributes positively to the sentiment; otherwise, it contributes negatively.
The final rating is a normalized value based on the relationship between these EMAs, producing a sentiment score between 1 (bullish) and -1 (bearish).
Color Coding and Bands:
The indicator uses the sentiment rating to color the space between the 100 EMA and 200 EMA, representing the strength of the trend.
If the sentiment is bullish (rating > 0), the band is shaded green. If the sentiment is bearish (rating < 0), the band is shaded red.
The intensity of the color is based on the strength of the sentiment, with stronger trends resulting in more saturated colors.
Utility for Traders:
The EMA Grid is ideal for traders looking to gauge the broader market trend by analyzing the structure and alignment of multiple EMAs. The color-coded band between the 100 and 200 EMAs provides an at-a-glance view of market momentum, helping traders make informed decisions based on the trend's strength and direction.
This indicator can be used to identify bullish or bearish conditions and offers a smoothed perspective on market trends, reducing noise and highlighting significant trend shifts.
المؤشرات والاستراتيجيات
3-Bar (Outside Bar) Scanner with Table Display# 3-Bar (Outside Bar) Scanner with Table Display
## Overview
The **3-Bar (Outside Bar) Scanner with Table Display** is a custom TradingView indicator designed for traders who utilize **The Strat** methodology. This indicator scans for **3-bar (Outside Bar)** patterns across multiple symbols and displays the results in a convenient table format directly on your chart.
## Purpose
- **Efficient Multi-Symbol Scanning**: Monitor up to four symbols simultaneously for 3-bar patterns without the need to switch between charts.
- **Real-Time Updates**: The table dynamically updates with new price data, providing immediate insights into potential trading opportunities.
- **Visual Clarity**: Displays whether a 3-bar is bullish ("3 Up") or bearish ("3 Down"), helping you quickly interpret market sentiment.
## How It Works
- **Data Retrieval**: The indicator uses `request.security()` to fetch high, low, open, and close prices for the specified symbols and timeframe.
- **3-Bar Detection**:
- **Outside Bar Criteria**: Checks if the current candle's high is higher than the previous candle's high and the current low is lower than the previous low.
- **Direction Determination**:
- **"3 Up"**: If the candle closes higher than it opens (bullish candle).
- **"3 Down"**: If the candle closes lower than it opens (bearish candle).
- **Table Display**:
- The table shows the **Symbol**, **Timeframe**, and **State** ("3 Up", "3 Down", or blank if no pattern detected).
- Customizable colors and positioning to fit your chart's aesthetics.
## Best Use Cases
- **Rapid Market Analysis**: Ideal for traders needing a quick overview of multiple assets for potential 3-bar setups.
- **Strategic Decision-Making**: Helps identify key reversal or continuation patterns in alignment with **The Strat** principles.
- **Scalable Monitoring**: By utilizing TradingView's multi-chart layouts, you can expand monitoring beyond four symbols.
## Instructions for Use
### Adding the Indicator to Your Chart
1. **Copy the Code**: Use the provided Pine Script code for the indicator.
2. **Create a New Indicator**:
- In TradingView, click on **Pine Editor** at the bottom of the platform.
- Paste the code into the editor.
3. **Save and Add to Chart**:
- Click **Save** and give your indicator a name.
- Click **Add to Chart** to apply it.
### Customizing the Inputs
- **Symbols**:
- **Symbol 1**: Leave blank to use the current chart's symbol or enter a specific symbol (e.g., `AAPL`).
- **Symbol 2 to Symbol 4**: Enter additional symbols or leave them blank.
- **Timeframe**: Select your desired timeframe (e.g., `D` for Daily, `60` for 60-minute).
- **Table Colors**:
- Customize header and data colors for better visibility against your chart background.
### Interpreting the Table
- **Symbol**: Displays the symbol without the exchange prefix for clarity.
- **Timeframe**: Shows the timeframe applied to the analysis.
- **State**:
- **"3 Up"**: A bullish outside bar where the candle closed higher than it opened.
- **"3 Down"**: A bearish outside bar where the candle closed lower than it opened.
- **Blank**: No 3-bar pattern detected on the latest candle.
### Monitoring More Than Four Symbols
- **Multi-Chart Layout**:
- Use TradingView's multi-chart feature to display multiple charts within a single workspace.
- Apply the indicator to each chart. For example:
- **Four-Chart Grid**: Monitor up to 16 symbols by setting up four charts, each with the indicator tracking four symbols.
- **Steps**:
1. Arrange your workspace into a multi-chart layout.
2. Add the indicator to each chart.
3. Input different symbols into the indicator on each chart.
## Example Usage
Suppose you want to monitor the following symbols on a Daily timeframe:
- **Symbol 1**: *(Leave blank to use the current chart's symbol, e.g., `SPY`)*
- **Symbol 2**: `AAPL`
- **Symbol 3**: `TSLA`
- **Symbol 4**: `AMZN`
After adding the indicator and entering these symbols:
- **SPY**: The table shows "3 Up" in the State column, indicating a bullish outside bar.
- **AAPL**: No 3-bar pattern detected; the State column is blank.
- **TSLA**: The table shows "3 Down," indicating a bearish outside bar.
- **AMZN**: The table shows "3 Up," indicating another bullish outside bar.
This setup allows you to quickly assess which symbols are exhibiting significant patterns that may warrant further analysis or action.
## Notes
- **Customization**: Feel free to adjust the table's position and colors to suit your preferences.
- **Limitations**:
- Be aware of TradingView's limitations on `request.security()` calls, which may vary based on your subscription plan.
- The indicator is designed to monitor up to four symbols per instance due to these limitations.
- **Scalability**:
- By using multi-chart layouts, you can effectively monitor more symbols without overloading a single chart.
- This approach allows you to scale up your monitoring capabilities to fit your trading strategy.
## Conclusion
The **3-Bar (Outside Bar) Scanner with Table Display** is a valuable tool for traders who utilize **The Strat** methodology. It streamlines the process of identifying key 3-bar patterns across multiple symbols and timeframes, enhancing your ability to make informed trading decisions quickly.
By integrating this indicator into your trading routine, you can:
- Stay alert to significant market movements.
- Reduce the time spent manually scanning charts.
- Increase efficiency in executing your trading strategy.
---
Feel free to share this indicator with the Strat community. Feedback and suggestions are welcome to further enhance its functionality. Happy trading!
$TUBR: Stop Loss IndicatorATR-Based Stop Loss Indicator for TradingView by The Ultimate Bull Run Community: TUBR
**Overview**
The ATR-Based Stop Loss Indicator is a custom tool designed for traders using TradingView. It helps you determine optimal stop loss levels by leveraging the Average True Range (ATR), a popular measure of market volatility. By adapting to current market conditions, this indicator aims to minimize premature stop-outs and enhance your risk management strategy.
---
**Key Features**
- **Dynamic Stop Loss Levels**: Calculates stop loss prices based on the ATR, providing both long and short stop loss suggestions.
- **Customizable Parameters**: Adjust the ATR period, multiplier, and smoothing method to suit your trading style and the specific instrument you're trading.
- **Visual Aids**: Plots stop loss lines directly on your chart for easy visualization.
- **Alerts and Notifications** (Optional): Set up alerts to notify you when the price approaches or hits your stop loss levels.
---
**Understanding the Indicator**
1. **Average True Range (ATR)**:
- **What It Is**: ATR measures market volatility by calculating the average range between high and low prices over a specified period.
- **Why It's Useful**: A higher ATR indicates higher volatility, which can help you set stop losses that accommodate market fluctuations.
2. **ATR Multiplier**:
- **Purpose**: Determines how far your stop loss is placed from the current price based on the ATR.
- **Example**: An ATR multiplier of 1.5 means the stop loss is set at 1.5 times the ATR away from the current price.
3. **Smoothing Methods**:
- **Options**: Choose from RMA (default), SMA, EMA, WMA, or Hull MA.
- **Effect**: Different smoothing methods can make the ATR more responsive or smoother, affecting where the stop loss is placed.
---
**How the Indicator Works**
- **Long Stop Loss Calculation**:
- **Formula**: `Long Stop Loss = Close Price - (ATR * ATR Multiplier)`
- **Purpose**: For long positions, the stop loss is set below the current price to protect against downside risk.
- **Short Stop Loss Calculation**:
- **Formula**: `Short Stop Loss = Close Price + (ATR * ATR Multiplier)`
- **Purpose**: For short positions, the stop loss is set above the current price to protect against upside risk.
- **Plotting on the Chart**:
- **Green Line**: Represents the suggested stop loss level for long positions.
- **Red Line**: Represents the suggested stop loss level for short positions.
---
**How to Use the Indicator**
1. **Adding the Indicator to Your Chart**:
- **Step 1**: Copy the PineScript code of the indicator.
- **Step 2**: In TradingView, click on **Pine Editor** at the bottom of the platform.
- **Step 3**: Paste the code into the editor and click **Add to Chart**.
- **Step 4**: The indicator will appear on your chart with the default settings.
2. **Adjusting the Settings**:
- **ATR Period**:
- **Definition**: Number of periods over which the ATR is calculated.
- **Adjustment**: Increase for a smoother ATR; decrease for a more responsive ATR.
- **ATR Multiplier**:
- **Definition**: Factor by which the ATR is multiplied to set the stop loss distance.
- **Adjustment**: Increase to widen the stop loss (less likely to be hit); decrease to tighten the stop loss.
- **Smoothing Method**:
- **Options**: RMA, SMA, EMA, WMA, Hull MA.
- **Adjustment**: Experiment to see which method aligns best with your trading strategy.
- **Display Options**:
- **Show Long Stop Loss**: Toggle to display or hide the long stop loss line.
- **Show Short Stop Loss**: Toggle to display or hide the short stop loss line.
3. **Interpreting the Indicator**:
- **Long Positions**:
- **Action**: Set your stop loss at the value indicated by the green line when entering a long trade.
- **Short Positions**:
- **Action**: Set your stop loss at the value indicated by the red line when entering a short trade.
