BTC vs Mag7 Combined IndexThis Mag7 Combined Index script is a custom TradingView indicator that calculates and visualizes the collective performance of the Magnificent 7 (Mag7) stocks—Apple, Microsoft, Alphabet, Amazon, NVIDIA, Tesla, and Meta (red line) compared to Bitcoin (blue line). It normalizes the daily closing prices of each stock to their initial value on the chart, scales them into percentages, and then computes their simple average to form a combined index. The result is plotted as a single red line, offering a clear view of the aggregated performance of these influential stocks over time compared to Bitcoin.
This indicator is ideal for analyzing the overall market impact of Bitcoin compared to the Mag7 stocks.
Educational
Kamal 5 Tick Trading SetupKamal 5 Tick Trading Setup
The "Kamal 5 Tick Trading Setup" is a custom indicator designed by Kamal Preet Singh Trader for TradingView to identify potential Buy and Sell signals on daily forex charts. This indicator helps traders make informed decisions based on the price action of the previous five daily candles.
Indicator Logic:
Buy Signal: A Buy signal is generated when the closing price of the current candle exceeds the highest high of the previous five daily candles.
Sell Signal: A Sell signal is generated when the closing price of the current candle falls below the lowest low of the previous five daily candles.
Features:
Lookback Period: The indicator uses a lookback period of five candles to determine the highest high and lowest low.
Visual Signals: Buy signals are plotted as green "BUY" labels below the candles, while Sell signals are plotted as red "SELL" labels above the candles.
Debugging Plots: The highest high and lowest low of the previous five candles are plotted as blue and orange lines, respectively, to help verify the conditions for Buy and Sell signals.
Non-Repetitive Signals: The indicator ensures that once a Buy signal is given, no further Buy signals are generated until a Sell signal is given, and vice versa.
Usage:
Apply the indicator to your daily forex chart in TradingView.
Observe the plotted Buy and Sell signals to identify potential entry and exit points.
Use the debugging plots to ensure the conditions for the signals are being met correctly.
This indicator provides a straightforward approach to trading based on recent price action, helping traders capitalize on potential breakout and breakdown opportunities.
Supply and Demand RebalancingPlease do not use this rudimentary script to lose money. As far as I can tell it has ZERO EDGE on its own.
Supply and Demand Pattern Detection Script
Overview
This script identifies potential supply and demand zones by detecting a specific double-wick pattern formation. It's designed as an educational tool and research aid for traders interested in price action and supply/demand concepts.
Pattern Detection
Looks for consecutive candles with long wicks (tails) that align with each other
The wicks must be larger than a specified percentile of recent wick lengths
The candle bodies must be relatively small compared to their wicks
Volume and volatility filters can be optionally applied
Higher timeframe trend confirmation is available as an optional filter
Visual Aids
Green triangles appear when a long setup is detected
Red triangles appear when a short setup is detected
Boxes show the risk zone (red) and reward zone (green)
Boxes extend until the trade reaches either its target or stop loss
A performance table shows win rate and profit factor statistics
Key Settings
1. Pattern Detection:
Wick Alignment Tolerance: How closely the wicks need to align
Min Wick Length Percentile: Minimum size requirement for wicks
Max Body/Wick Ratio: Controls maximum candle body size relative to wick
2. Additional Filters:
Volume Filter: Optional volume confirmation
ATR Filter: Optional volatility confirmation
Higher Timeframe Confirmation: Optional trend alignment
3. Trade Parameters:
Risk/Reward Ratio: Default 2:1
Bars to Wait for Outcome: How long to track trade results
Important Disclaimers
This is an educational tool and should NOT be used to trade real money without extensive testing and modification. Please do not use this rudimentary script to lose money. As far as I can tell it has zero edge on its own.
Historical backtesting results are not indicative of future performance. The script may miss some valid setups or generate false signals. Trade outcomes are simplified and don't account for:
Slippage
Trading fees
Market liquidity
Gap risk
Real-world execution challenges
Recommended Usage
Use as a learning tool to understand supply/demand concepts
Practice identifying these patterns manually
Paper trade the setups first
Combine with other forms of analysis and risk management
Consider it one tool among many, not a complete trading system
Best Practices
Always use proper risk management
Test thoroughly on demo accounts first
Keep detailed trading logs
Understand why each pattern forms
Study both winning and losing trades to improve pattern recognition
Remember: No trading script can guarantee profits. This tool is meant for educational purposes and should be part of a broader trading education and development process.
Simple Average Price & Target ProfitThis script is designed to help users calculate and visualize the weighted average price of an asset based on multiple entry points, along with the target price and the potential profit. The user can input specific prices for three different entries, along with the percentage of total investment allocated to each price point. The script then calculates the weighted average price based on these entries and displays it on the chart. Additionally, it calculates the potential profit at a given target price, which is plotted on the chart.
mr.crypto731Description:
📊 Enhanced MACD with Strong Buy/Sell Signals 🚀
This script is designed to enhance the standard MACD indicator by adding clear, strong buy and sell signals. It includes:
MACD Line: A fast-moving average that reacts quickly to price changes.
Signal Line: A slower-moving average that smooths out price fluctuations.
MACD Histogram: The difference between the MACD Line and Signal Line, helping to identify trend strength and direction.