- **Adjusting Stop Losses**:
- **Trailing Stops**: You may choose to adjust your stop loss over time, moving it in the direction of your trade as the ATR-based stop loss levels change.
4. **Implementing in Your Trading Strategy**:
- **Risk Management**:
- **Position Sizing**: Use the stop loss distance to calculate your position size based on your risk tolerance.
- **Consistency**: Apply the same settings consistently to maintain discipline.
- **Combining with Other Indicators**:
- **Enhance Decision-Making**: Use in conjunction with trend indicators, support and resistance levels, or other technical analysis tools.
- **Alerts Setup** (If included in the code):
- **Purpose**: Receive notifications when the price approaches or hits your stop loss level.
- **Configuration**: Set up alerts in TradingView based on the alert conditions defined in the indicator.
---
**Benefits of Using This Indicator**
- **Adaptive Risk Management**: By accounting for current market volatility, the indicator helps prevent setting stop losses that are too tight or too wide.
- **Minimize Premature Stop-Outs**: Reduces the likelihood of being stopped out due to normal price fluctuations.
- **Flexibility**: Customizable settings allow you to tailor the indicator to different trading instruments and timeframes.
- **Visualization**: Clear visual representation of stop loss levels aids in quick decision-making.
---
**Things to Consider**
- **Market Conditions**:
- **High Volatility**: Be cautious as ATR values—and thus stop loss distances—can widen, increasing potential losses.
- **Low Volatility**: Tighter stop losses may increase the chance of being stopped out by minor price movements.
- **Backtesting and Optimization**:
- **Historical Analysis**: Test the indicator on past data to evaluate its effectiveness and adjust settings accordingly.
- **Continuous Improvement**: Regularly reassess and fine-tune the parameters to adapt to changing market conditions.
- **Risk Per Trade**:
- **Alignment with Risk Tolerance**: Ensure the stop loss level keeps potential losses within your acceptable risk per trade (e.g., 1-2% of your trading capital).
- **Emotional Discipline**:
- **Stick to Your Plan**: Avoid making impulsive changes to your stop loss levels based on emotions rather than analysis.
---
**Example Usage Scenario**
1. **Setting Up a Long Trade**:
- **Entry Price**: $100
- **ATR Value**: $2
- **ATR Multiplier**: 1.5
- **Calculated Stop Loss**: $100 - ($2 * 1.5) = $97
- **Action**: Place a stop loss order at $97.
2. **During the Trade**:
- **Price Increases to $105**
- **ATR Remains at $2**
- **New Stop Loss Level**: $105 - ($2 * 1.5) = $102
- **Action**: Move your stop loss up to $102 to lock in profits.
---
**Final Tips**
- **Documentation**: Keep a trading journal to record your trades, stop loss levels, and observations for future reference.
- **Education**: Continuously educate yourself on risk management and technical analysis to enhance your trading skills.
- **Support**: Engage with trading communities or seek professional advice if you're unsure about implementing the indicator effectively.
---
**Conclusion**
The ATR-Based Stop Loss Indicator is a valuable tool for traders looking to enhance their risk management by setting stop losses that adapt to market volatility. By integrating this indicator into your trading routine, you can improve your ability to protect capital and potentially increase profitability. Remember to use it as part of a comprehensive trading strategy, and always adhere to sound risk management principles.
---
**How to Access the Indicator**
To start using the ATR-Based Stop Loss Indicator, follow these steps:
1. **Obtain the Code**: Copy the PineScript code provided for the indicator.
2. **Create a New Indicator in TradingView**:
- Open TradingView and navigate to the **Pine Editor**.
- Paste the code into the editor.
- Click **Save** and give your indicator a name.
3. **Add to Chart**: Click **Add to Chart** to apply the indicator to your current chart.
4. **Customize Settings**: Adjust the input parameters to suit your preferences and start integrating the indicator into your trading strategy.
---
**Disclaimer**
Trading involves significant risk, and it's possible to lose all your capital. The ATR-Based Stop Loss Indicator is a tool to aid in decision-making but does not guarantee profits or prevent losses. Always conduct your own analysis and consider seeking advice from a financial professional before making trading decisions.
3% Above and Below Previous Day Close (Stable)This indictor will mark intraday levels. Levels will be marked by calculating 3% up and 3% down from previous day close.
This indicator calculates 3% levels above and below the previous day's close. These levels can be used to track potential support or resistance levels throughout the trading day.
This script helps plot 3% above and below the previous day's close price. It allows you to toggle historical levels and can be useful for monitoring potential intraday price action around these key levels.
Daksh RSI POINT to ShootHere are the key points and features of the Pine Script provided:
### 1. **Indicator Settings**:
- The indicator is named **"POINT and Shoot"** and is set for non-overlay (`overlay=false`) on the chart.
- `max_bars_back=4000` is defined, indicating the maximum number of bars that the script can reference.
### 2. **Input Parameters**:
- `Src` (Source): The price source, default is `close`.
- `rsilen` (RSI Length): The length for calculating RSI, default is 20.
- `linestylei`: Style for the trend lines (`Solid` or `Dashed`).
- `linewidth`: Width of the plotted lines, between 1 and 4.
- `showbroken`: Option to show broken trend lines.
- `extendlines`: Option to extend trend lines.
- `showpivot`: Show pivot points (highs and lows).
- `showema`: Show a weighted moving average (WMA) line.
- `len`: Length for calculating WMA, default is 9.
### 3. **RSI Calculation**:
- Calculates a custom RSI value using relative moving averages (`ta.rma`), and optionally uses On-Balance Volume (`ta.obv`) if `indi` is set differently.
- Plots RSI values as a green or red line depending on its position relative to the WMA.
### 4. **Pivot Points**:
- Utilizes the `ta.pivothigh` and `ta.pivotlow` functions to detect pivot highs and lows over the defined period.
- Stores up to 10 recent pivot points for highs and lows.
### 5. **Trend Line Drawing**:
- Lines are drawn based on pivot highs and lows.
- Calculates potential trend lines using linear interpolation and validates them by checking if subsequent bars break or respect the trend.
- If the trend is broken, and `showbroken` is enabled, it draws dotted lines to represent these broken trends.
### 6. **Line Management**:
- Initializes multiple lines (`l1` to `l20` and `t1` to `t20`) and uses these lines for drawing uptrend and downtrend lines.
- The maximum number of lines is set to 20 for uptrends and 20 for downtrends, due to a limit on the total number of lines that can be displayed on the chart.
### 7. **Line Style and Color**:
- Defines different colors for uptrend lines (`ulcolor = color.red`) and downtrend lines (`dlcolor = color.blue`).
- Line styles are determined by user input (`linestyle`) and use either solid or dashed patterns.
- Broken lines use a dotted style to indicate invalidated trends.
### 8. **Pivot Point Plotting**:
- Plots labels "H" and "L" for pivot highs and lows, respectively, to visually indicate turning points on the chart.
### 9. **Utility Functions**:
- Uses helper functions to get the values and positions of the last 10 pivot points, such as `getloval`, `getlopos`, `gethival`, and `gethipos`.
- The script uses custom logic for line placement based on whether the pivots are lower lows or higher highs, with lines adjusted dynamically based on price movement.
### 10. **Plotting and Visuals**:
- The main RSI line is plotted using a color gradient based on its position relative to the WMA.
- Horizontal lines (`hline1` and `hline2`) are used for visual reference at RSI levels of 60 and 40.
- Filled regions between these horizontal lines provide visual cues for potential overbought or oversold zones.
These are the main highlights of the script, which focuses on trend detection, visualization of pivot points, and dynamic line plotting based on price action.
ADX Trend Strength Analyzer█ OVERVIEW
This script implements the Average Directional Index (ADX), a powerful tool used to measure the strength of market trends. It works alongside the Directional Movement Index (DMI), which breaks down the directional market pressure into bullish (+DI) and bearish (-DI) components. The purpose of the ADX is to indicate when the market is in a strong trend, without specifying the direction. This indicator can be especially useful for identifying market trends early and validating trading strategies based on trend-following systems.
The ADX component in this script is based on two key parameters:
ADX Smoothing Length (adxlen), which determines the degree of smoothing for the trend strength.
DI Length (dilen), which defines the look-back period for calculating the directional index values.
Additionally, a horizontal line is plotted at the 30 level, providing a widely used threshold that signifies when a trend is considered strong (above 30).
█ CONCEPTS
Directional Movement (DM): The core idea behind this indicator is the calculation of price movement in terms of bullish and bearish forces. By evaluating the change in highs and lows, the script distinguishes between bullish movement (+DM) and bearish movement (-DM). These values are normalized by dividing them by the True Range (TR), creating the +DI and -DI values.
True Range (TR): The True Range is calculated using the Average True Range (ATR) formula, and it serves to smooth out volatility, ensuring that short-term fluctuations don't distort the long-term trend signal.
ADX Calculation: The ADX is derived from the absolute difference between the +DI and -DI. By smoothing this difference and normalizing it, the ADX is able to measure the overall strength of the trend without regard to whether the market is moving up or down. A rising ADX indicates increasing trend strength, while a falling ADX signals weakening trends.
█ METHODOLOGY
Directional Movement Calculation: The script first determines the upward and downward price movement by comparing changes in the high and low prices. If the upward movement is greater than the downward movement, it registers a bullish signal and vice versa for bearish movement.
True Range Adjustment: The script then applies a smoothing function to normalize these movements by dividing them by the True Range (ATR). This ensures that the trend signal is based on relative, rather than absolute, price movements.
ADX Signal Generation: The final step is to calculate the ADX by applying the Relative Moving Average (RMA) to the difference between +DI and -DI. This produces the ADX value, which is plotted in red, making it easy to visualize shifts in market momentum.
Threshold Line: A blue horizontal line is plotted at 30, which serves as a key reference point. When the ADX is above this line, it indicates a strong trend, whether bullish or bearish.
█ HOW TO USE
Trend Strength: Traders typically use the 30 level as a critical threshold. When the ADX is above 30, it signifies a strong trend, making it a favorable environment for trend-following strategies. Conversely, ADX values below 30 suggest a weak or non-trending market.
+DI and -DI Relationship: The indicator also provides insight into whether the trend is bullish or bearish. When +DI is greater than -DI, the market is considered bullish. When -DI is greater than +DI, the market is considered bearish. While this script focuses on the ADX value itself, the underlying +DI and -DI help interpret the trend direction.
Market Conditions: This indicator is effective in trending markets, but not ideal for choppy or sideways conditions. Traders can use it to determine the best entry and exit points when trends are strong, or to avoid trading in periods of low volatility.
Combining with Other Indicators: The ADX is commonly used in conjunction with oscillators like RSI or moving averages, to confirm the trend strength and avoid false signals.
█ METHOD VARIANTS
This script applies the standard approach for calculating the ADX, but could be adapted with the following variants:
Different Timeframes: The script could be modified to calculate ADX values across higher or lower timeframes, depending on the trader's strategy.
Custom Thresholds: Instead of using the default 30 threshold, traders could adjust the horizontal line to suit their own risk tolerance or market conditions.
EMA Regime FilterEMA REGIME FILTER INDICATOR
✦ OVERVIEW
The EMA Regime Filter is a custom indicator, designed to identify and visualize different market regimes based on the relationship between price action and an Exponential Moving Average (EMA).
✦ KEY FEATURES
Identifies four distinct market regimes: Strong Bullish, Weak Bullish, Strong Bearish, and Weak Bearish
Uses a current/higher timeframe for calculations to reduce noise
Incorporates ATR (Average True Range) to determine significant price moves
Includes an inactivity timer to revert to a neutral state after periods of low volatility
Visualizes the regime through bar colors and candle plots
✦ INPUT PARAMETERS
Source Timeframe : The timeframe used for calculations (default is the chart's timeframe)
ATR Threshold For Significant Move : Multiplier for ATR to determine significant price moves (default: 0.5)
Inactive Regime Period : Number of periods of inactivity before reverting to neutral (default: 10)
EMA Length : Period for the Exponential Moving Average calculation (default: 22)
✦ HOW IT WORKS
Higher Timeframe Data: The indicator requests data from a higher timeframe specified by the user.
Significant Move Detection:
Calculates ATR and multiplies it by the user-defined threshold.
Compares the body width of each candle to this threshold to determine if it's a significant move.
EMA Calculation: Computes an EMA based on the user-defined length.
Regime Determination:
Strong Bullish (2): Significant bullish move above EMA
Weak Bullish (1): Transitioning from bearish, but still above EMA
Strong Bearish (-2): Significant bearish move below EMA
Weak Bearish (-1): Transitioning from bullish, but still below EMA
Neutral (0): After a period of inactivity or at the start
Regime Transitions:
The indicator tracks the current regime and updates it based on new significant moves and the price's relation to the EMA.
An inactivity counter reverts the regime to neutral if no significant moves occur for the specified period.
Visualization:
Bar colors change based on the current regime (lime for bullish, red for bearish, white for neutral).
The intensity of the color indicates the strength of the regime.
✦ USING THE INDICATOR
Add the indicator to your TradingView chart.
Adjust the input parameters as needed:
Increase the ATR threshold for fewer but more significant regime changes.
Adjust the inactive period to change how quickly the indicator reverts to neutral.
Modify the EMA length to suit your trading timeframe.
Observe the changing bar colors to identify the current market regime.
Use the regime information to inform your trading decisions, such as:
Looking for long opportunities in bullish regimes
Considering short positions in bearish regimes
Being cautious or staying out of the market during neutral regimes
Double BBW OverlayDouble BBW Overlay Indicator
Overview
The Double BBW (Bollinger Band Width) Overlay indicator is a custom script for TradingView that combines two BBW indicators with adjustable settings. It allows traders to compare the volatility of two different periods of Bollinger Bands on the same chart. By default, the first BBW is calculated with a 10-period center line, and the second BBW with a 20-period center line, but these values can be customized.
How It Works
Bollinger Bands consist of an upper band, a lower band, and a middle band (typically a moving average). The Bollinger Band Width (BBW) measures the distance between the upper and lower bands relative to the center line. The width of these bands indicates market volatility:
Narrow Bands: Low volatility, usually preceding a breakout.
Wide Bands: High volatility, often following a strong price movement.
This indicator plots two BBW values on a non-overlay chart, making it easy to visualize and compare different market conditions over different periods.
Indicator Components
BBW 1 (default period: 10)
Calculates the BBW using a center line based on a 10-period moving average.
The width is plotted in blue by default.
BBW 2 (default period: 20)
Calculates the BBW using a center line based on a 20-period moving average.
The width is plotted in red by default.
Zero Line
A gray horizontal line at the value of 0 for reference, helping to understand the scale of BBW values.
Input Parameters
Center Line Period for BBW 1 (length1)
Default: 10
This controls the length of the moving average for the first BBW calculation. It defines how many periods are used to calculate the middle Bollinger Band for BBW 1.
Center Line Period for BBW 2 (length2)
Default: 20
This controls the length of the moving average for the second BBW calculation. It defines how many periods are used to calculate the middle Bollinger Band for BBW 2.
Standard Deviation Multiplier (mult)
Default: 2.0
This controls how far the upper and lower Bollinger Bands are from the center line. The multiplier affects how sensitive the Bollinger Bands are to price changes, with higher values producing wider bands.
How to Use
Adding the Indicator: Once the script is added to your TradingView account, simply apply the indicator to any chart. It will be displayed as a separate pane below the price chart, showing two BBW lines corresponding to the two different periods.
Customizing Periods: Use the settings panel to adjust the center line periods for BBW 1 and BBW 2 to match your desired trading strategy. For instance, you can analyze short-term versus long-term volatility by adjusting the periods.
Volatility Analysis:
When both BBW lines are narrow, it indicates low volatility across both short-term and long-term periods, which could suggest that a breakout is imminent.
If both BBW lines widen simultaneously, it shows that volatility is increasing in both timeframes, possibly indicating a strong trend.
Use Cases
Breakout Strategy: When the BBW lines contract significantly, it may signal that a low-volatility period is about to end, which is often followed by a price breakout in either direction.
Trend Strength: Comparing short-term and long-term BBW values can help determine if recent price movements are supported by broader market volatility or if they are isolated to the short term.
Chart Display
BBW 1: Blue line, representing the Bollinger Band Width calculated with a center line period of 10 (or your customized value).
BBW 2: Red line, representing the Bollinger Band Width calculated with a center line period of 20 (or your customized value).
Zero Line: A gray line at 0 is provided for reference, although BBW values are always positive.
Advantages of Using Double BBW
Comprehensive View of Volatility: By overlaying two BBW indicators with different timeframes, you can gain insights into both short-term and long-term market volatility trends.
Customizable: You can easily adjust the moving average periods and the standard deviation multiplier to match your preferred trading strategy or the characteristics of the asset you are trading.
Easy Visualization: The separate plots of BBW values make it easier to see shifts in market volatility, allowing you to spot potential trading opportunities.
Entry Weight Indicator(Dual Labels)이 지표는 트레이더가 동적으로 진입 비중을 결정할 수 있도록 도와주는 도구입니다. 이전 캔들의 종가를 기준으로 두 가지 다른 진입 비중을 계산하여 표시합니다.
주요 특징:
1. 두 가지 진입 비중 계산:
- 저점 기준 (EW Long): 이전 캔들 종가와 룩백 기간 내 최저가 사이의 거리를 기준으로 계산
- 고점 기준 (EW Short): 이전 캔들 종가와 룩백 기간 내 최고가 사이의 거리를 기준으로 계산
2. 시각적 표시:
- 초록색 라벨 (EW Long): 캔들 위에 표시
- 빨간색 라벨 (EW Short): 캔들 아래에 표시
- 룩백 기간 내 최고가와 최저가를 녹색과 빨간색 선으로 표시
3. 사용자 정의 파라미터:
- 원하는 손실 비율 (Desired Loss Percentage)
- 레버리지 (Leverage)
- 룩백 기간 (Lookback Period)
4. 추가 정보 표시:
- 차트 우측 상단에 이전 종가, 최고가, 최저가, 손실 비율 등의 정보를 표시
사용 방법:
1. 원하는 손실 비율, 레버리지, 룩백 기간을 설정합니다.
2. 차트에 표시되는 라벨을 통해 각 캔들에 대한 두 가지 진입 비중을 확인합니다.
3. EW Long (초록색)은 Long 진입 시 비중을, EW Short (빨간색)는 Short 진입 시 비중을 나타냅니다.
주의: 이 지표는 투자 시 직접적인 성과를 가져다주는 지표가 아니며, 실제 거래 결정 시에는 다른 분석 도구와 함께 사용하는 것이 좋습니다.
This indicator is a tool that helps traders dynamically determine their entry weight. It calculates and displays two different entry weights based on the closing price of the previous candle.
Key features:
1. Calculation of two entry weights:
- Low-based (EW Long): Calculated based on the distance between the previous candle's close and the lowest price within the lookback period
- High-based (EW Short): Calculated based on the distance between the previous candle's close and the highest price within the lookback period
2. Visual display:
- Green label (EW Long): Displayed above the candle
- Red label (EW Short): Displayed below the candle
- Highest and lowest prices within the lookback period are shown as green and red lines
3. User-defined parameters:
- Desired Loss Percentage
- Leverage
- Lookback Period
4. Additional information display:
- Information such as previous close, highest price, lowest price, and loss percentage is displayed in the upper right corner of the chart
How to use:
1. Set the desired loss percentage, leverage, and lookback period.
2. Check the two entry weights for each candle through the labels displayed on the chart.
3. EW Long (green) represents the entry weight for long positions, while EW Short (red) represents the entry weight for short positions.
Caution: This indicator does not directly lead to investment performance. When making actual trading decisions, it is advisable to use it in conjunction with other analytical tools.
Aurous - Horizontal Rays Define Pip Size:
Since 1 pip for XAUUSD is usually considered as 0.1, the pip Size is set to 0.1. A 50-pip interval is therefore 50 * 0.1 = 5.0.
Nearest Pip Level Calculation:
We find the nearest 50-pip level based on the current price of XAUUSD. The formula nearestPipLevel = round(close / pipInterval) * pipInterval rounds the current price to the nearest multiple of the 50-pip interval.
Loop for Multiple Lines:
We use a loop that runs from -20 to 20 to plot horizontal ray lines 50 pips above and below the current price. The range (-20 to 20) ensures there are enough lines plotted both above and below the price.
Horizontal Ray Lines:
The line.new function is used to draw the horizontal rays, extending to the right.
Plot Current Price:
We also plot the closing price with a blue line to make it easier to track the price against the horizontal rays.
Gann Levels 360
This indicator plots a series of horizontal lines on a chart based on pre-defined levels and the current market price. These levels are believed to be significant for potential support and resistance zones according to the Gann trading methodology.
This code defines a custom indicator that plots a set of Gann levels and dynamically adjusts them based on the current market price. Users can change the line color through the input option.
Monthly Breakout StrategyThis Monthly High/Low Breakout Strategy is designed to take long or short positions based on breakouts from the high or low of the previous month. Users can select whether they want to go long at a breakout above the previous month’s high, short at a breakdown below the previous month’s low, or use the reverse logic. Additionally, it includes a month filter, allowing trades to be executed only during user-specified months.
Breakout strategies, particularly those based on monthly highs and lows, aim to capitalize on price momentum. These systems rely on the assumption that once a significant price level is breached (such as the previous month's high or low), the market is likely to continue moving in the same direction due to increased volatility and trend-following behaviors by traders. Studies have demonstrated the potential effectiveness of breakout strategies in financial markets.
Scientific Evidence Supporting Breakout Strategies:
Momentum in Financial Markets:
Research on momentum-based strategies, which include breakout trading, shows that securities breaking key levels of support or resistance tend to continue their price movement in the direction of the breakout. Jegadeesh and Titman (1993) found that stocks with strong performance over a given period tend to continue performing well in subsequent periods, a principle also applied to breakout strategies.
Behavioral Finance:
The psychological factor of herd behavior is one of the driving forces behind breakout strategies. When prices break out of a key level (such as a monthly high), it triggers increased buying or selling pressure as traders join the trend. Barberis, Shleifer, and Vishny (1998) explained how cognitive biases, such as overconfidence and sentiment, can amplify price trends, which breakout strategies attempt to exploit.
Market Efficiency:
While markets are generally efficient, periods of inefficiency can occur, particularly around the breakouts of significant price levels. These inefficiencies often result in temporary price trends, which breakout strategies can exploit before the market corrects itself (Fama, 1970).
Risk Considerations:
Despite the potential for profit, the Monthly Breakout Strategy comes with several risks:
False Breakouts:
One of the most common risks in breakout strategies is the occurrence of false breakouts. These happen when the price temporarily moves above (or below) a key level but quickly reverses direction, causing losses for traders who entered positions too early. This is particularly risky in low-volatility environments.
Market Volatility:
Monthly breakout strategies rely on momentum, which may not be consistent across different market conditions. During periods of low volatility, price breakouts might lack the follow-through required for the strategy to succeed, leading to poor performance.
Whipsaw Risk:
The strategy is vulnerable to whipsaw markets, where prices oscillate around key levels without establishing a clear direction. This can result in frequent entry and exit signals that lead to losses, especially if trading costs are not managed properly.
Overfitting to Past Data:
If the month-selection filter is overly optimized based on historical data, the strategy may suffer from overfitting—performing well in backtests but poorly in real-time trading. This happens when strategies are tailored to past market conditions that may not repeat.
Conclusion:
While monthly breakout strategies can be effective in markets with strong momentum, they are subject to several risks, including false breakouts, volatility dependency, and whipsaw behavior. It is crucial to backtest this strategy thoroughly and ensure it aligns with your risk tolerance before implementing it in live trading.
References:
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
Barberis, N., Shleifer, A., & Vishny, R. (1998). A Model of Investor Sentiment. Journal of Financial Economics, 49(3), 307-343.
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. Journal of Finance, 25(2), 383-417.
Candle Low Offset [QuadzCrypto]==== Candle Low Offset Indicator ====
==== Overview ====
The "Candle Low Offset" indicator offers a method for tracking a price point that sit below the low of each candle by a percentage offset.
It was originally intended to provide a price point with flexibility for setting a stop loss below the entry candle low, however, it could be used for other applications.
==== Definitions ====
- Offset Percentage: The % below the low you wish the trend line to follow configurable to 0.01 increments
==== Plots ====
- Offset: Plots a trend line below the candle lows
==== Style ====
- Offset: Allows users to configure the colour and thickness of the offset plot line
==== Application ====
This has been coded to be used with the Max StopLoss function on the Krown Quant SKX indicator to provide an alternative stop loss location on the entry candle.
==== Disclaimer ====
This indicator is for educational purposes only and should not be construed as financial advice. Trading involves risk, and you should consult with a qualified financial advisor before making any trading decisions.
ToS█ OVERVIEW
Contains methods for conversion to string of simple types int/float/bool/string/line/label/box .
- toS() - For bool/int/float works much the same as str.tostring() with some shorthand formatting options for int/float. For line/label/box displays their text and coordinates automatically formatting x coordinate as time or bar index.
- toShortString() - Converts a number to a short form using "k", "m", "bn" and "T" nominators. (e.g. `12,350` --> `12.4k`).
Supports some shorthand formatting options for int/float and time.
█ HOW TO USE
All toS() methods have the same parameters:
Parameters:
val (int) : A float to be converted to string
format (string) : Format string, which depends on the value type
nz (string) : (string) A string used to represent na (na values are substituted with this string).
For toS(bool/int/float) format parameter works in the same way as `str.format()` (i.e. you can use same format strings as with `str.format()` with `{0}` as a placeholder for the value)
Some shorthand "format" options available:
--- number ---
- "" => "{0}"
- "number" => "{0}"
- "0" => "{0, number, 0 }"
- "0.0" => "{0, number, 0.0 }"
- "0.00" => "{0, number, 0.00 }"
- "0.000" => "{0, number, 0.000 }"
- "0.0000" => "{0, number, 0.0000 }"
- "0.00000" => "{0, number, 0.00000 }"
- "0.000000" => "{0, number, 0.000000 }"
- "0.0000000" => "{0, number, 0.0000000}"
--- date ---
- "... ... " in any place is substituted with "{0, date, dd.MM.YY}"
- "date" => "{0, date, dd.MM.YY}"
- "date : time" => "{0, date, dd.MM.YY} : {0, time, HH.mm.ss}"
- "dd.MM" => "{0, date, dd:MM}"
- "dd" => "{0, date, dd}"
--- time ---
- "... ... " in any place is substituted with "{0, time, HH.mm.ss}"
- "time" => "{0, time, HH:mm:ss}"
- "HH:mm" => "{0, time, HH:mm}"
- "mm:ss" => "{0, time, mm:ss}"
- "date time" => "{0, date, dd.MM.YY\} {0, time, HH.mm.ss}"
- "date, time" => "{0, date, dd.MM.YY\}, {0, time, HH.mm.ss}"
- "date,time" => "{0, date, dd.MM.YY\},{0, time, HH.mm.ss}"
- "date time" => "{0, date, dd.MM.YY\} {0, time, HH.mm.ss}"
For toS(line) :
format (string) : (string) (Optional) Use `x1` as placeholder for `x1` and so on. E.g. default format is `"(x1, y1) - (x2, y2)"`.
For toS(label) :
format (string) : (string) (Optional) Use `x1` as placeholder for `x`, `y1 - for `y` and `txt` for label's text. E.g. default format is `(x1, y1): "txt"` if ptint_text is true and `(x1, y1)` if false.
For toS(box) :
format (string) : (string) (Optional) Use `x1` as placeholder for `x`, `y1 - for `y` etc. E.g. default format is "(x1, y1) - (x2, y2)".
For toS(color) :
format (string) : (string) (Optional) Options are "HEX" (e.g. "#FFFFFF33") or "RGB" (e.g. "rgb(122,122,122,23)"). Default is "HEX".
█ LIST OF FUNCTIONS AND PARAMETERS
method toS(val, format, nz)
Formats the `int/float` in the same way as `str.format()` (i.e. you can use same format strings as with
`str.format()` with `{0}` arg) with some shorthand "format" options:
```
--- number ---
- "" => "{0}"
- "number" => "{0}"
- "0" => "{0, number, 0 }"
- "0.0" => "{0, number, 0.0 }"
- "0.00" => "{0, number, 0.00 }"
- "0.000" => "{0, number, 0.000 }"
- "0.0000" => "{0, number, 0.0000 }"
- "0.00000" => "{0, number, 0.00000 }"
- "0.000000" => "{0, number, 0.000000 }"
- "0.0000000" => "{0, number, 0.0000000}"
--- date ---
- "......" in angular brackets in any place is substituted with "{0, date, dd.MM.YY}"
- "date" => "{0, date, dd.MM.YY}"
- "date : time" => "{0, date, dd.MM.YY} : {0, time, HH.mm.ss}"
- "dd.MM" => "{0, date, dd:MM}"
- "dd" => "{0, date, dd}"
--- time ---
- "......" in angular brackets in any place is substituted with "{0, time, HH.mm.ss}"
- "time" => "{0, time, HH:mm:ss}"
- "HH:mm" => "{0, time, HH:mm}"
- "mm:ss" => "{0, time, mm:ss}"
- "date time" => "{0, date, dd.MM.YY\} {0, time, HH.mm.ss}"
- "date, time" => "{0, date, dd.MM.YY\}, {0, time, HH.mm.ss}"
- "date,time" => "{0, date, dd.MM.YY\},{0, time, HH.mm.ss}"
- "date time" => "{0, date, dd.MM.YY\} {0, time, HH.mm.ss}"
```
Namespace types: series int, simple int, input int, const int
Parameters:
val (int) : A float to be converted to string
format (string) : Format string (e.g. "0.000" or "date : time" or "HH:mm")
nz (string) : (string) A string used to represent na (na values are substituted with this string).
method toS(val, format, nz)
Formats the `int/float` in the same way as `str.format()` (i.e. you can use same format strings as with
`str.format()` with `{0}` arg) with some shorthand "format" options:
```
--- number ---
- "" => "{0}"
- "number" => "{0}"
- "0" => "{0, number, 0 }"
- "0.0" => "{0, number, 0.0 }"
- "0.00" => "{0, number, 0.00 }"
- "0.000" => "{0, number, 0.000 }"
- "0.0000" => "{0, number, 0.0000 }"
- "0.00000" => "{0, number, 0.00000 }"
- "0.000000" => "{0, number, 0.000000 }"
- "0.0000000" => "{0, number, 0.0000000}"
--- date ---
- "......" in angular brackets in any place is substituted with "{0, date, dd.MM.YY}"
- "date" => "{0, date, dd.MM.YY}"
- "date : time" => "{0, date, dd.MM.YY} : {0, time, HH.mm.ss}"
- "dd.MM" => "{0, date, dd:MM}"
- "dd" => "{0, date, dd}"
--- time ---
- "......" in angular brackets in any place is substituted with "{0, time, HH.mm.ss}"
- "time" => "{0, time, HH:mm:ss}"
- "HH:mm" => "{0, time, HH:mm}"
- "mm:ss" => "{0, time, mm:ss}"
- "date time" => "{0, date, dd.MM.YY\} {0, time, HH.mm.ss}"
- "date, time" => "{0, date, dd.MM.YY\}, {0, time, HH.mm.ss}"
- "date,time" => "{0, date, dd.MM.YY\},{0, time, HH.mm.ss}"
- "date time" => "{0, date, dd.MM.YY\} {0, time, HH.mm.ss}"
```
Namespace types: series float, simple float, input float, const float
Parameters:
val (float) : A float to be converted to string
format (string) : Format string (e.g. "0.000" or "date : time" or "HH:mm")
nz (string) : (string) A string used to represent na (na values are substituted with this string).
method toS(val, format, nz)
Formats `bool val` in the same way as `str.format()` (i.e. you can use same format strings as with
`str.format()` with `{0}` placeholder for the `val` argument).
Namespace types: series bool, simple bool, input bool, const bool
Parameters:
val (bool) : (bool) Value to be formatted
format (string)
nz (string) : (string) A string used to represent na (na values are substituted with this string).
method toS(val, format, nz)
Formats `string val` in the same way as `str.format()` (i.e. you can use same format strings as with
`str.format()` with `{0}` placeholder for the `val` argument).
Namespace types: series color, simple color, input color, const color
Parameters:
val (color)
format (string) : (string) "HEX" or "RGB"
nz (string) : (string) A string used to represent na (na values are substituted with this string).
method toS(val, format, nz)
Formats `string val` in the same way as `str.format()` (i.e. you can use same format strings as with
`str.format()` with `{0}` placeholder for the `val` argument).
Namespace types: series string, simple string, input string, const string
Parameters:
val (string)
format (string)
nz (string) : (string) A string used to represent na (na values are substituted with this string).
method toS(ln, format, nz)
Returns line's coordinates as a string (by default in "(x1, y1) - (x2, y2)" format, use `x1`, `y1`, `x2`,`y2` as placeholders in `format` string)). Automatically detects
whether the coordinates are in `xloc.bar_index` or `xloc.bar_time` and displays
accordingly (in _dd.MM.yy HH:mm:ss_ format)
Namespace types: series line
Parameters:
ln (line)
format (string) : (string) (Optional) Use `x1` as placeholder for `x1` and so on. E.g. default format is `"(x1, y1) - (x2, y2)"`.
nz (string) : (string) (Optional) If `val` is `na` and `nz` is not `na` the value of `nz` param is returned instead.
method toS(lbl, format, nz, print_text)
Returns label's coordinates and text as a string (by default in "(x, y): text = ...)" format; use `x1`, `y1`, `txt` as placeholders in `format` string))).
Automatically detects whether the coordinates are in `xloc.bar_index` or `xloc.bar_time` and displays.
accordingly (in _dd.MM.yy HH:mm:ss_ format)
Namespace types: series label
Parameters:
lbl (label)
format (string) : (string) (Optional) Use `x1` as placeholder for `x`, `y1 - for `y` and `txt` for label's text. E.g. default format is `(x1, y1): "txt"`.
nz (string) : (string) A string used to represent na (na values are substituted with this string).
print_text (bool)
method toS(bx, format, nz)
Returns box's coordinates as a string (by default in "(x1, y1) - (x2, y2)" format)
Namespace types: series box
Parameters:
bx (box)
format (string) : (string) (Optional) Use `x1` as placeholder for `x`, `y1 - for `y` etc. E.g. default format is "(x1, y1) - (x2, y2)".
nz (string) : (string) A string used to represent na (na values are substituted with this string).
method toShortString(this, decimals)
Converts number to a short form using "k", "m", "bn" and "T" nominators. (e.g. `12,350` --> `12.4k`).
@this (series float) Number to be converted to short format.
@decimals (series int) Optional argument. Decimal places to which number will be rounded. When no argument
is supplied, rounding is to the nearest integer.
Namespace types: series float, simple float, input float, const float
Parameters:
this (float)
decimals (int)
Mean Reversion Cloud (Ornstein-Uhlenbeck) // AlgoFyreThe Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator detects mean-reversion opportunities by applying the Ornstein-Uhlenbeck process. It calculates a dynamic mean using an Exponential Weighted Moving Average, surrounded by volatility bands, signaling potential buy/sell points when prices deviate.
TABLE OF CONTENTS
🔶 ORIGINALITY
🔸Adaptive Mean Calculation
🔸Volatility-Based Cloud
🔸Speed of Reversion (θ)
🔶 FUNCTIONALITY
🔸Dynamic Mean and Volatility Bands
🞘 How it works
🞘 How to calculate
🞘 Code extract
🔸Visualization via Table and Plotshapes
🞘 Table Overview
🞘 Plotshapes Explanation
🞘 Code extract
🔶 INSTRUCTIONS
🔸Step-by-Step Guidelines
🞘 Setting Up the Indicator
🞘 Understanding What to Look For on the Chart
🞘 Possible Entry Signals
🞘 Possible Take Profit Strategies
🞘 Possible Stop-Loss Levels
🞘 Additional Tips
🔸Customize settings
🔶 CONCLUSION
▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅
🔶 ORIGINALITY The Mean Reversion Cloud (Ornstein-Uhlenbeck) is a unique indicator that applies the Ornstein-Uhlenbeck stochastic process to identify mean-reverting behavior in asset prices. Unlike traditional moving average-based indicators, this model uses an Exponentially Weighted Moving Average (EWMA) to calculate the long-term mean, dynamically adjusting to recent price movements while still considering all historical data. It also incorporates volatility bands, providing a "cloud" that visually highlights overbought or oversold conditions. By calculating the speed of mean reversion (θ) through the autocorrelation of log returns, this indicator offers traders a more nuanced and mathematically robust tool for identifying mean-reversion opportunities. These innovations make it especially useful for markets that exhibit range-bound characteristics, offering timely buy and sell signals based on statistical deviations from the mean.
🔸Adaptive Mean Calculation Traditional MA indicators use fixed lengths, which can lead to lagging signals or over-sensitivity in volatile markets. The Mean Reversion Cloud uses an Exponentially Weighted Moving Average (EWMA), which adapts to price movements by dynamically adjusting its calculation, offering a more responsive mean.
🔸Volatility-Based Cloud Unlike simple moving averages that only plot a single line, the Mean Reversion Cloud surrounds the dynamic mean with volatility bands. These bands, based on standard deviations, provide traders with a visual cue of when prices are statistically likely to revert, highlighting potential reversal zones.
🔸Speed of Reversion (θ) The indicator goes beyond price averages by calculating the speed at which the price reverts to the mean (θ), using the autocorrelation of log returns. This gives traders an additional tool for estimating the likelihood and timing of mean reversion, making the signals more reliable in practice.
🔶 FUNCTIONALITY The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator is designed to detect potential mean-reversion opportunities in asset prices by applying the Ornstein-Uhlenbeck stochastic process. It calculates a dynamic mean through the Exponentially Weighted Moving Average (EWMA) and plots volatility bands based on the standard deviation of the asset's price over a specified period. These bands create a "cloud" that represents expected price fluctuations, helping traders to identify overbought or oversold conditions. By calculating the speed of reversion (θ) from the autocorrelation of log returns, the indicator offers a more refined way of assessing how quickly prices may revert to the mean. Additionally, the inclusion of volatility provides a comprehensive view of market conditions, allowing for more accurate buy and sell signals.
Let's dive into the details:
🔸Dynamic Mean and Volatility Bands The dynamic mean (μ) is calculated using the EWMA, giving more weight to recent prices but considering all historical data. This process closely resembles the Ornstein-Uhlenbeck (OU) process, which models the tendency of a stochastic variable (such as price) to revert to its mean over time. Volatility bands are plotted around the mean using standard deviation, forming the "cloud" that signals overbought or oversold conditions. The cloud adapts dynamically to price fluctuations and market volatility, making it a versatile tool for mean-reversion strategies. 🞘 How it works Step one: Calculate the dynamic mean (μ) The Ornstein-Uhlenbeck process describes how a variable, such as an asset's price, tends to revert to a long-term mean while subject to random fluctuations. In this indicator, the EWMA is used to compute the dynamic mean (μ), mimicking the mean-reverting behavior of the OU process. Use the EWMA formula to compute a weighted mean that adjusts to recent price movements. Assign exponentially decreasing weights to older data while giving more emphasis to current prices. Step two: Plot volatility bands Calculate the standard deviation of the price over a user-defined period to determine market volatility. Position the upper and lower bands around the mean by adding and subtracting a multiple of the standard deviation. 🞘 How to calculate Exponential Weighted Moving Average (EWMA)
The EWMA dynamically adjusts to recent price movements:
mu_t = lambda * mu_{t-1} + (1 - lambda) * P_t
Where mu_t is the mean at time t, lambda is the decay factor, and P_t is the price at time t. The higher the decay factor, the more weight is given to recent data.
Autocorrelation (ρ) and Standard Deviation (σ)
To measure mean reversion speed and volatility: rho = correlation(log(close), log(close ), length) Where rho is the autocorrelation of log returns over a specified period.
To calculate volatility:
sigma = stdev(close, length)
Where sigma is the standard deviation of the asset's closing price over a specified length.
Upper and Lower Bands
The upper and lower bands are calculated as follows:
upper_band = mu + (threshold * sigma)
lower_band = mu - (threshold * sigma)
Where threshold is a multiplier for the standard deviation, usually set to 2. These bands represent the range within which the price is expected to fluctuate, based on current volatility and the mean.
🞘 Code extract // Calculate Returns
returns = math.log(close / close )
// Calculate Long-Term Mean (μ) using EWMA over the entire dataset
var float ewma_mu = na // Initialize ewma_mu as 'na'
ewma_mu := na(ewma_mu ) ? close : decay_factor * ewma_mu + (1 - decay_factor) * close
mu = ewma_mu
// Calculate Autocorrelation at Lag 1
rho1 = ta.correlation(returns, returns , corr_length)
// Ensure rho1 is within valid range to avoid errors
rho1 := na(rho1) or rho1 <= 0 ? 0.0001 : rho1
// Calculate Speed of Mean Reversion (θ)
theta = -math.log(rho1)
// Calculate Volatility (σ)
sigma = ta.stdev(close, corr_length)
// Calculate Upper and Lower Bands
upper_band = mu + threshold * sigma
lower_band = mu - threshold * sigma
🔸Visualization via Table and Plotshapes
The table shows key statistics such as the current value of the dynamic mean (μ), the number of times the price has crossed the upper or lower bands, and the consecutive number of bars that the price has remained in an overbought or oversold state.
Plotshapes (diamonds) are used to signal buy and sell opportunities. A green diamond below the price suggests a buy signal when the price crosses below the lower band, and a red diamond above the price indicates a sell signal when the price crosses above the upper band.
The table and plotshapes provide a comprehensive visualization, combining both statistical and actionable information to aid decision-making.
🞘 Code extract // Reset consecutive_bars when price crosses the mean
var consecutive_bars = 0
if (close < mu and close >= mu) or (close > mu and close <= mu)
consecutive_bars := 0
else if math.abs(deviation) > 0
consecutive_bars := math.min(consecutive_bars + 1, dev_length)
transparency = math.max(0, math.min(100, 100 - (consecutive_bars * 100 / dev_length)))
🔶 INSTRUCTIONS
The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator can be set up by adding it to your TradingView chart and configuring parameters such as the decay factor, autocorrelation length, and volatility threshold to suit current market conditions. Look for price crossovers and deviations from the calculated mean for potential entry signals. Use the upper and lower bands as dynamic support/resistance levels for setting take profit and stop-loss orders. Combining this indicator with additional trend-following or momentum-based indicators can improve signal accuracy. Adjust settings for better mean-reversion detection and risk management.
🔸Step-by-Step Guidelines
🞘 Setting Up the Indicator
Adding the Indicator to the Chart:
Go to your TradingView chart.
Click on the "Indicators" button at the top.
Search for "Mean Reversion Cloud (Ornstein-Uhlenbeck)" in the indicators list.
Click on the indicator to add it to your chart.
Configuring the Indicator:
Open the indicator settings by clicking on the gear icon next to its name on the chart.
Decay Factor: Adjust the decay factor (λ) to control the responsiveness of the mean calculation. A higher value prioritizes recent data.
Autocorrelation Length: Set the autocorrelation length (θ) for calculating the speed of mean reversion. Longer lengths consider more historical data.
Threshold: Define the number of standard deviations for the upper and lower bands to determine how far price must deviate to trigger a signal.
Chart Setup:
Select the appropriate timeframe (e.g., 1-hour, daily) based on your trading strategy.
Consider using other indicators such as RSI or MACD to confirm buy and sell signals.
🞘 Understanding What to Look For on the Chart
Indicator Behavior:
Observe how the price interacts with the dynamic mean and volatility bands. The price staying within the bands suggests mean-reverting behavior, while crossing the bands signals potential entry points.
The indicator calculates overbought/oversold conditions based on deviation from the mean, highlighted by color-coded cloud areas on the chart.
Crossovers and Deviation:
Look for crossovers between the price and the mean (μ) or the bands. A bullish crossover occurs when the price crosses below the lower band, signaling a potential buying opportunity.
A bearish crossover occurs when the price crosses above the upper band, suggesting a potential sell signal.
Deviations from the mean indicate market extremes. A large deviation indicates that the price is far from the mean, suggesting a potential reversal.
Slope and Direction:
Pay attention to the slope of the mean (μ). A rising slope suggests bullish market conditions, while a declining slope signals a bearish market.
The steepness of the slope can indicate the strength of the mean-reversion trend.
🞘 Possible Entry Signals
Bullish Entry:
Crossover Entry: Enter a long position when the price crosses below the lower band with a positive deviation from the mean.
Confirmation Entry: Use additional indicators like RSI (above 50) or increasing volume to confirm the bullish signal.
Bearish Entry:
Crossover Entry: Enter a short position when the price crosses above the upper band with a negative deviation from the mean.
Confirmation Entry: Look for RSI (below 50) or decreasing volume to confirm the bearish signal.
Deviation Confirmation:
Enter trades when the deviation from the mean is significant, indicating that the price has strayed far from its expected value and is likely to revert.
🞘 Possible Take Profit Strategies
Static Take Profit Levels:
Set predefined take profit levels based on historical volatility, using the upper and lower bands as guides.
Place take profit orders near recent support/resistance levels, ensuring you're capitalizing on the mean-reversion behavior.
Trailing Stop Loss:
Use a trailing stop based on a percentage of the price deviation from the mean to lock in profits as the trend progresses.
Adjust the trailing stop dynamically along the calculated bands to protect profits as the price returns to the mean.
Deviation-Based Exits:
Exit when the deviation from the mean starts to decrease, signaling that the price is returning to its equilibrium.
🞘 Possible Stop-Loss Levels
Initial Stop Loss:
Place an initial stop loss outside the lower band (for long positions) or above the upper band (for short positions) to protect against excessive deviations.
Use a volatility-based buffer to avoid getting stopped out during normal price fluctuations.
Dynamic Stop Loss:
Move the stop loss closer to the mean as the price converges back towards equilibrium, reducing risk.
Adjust the stop loss dynamically along the bands to account for sudden market movements.
🞘 Additional Tips
Combine with Other Indicators:
Enhance your strategy by combining the Mean Reversion Cloud with momentum indicators like MACD, RSI, or Bollinger Bands to confirm market conditions.
Backtesting and Practice:
Backtest the indicator on historical data to understand how it performs in various market environments.
Practice using the indicator on a demo account before implementing it in live trading.
Market Awareness:
Keep an eye on market news and events that might cause extreme price movements. The indicator reacts to price data and might not account for news-driven events that can cause large deviations.
🔸Customize settings 🞘 Decay Factor (λ): Defines the weight assigned to recent price data in the calculation of the mean. A value closer to 1 places more emphasis on recent prices, while lower values create a smoother, more lagging mean.
🞘 Autocorrelation Length (θ): Sets the period for calculating the speed of mean reversion and volatility. Longer lengths capture more historical data, providing smoother calculations, while shorter lengths make the indicator more responsive.
🞘 Threshold (σ): Specifies the number of standard deviations used to create the upper and lower bands. Higher thresholds widen the bands, producing fewer signals, while lower thresholds tighten the bands for more frequent signals.
🞘 Max Gradient Length (γ): Determines the maximum number of consecutive bars for calculating the deviation gradient. This setting impacts the transparency of the plotted bands based on the length of deviation from the mean.
🔶 CONCLUSION
The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator offers a sophisticated approach to identifying mean-reversion opportunities by applying the Ornstein-Uhlenbeck stochastic process. This dynamic indicator calculates a responsive mean using an Exponentially Weighted Moving Average (EWMA) and plots volatility-based bands to highlight overbought and oversold conditions. By incorporating advanced statistical measures like autocorrelation and standard deviation, traders can better assess market extremes and potential reversals. The indicator’s ability to adapt to price behavior makes it a versatile tool for traders focused on both short-term price deviations and longer-term mean-reversion strategies. With its unique blend of statistical rigor and visual clarity, the Mean Reversion Cloud provides an invaluable tool for understanding and capitalizing on market inefficiencies.
Periodic Linear Regressions [LuxAlgo]The Periodic Linear Regressions (PLR) indicator calculates linear regressions periodically (similar to the VWAP indicator) based on a user-set period (anchor).
This allows for estimating underlying trends in the price, as well as providing potential supports/resistances.
🔶 USAGE
The Periodic Linear Regressions indicator calculates a linear regression over a user-selected interval determined from the selected "Anchor Period".
The PLR can be visualized as a regular linear regression (Static), with a fit readjusting for new data points until the end of the selected period, or as a moving average (Rolling), with new values obtained from the last point of a linear regression fitted over the calculation interval. While the static method line is prone to repainting, it has value since it can further emphasize the linearity of an underlying trend, as well as suggest future trend directions by extrapolating the fit.
Extremities are included in the indicator, these are obtained from the root mean squared error (RMSE) between the price and calculated linear regression. The Multiple setting allows the users to control how far each extremity is from the other.
Periodic Linear Regressions can be helpful in finding support/resistance areas or even opportunities when ranging in a channel.
The anchor - where a new period starts - can be shown (in this case in the top right corner).
The shown bands can be visualized by enabling Show Extremities in settings ( Rolling or Static method).
The script includes a background gradient color option for the bands, which only applies when using the Rolling method.
The indicator colors can be suggestive of the detected trend and are determined as follows:
Method Rolling: a gradient color between red and green indicates the trend; more green if the output is rising, suggesting an uptrend, and more red if it is decreasing, suggesting a downtrend.
Method Static: green if the slope of the line is positive, suggesting an uptrend, red if negative, suggesting a downtrend.
🔶 DETAILS
🔹 Anchor Type
When the Anchor Type is set to Periodic , the indicator will be reset when the "Anchor Period" changes, after which calculations will start again.
An anchored rolling line set at First Bar won't reset at a new session; it will continue calculating the linear regression from the first bar to the last; in other words, every bar is included in the calculation. This can be useful to detect potential long-term tops/bottoms.
Note that a linear regression needs at least two values for its calculation, which explains why you won't see a static line at the first bar of the session. The rolling linear regression will only show from the 3rd bar of the session since it also needs a previous value.
🔹 Rolling/Static
When Anchor Type is set at Periodic , a linear regression is calculated between the first bar of the chosen session and the current bar, aiming to find the line that best fits the dataset.
The example above shows the lines drawn during the session. The offered script, though, shows the last calculated point connected to the previous point when the Rolling method is chosen, while the Static method shows the latest line.
Note that linear regression needs at least two values, which explains why you won't see a static line at the first bar of the session. The rolling line will only show from the 3rd bar of the session since it also needs a previous value.
🔶 SETTINGS
Method: Indicator method used, with options: "Static" (straight line) / "Rolling" (rolling linear regression).
Anchor Type: "Periodic / First Bar" (the latter works only when "Method" is set to "Rolling").
Anchor Period: Only applicable when "Anchor Type" is set at "Periodic".
Source: open, high, low, close, ...
Multiple: Alters the width of the bands when "Show Extremities" is enabled.
Show Extremities: Display one upper and one lower extremity.
🔹 Color Settings
Mono Color: color when "Bicolor" is disabled
Bicolor: Toggle on/off + Colors
Gradient: Background color when "Show extremities" is enabled + level of gradient
🔹 Dashboard
Show Dashboard
Location of dashboard
Text size
EV Calculator [CHE]EV Calculator with Adjustable Boxes and Custom Colors for TradingView
Introduction:
As a trader, one of the key metrics you need to evaluate is the Expected Value (EV) of your trading strategy. Understanding EV helps you gauge whether your trades will be profitable in the long run. This TradingView script allows you to visualize your EV alongside customizable win rates and risk-to-reward ratios. With adjustable visual components, you can quickly determine whether your trading strategy has a positive or negative EV, and make informed decisions.
Features of the Script:
1. Customizable Inputs:
- Win Rate: Set your win probability (0.0 to 1.0), which represents how often your strategy is successful.
- Risk and Reward: Define how much you're risking and the potential reward for each trade.
2. Visual Representation:
- The script creates colored boxes representing different EV scenarios:
- Green Box: Indicates a good EV (>2), suggesting a highly profitable strategy.
- Yellow Box: Represents a neutral EV (between 0 and 2), where the strategy could work but is not optimal.
- Red Box: Shows a negative EV (<0), signaling that the strategy may lead to losses.
3. Adjustable Box Size:
- You can modify the width and height of the boxes to fit your chart display preferences, giving you better visual clarity based on your screen or chart style.
4. Dynamic Labels:
- Each bar in the chart includes dynamic labels showing:
- Win Rate: Displays the percentage chance of success.
- EV Value: Shows the calculated expected value based on the win rate and risk-reward ratio.
- Guide: Explains what each colored box means so that you can easily interpret the chart.
5. Scalability and Flexibility:
- The script only keeps a maximum of 20 recent entries, ensuring that your chart stays clean and organized.
- Both the number of labels and boxes adjust automatically to match your preferred settings, enhancing usability.
How the EV Calculation Works:
The formula for EV is based on a standard risk-to-reward model:
EV = (Win\ Rate \times Reward) - (Loss\ Probability \times Risk)
For example:
- If your win rate is 60% and your risk-to-reward ratio is 1:3, the script will calculate whether this strategy is expected to yield positive returns or result in long-term losses.
Example Use Case:
Let's say you are trading with a 60% win rate, risking 1 unit to gain 3 units. The script calculates that your EV is positive and represents this with a Green Box, showing you that your strategy has a high likelihood of being profitable. If your strategy slips and the win rate drops, the EV calculation will adjust, and you may see Yellow or Red Boxes, signaling a need for adjustment.
Final Thoughts:
This script is designed for traders who want to take their analysis beyond the basics. By providing real-time visualization of your EV, you can better assess whether your strategy is sound and make adjustments as needed.
How to Use:
- Adjust the input parameters for Win Rate, Risk, and Reward to match your trading strategy.
- Observe the colored boxes and labels to quickly understand if your current strategy is in a healthy EV zone.
- Use this visual feedback to refine your approach and stay on track towards profitability.
This tool simplifies the complex calculations behind EV and turns it into an intuitive and powerful decision-making aid for traders.
Now you're ready to integrate the EV Calculator with Adjustable Boxes and Custom Colors into your trading routine and start optimizing your strategies for long-term success!
Happy Trading and best regards Chervolino
Inamdar Wave - Winning Wave
The **"Inamdar Wave"**, also known as the **"Winning Wave"**, is a cutting-edge market indicator designed to help traders ride the waves of momentum and capitalize on high-probability opportunities. With its unique ability to adapt to market shifts, the Inamdar Wave ensures you're always in sync with the market's most profitable moves, making it an indispensable tool for traders looking for consistent success.
### Key Features of the "Inamdar Wave":
1. **Dynamic Market Movement Detection**:
- The **Inamdar Wave** tracks the market’s momentum and identifies clear waves of movement, allowing traders to catch both upswings and downswings with ease.
- This indicator dynamically adjusts based on price action and volatility, ensuring you're always aligned with the market’s natural flow.
- Whether the market is trending or ranging, the **Inamdar Wave** keeps you on the right path, helping you surf the market's waves effortlessly.
2. **Highly Profitable Buy/Sell Signals**:
- The **Inamdar Wave** generates precise buy and sell signals that guide you to the most profitable entry and exit points.
- Its built-in filters ensure you avoid market noise, focusing only on high-probability trades that maximize your potential for profit.
- You’ll confidently enter trades at the start of each new wave, ensuring you ride the momentum for maximum gains.
3. **Visual Wave Highlighting**:
- Color-coded zones help you easily spot bullish (upward) and bearish (downward) waves.
- Green highlights signal upward waves, while red zones indicate downward waves, making it visually simple to recognize the current market direction.
- This feature allows for quick decision-making and a clear understanding of the market's direction at a glance.
4. **Tailored for Any Market Condition**:
- Whether you’re trading a calm or highly volatile market, the **Inamdar Wave** adapts to the changing conditions, ensuring consistent performance across all environments.
- Its flexibility allows it to work seamlessly with any asset class—stocks, forex, crypto, or commodities—making it an all-in-one solution for traders.
- The **Inamdar Wave**'s real-time adjustments keep it relevant regardless of market conditions or timeframes.
5. **Real-Time Alerts**:
- Get instant alerts when a new wave begins, whether it's a buy, sell, or wave reversal.
- You’ll never miss out on a profitable opportunity with real-time notifications that keep you one step ahead of the market.
- These alerts help you act quickly, maximizing the potential of every market movement.
### Inputs:
- **Wave Period**: Customize the sensitivity of the wave detection with adjustable periods to suit your trading style.
- **Signal Source**: Choose from different price sources to fine-tune how the **Inamdar Wave** reacts to market movements.
- **Signal Strength**: Control the sensitivity of wave detection to focus on only the strongest and most profitable moves.
- **Buy/Sell Signals**: Easily toggle buy/sell signals on your chart for enhanced clarity.
- **Wave Highlighting**: Turn visual wave highlights on or off, depending on your preference.
### Use Case:
The **Inamdar Wave** is perfect for traders looking to capture the most profitable waves in any market. Whether you're a short-term scalper or a long-term trend follower, this indicator keeps you in sync with the market’s natural rhythm, ensuring that you're always riding the winning wave. With its powerful buy/sell signals and dynamic wave detection, you'll be better positioned to take advantage of market momentum and secure consistent profits.
In conclusion, the **"Inamdar Wave"** is not just another indicator—it’s your key to riding the market’s most profitable waves with precision and confidence. By following the signals and staying in tune with the market’s natural flow, you’ll be able to maximize your gains and minimize your risks, ensuring a successful trading journey.
Killzones And Macros LibraryKillzones & Macros Library for Trading Sessions
This Pine Script library is designed to help traders identify and act during high-volatility trading windows, commonly referred to as "Killzones." These are specific times during the day when institutional traders are most active, resulting in increased liquidity and price movement. The library provides boolean fields that return true when the current time falls within one of the killzones or macroeconomic event windows, allowing for enhanced trade timing and precision.
Killzones Include:
London Open, New York Open, Midnight Open, London Lunch, New York PM, and more.
Capture high-volume periods like Power Hour, Equities Open, and Asian Range.
Macros:
Identify key moments like London 02:33, New York 08:50, and other significant times aligned with market movements or events.
This library is perfect for integrating into your custom strategies, backtesting, or setting alerts for optimal trade execution during major trading sessions and events.
Pi Cycle Top & Bottom Indicator [InvestorUnknown]The Pi Cycle Top & Bottom Indicator is designed for long-term cycle analysis, particularly useful for detecting significant market tops and bottoms in assets like Bitcoin. By comparing the behavior of two moving averages, one with a shorter period (default 111) and the other with a longer period (default 350), the indicator helps investors identify potential turning points in the market.
Key Features:
Dual Moving Average System:
The indicator uses two moving averages (MA) to create a cyclic oscillator. The shorter moving average (Short Length MA) is more reactive to recent price changes, while the longer moving average (Long Length MA) smooths out long-term trends. Users can select between:
Simple Moving Average (SMA): A straightforward average of closing prices.
Exponential Moving Average (EMA): Places more weight on recent prices, making it more responsive to market changes.
Oscillator Mode Options:
The Pi Cycle Indicator offers two modes of oscillation to better suit different analysis styles:
RAW Mode: This mode calculates the raw ratio of the Short MA to the Long MA, offering a simple comparison of the two averages.
LOG(X) Mode: In this mode, the oscillator takes the natural logarithm of the Short MA to Long MA ratio. This transformation compresses extreme values and highlights relative changes more effectively, making it particularly useful for spotting shifts in long-term trends.
Cyclical Analysis:
The core of the Pi Cycle Indicator is its ability to visualize the relationship between the two moving averages. The ratio of the Short MA to the Long MA is plotted as an oscillator. When the oscillator crosses above or below a baseline (which is 1 for RAW mode and 0 for LOG(X) mode), it signals potential market turning points.
Visual Representation:
The indicator provides a clear visual display of market conditions:
Orange Line: Represents the Pi Cycle Oscillator, which shows the relationship between the short and long moving averages.
Gray Baseline: A reference line that dynamically adjusts based on the oscillator mode. Crosses above or below this line help indicate possible trend reversals.
Shaded Areas: Color-filled areas between the oscillator and the baseline, which are shaded green when the market is bullish (oscillator above baseline) and red when bearish (oscillator below baseline). This provides a visual cue to assist in identifying potential market tops and bottoms.
Use Cases:
The Pi Cycle Top & Bottom Indicator is primarily used in long-term market analysis, such as Bitcoin cycles, to identify significant tops and bottoms. These moments often coincide with large cyclical shifts, making it valuable for those aiming to enter or exit positions at key moments in the market cycle.
By analyzing the interaction between short-term and long-term trends, investors can gain insight into broader market dynamics and make more informed decisions regarding entry and exit points. The ability to switch between moving average types (SMA/EMA) and oscillator modes (RAW/LOG) adds flexibility for adapting to different market environments.
Nifty IT VolumeHello everyone,
Here I present Nifty IT index volumes calculated based on weighted volumes of all constituents.
A simple formula for calculation:
constituent1.volume*weightage + constituent2.volume*weightage + ....
You can change color and code if there is a change in constituents of the index from NSE. I will share other index volumes soon.
Enjoy!
TechniTrend: Dynamic Pair CorrelationTechniTrend: Dynamic Pair Correlation
Description:
The TechniTrend: Dynamic Pair Correlation is a powerful and versatile indicator designed to track the correlation between two assets—whether cryptocurrencies, indices, or other financial instruments—across multiple timeframes. Understanding correlations can provide deep insights into market behavior, helping traders make informed decisions based on how two assets move in relation to each other.
Key Features:
Customizable Pair Selection: Compare any two assets (e.g., Bitcoin and DXY, Ethereum and SP500) to study how their price movements relate over time.
Multi-Timeframe Analysis: Simultaneously track correlations across different timeframes—standard, lower, and higher—providing a comprehensive view of market dynamics.
Dynamic Color Coding for Correlation Strength: Instantly spot correlations with visually intuitive colors—green for strong positive correlation, red for strong negative correlation, and yellow for neutral.
Heatmap Background: An easy-to-read background color heatmap highlights when correlations hit extreme levels, adding another layer of insight to your charts.
Real-Time Alerts: Get notified when correlations exceed your custom thresholds, signaling opportunities for potential breakouts, reversals, or divergences.
Divergence Detection: Automatically highlight moments when asset prices diverge, offering potential entry/exit points for smart trading decisions.
How to Use:
Asset Pair Comparison: Select two symbols to analyze their price correlation, such as BTC/USDT and DXY, or any other pair that fits your strategy.
Set Your Timeframes: Customize your standard, lower, and higher timeframes to monitor correlations at different intervals, allowing you to capture both short-term and long-term relationships.
Track Correlation Strength: Use dynamic color coding to quickly see how closely two assets are moving together. Strong correlations (positive or negative) could signal potential opportunities, while low correlations may indicate the absence of a strong trend.
Utilize Alerts: Receive real-time alerts when correlations cross your predefined thresholds, helping you take action when the market presents strong alignment or divergence.
Divergence Signals: Watch for divergence between the assets on multiple timeframes, which could indicate a potential trend reversal or a shift in market behavior.
Why It’s Essential:
Understanding the relationship between two assets can be a game changer for traders. Whether you're comparing Bitcoin to DXY, tracking the correlation between Ethereum and major indices, or evaluating two cryptocurrencies, this indicator gives you the tools to visualize and respond to market conditions with precision.
Perfect For:
Crypto traders looking to optimize strategies by monitoring the relationship between major cryptocurrencies and other assets.
Arbitrageurs seeking to capitalize on temporary pricing anomalies between correlated pairs.
Trend-followers aiming to catch large movements by detecting alignment or divergence between asset classes.
Portfolio managers monitoring how different asset classes impact each other to hedge or diversify investments.
By leveraging the TechniTrend: Dynamic Pair Correlation indicator, traders can gain deeper insights into market trends, correlations, and divergences, giving them an edge in fast-moving markets.
MTF Squeeze Analyzer - [tradeviZion]MTF Squeeze Analyzer
Multi-Timeframe Squeeze Pro Analyzer Tool
Overview:
The MTF Squeeze Analyzer is a comprehensive tool designed to help traders monitor the TTM Squeeze indicator across multiple timeframes in a streamlined and efficient manner. Built with Pine Script™ version 5, this indicator enhances your market analysis by providing detailed insights into squeeze conditions and momentum shifts, enabling you to make more informed trading decisions.
Key Features:
1. Multi-Timeframe Monitoring:
Comprehensive Coverage: Track squeeze conditions across multiple timeframes, including 1-minute, 5-minute, 15-minute, 30-minute, 1-hour, 2-hour, 4-hour, and daily charts.
Squeeze Counts: Keep count of the number of consecutive bars the price has been within each squeeze level (low, mid, high), helping you assess the strength and duration of consolidation periods.
2. Dynamic Table Display:
Customizable Appearance: Adjust table position, text size, and colors to suit your preferences.
Color-Coded Indicators: Easily identify squeeze levels and momentum shifts with intuitive color schemes.
Message Integration: Features rotating messages to keep you engaged and informed.
3. Alerts for Key Market Events:
Squeeze Start and Fire Alerts: Receive notifications when a squeeze starts or fires on your selected timeframes.
Custom Squeeze Count Alerts: Set thresholds for squeeze counts and get alerted when these levels are reached, allowing you to anticipate potential breakouts.
Fully Customizable: Choose which alerts you want to receive and tailor them to your trading strategy.
4. Momentum Analysis:
Momentum Oscillator: Visualize momentum using a histogram that changes color based on momentum shifts.
Detailed Insights: Determine whether momentum is increasing or decreasing to make more strategic trading decisions.
How It Works:
The indicator is based on the TTM Squeeze concept, which identifies periods of low volatility where the market is "squeezing" before a potential breakout. It analyzes the relationship between Bollinger Bands and Keltner Channels to determine squeeze conditions and uses linear regression to calculate momentum.
1. Squeeze Levels:
No Squeeze (Green): Market is not in a squeeze.
Low Compression Squeeze (Gray): Mild consolidation, potential for a breakout.
Mid Compression Squeeze (Red): Moderate consolidation, higher breakout potential.
High Compression Squeeze (Orange): Strong consolidation, significant breakout potential.
2. Squeeze Counts:
Tracks the number of consecutive bars in each squeeze condition.
Helps identify how long the market has been consolidating, providing clues about potential breakout timing.
3. Momentum Histogram:
Upward Momentum: Shown in aqua or blue, indicating increasing or decreasing upward momentum.
Downward Momentum: Displayed in red or yellow, representing increasing or decreasing downward momentum.
Using Alerts:
Stay ahead of market movements with customizable alerts:
1. Enable Alerts in Settings:
Squeeze Start Alert: Get notified when a new squeeze begins.
Squeeze Fire Alert: Be alerted when a squeeze ends, signaling a potential breakout.
Squeeze Count Alert: Set a specific number of bars for a squeeze condition, and receive an alert when this count is reached.
2. Set Up Alerts on Your Chart:
Click on the indicator name and select " Add Alert on MTF Squeeze Analyzer ".
Choose your desired alert conditions and customize the notification settings.
Click " Create " to activate the alerts.
How to Set It Up:
1. Add the Indicator to Your Chart:
Search for " MTF Squeeze Analyzer " in the TradingView Indicators library.
Add it to your chart.
2. Customize Your Settings:
Table Display:
Choose whether to show the table and select its position on the chart.
Adjust text size and colors to enhance readability.
Timeframe Selection:
Select the timeframes you want to monitor.
Enable or disable specific timeframes based on your trading strategy.
Colors & Styles:
Customize colors for different squeeze levels and momentum shifts.
Adjust header and text colors to match your chart theme.
Alert Settings:
Enable alerts for squeeze start, squeeze fire, and squeeze counts.
Set your preferred squeeze type and count threshold for alerts.
3. Interpret the Data:
Table Information:
The table displays the squeeze status and counts for each selected timeframe.
Colors indicate the type of squeeze, making it easy to assess market conditions at a glance.
Momentum Histogram:
Use the histogram to gauge the strength and direction of market momentum.
Observe color changes to identify shifts in momentum.
Why Use MTF Squeeze Analyzer ?
Enhanced Market Insight:
Gain a deeper understanding of market dynamics by monitoring multiple timeframes simultaneously.
Identify potential breakout opportunities by analyzing squeeze durations and momentum shifts.
Customizable and User-Friendly:
Tailor the indicator to fit your trading style and preferences.
Easily adjust settings without needing to delve into the code.
Time-Efficient:
Save time by viewing all relevant squeeze information in one place.
Reduce the need to switch between different charts and timeframes.
Stay Informed with Alerts:
Never miss a critical market movement with fully customizable alerts.
Focus on other tasks while the indicator monitors the market for you.
Acknowledgment:
This tool builds upon the foundational work of John Carter , who developed the TTM Squeeze concept. It also incorporates enhancements from LazyBear and Makit0 , providing a more versatile and powerful indicator. MTF Squeeze Analyzer extends these concepts by adding multi-timeframe analysis, squeeze counting, and advanced alerting features, offering traders a comprehensive solution for market analysis.
Note: Always practice proper risk management and test the indicator thoroughly to ensure it aligns with your trading strategy. Past performance is not indicative of future results.
Trade smarter with TradeVizion—unlock your trading potential today!