Key Features:
Strong Buy/Sell Signals: Uses crossovers of the MACD Line and Signal Line to generate strong buy/sell signals.
Color-Coded Background: Provides visual cues with background colors to highlight strong signals.
User-Friendly Interface: Customizable settings for MACD Fast Length, Slow Length, and Signal Smoothing.
Dynamic Volatility Differential Model (DVDM)The Dynamic Volatility Differential Model (DVDM) is a quantitative trading strategy designed to exploit the spread between implied volatility (IV) and historical (realized) volatility (HV). This strategy identifies trading opportunities by dynamically adjusting thresholds based on the standard deviation of the volatility spread. The DVDM is versatile and applicable across various markets, including equity indices, commodities, and derivatives such as the FDAX (DAX Futures).
Key Components of the DVDM:
1. Implied Volatility (IV):
The IV is derived from options markets and reflects the market’s expectation of future price volatility. For instance, the strategy uses volatility indices such as the VIX (S&P 500), VXN (Nasdaq 100), or RVX (Russell 2000), depending on the target market. These indices serve as proxies for market sentiment and risk perception (Whaley, 2000).
2. Historical Volatility (HV):
The HV is computed from the log returns of the underlying asset’s price. It represents the actual volatility observed in the market over a defined lookback period, adjusted to annualized levels using a multiplier of \sqrt{252} for daily data (Hull, 2012).
3. Volatility Spread:
The difference between IV and HV forms the volatility spread, which is a measure of divergence between market expectations and actual market behavior.
4. Dynamic Thresholds:
Unlike static thresholds, the DVDM employs dynamic thresholds derived from the standard deviation of the volatility spread. The thresholds are scaled by a user-defined multiplier, ensuring adaptability to market conditions and volatility regimes (Christoffersen & Jacobs, 2004).
Trading Logic:
1. Long Entry:
A long position is initiated when the volatility spread exceeds the upper dynamic threshold, signaling that implied volatility is significantly higher than realized volatility. This condition suggests potential mean reversion, as markets may correct inflated risk premiums.
2. Short Entry:
A short position is initiated when the volatility spread falls below the lower dynamic threshold, indicating that implied volatility is significantly undervalued relative to realized volatility. This signals the possibility of increased market uncertainty.
3. Exit Conditions:
Positions are closed when the volatility spread crosses the zero line, signifying a normalization of the divergence.
Advantages of the DVDM:
1. Adaptability:
Dynamic thresholds allow the strategy to adjust to changing market conditions, making it suitable for both low-volatility and high-volatility environments.
2. Quantitative Precision:
The use of standard deviation-based thresholds enhances statistical reliability and reduces subjectivity in decision-making.
3. Market Versatility:
The strategy’s reliance on volatility metrics makes it universally applicable across asset classes and markets, ensuring robust performance.
Scientific Relevance:
The strategy builds on empirical research into the predictive power of implied volatility over realized volatility (Poon & Granger, 2003). By leveraging the divergence between these measures, the DVDM aligns with findings that IV often overestimates future volatility, creating opportunities for mean-reversion trades. Furthermore, the inclusion of dynamic thresholds aligns with risk management best practices by adapting to volatility clustering, a well-documented phenomenon in financial markets (Engle, 1982).
References:
1. Christoffersen, P., & Jacobs, K. (2004). The importance of the volatility risk premium for volatility forecasting. Journal of Financial and Quantitative Analysis, 39(2), 375-397.
2. Engle, R. F. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987-1007.
3. Hull, J. C. (2012). Options, Futures, and Other Derivatives. Pearson Education.
4. Poon, S. H., & Granger, C. W. J. (2003). Forecasting volatility in financial markets: A review. Journal of Economic Literature, 41(2), 478-539.
5. Whaley, R. E. (2000). The investor fear gauge. Journal of Portfolio Management, 26(3), 12-17.
This strategy leverages quantitative techniques and statistical rigor to provide a systematic approach to volatility trading, making it a valuable tool for professional traders and quantitative analysts.
Spent Output Profit Ratio | JeffreyTimmermansSOPR
The "Spent Output Profit Ratio" , aka SOPR indicator is a valuable tool designed to analyze the profitability of spent Bitcoin outputs. SOPR is derived by dividing the selling price of Bitcoin by its purchase price, offering insights into market participants' profit-taking or loss-cutting behavior.
This script features two selectable SOPR metrics:
SOPR 30D: A 30-day Exponential Moving Average (EMA) for short-term trend analysis.
SOPR 365D: A 365-day EMA for assessing long-term profitability trends.
How It Works
Key Levels: The horizontal reference line at 1.0 acts as a critical threshold:
Above 1.0: Market participants are generally in profit, indicating bullish sentiment.
Below 1.0: Market participants are selling at a loss, often signaling bearish sentiment.
Background Colors
Green: Indicates bullish conditions when the selected SOPR value is above 1.
Red: Highlights bearish conditions when the value is below 1.
Dynamic Selection
Easily switch between SOPR 30D and SOPR 365D in the settings for tailored analysis.
Features
Customizable SOPR Selection: Toggle between 30-day and 365-day SOPR views based on your trading preferences.
Dynamic Label: A floating label displays the current SOPR value in real-time, along with the selected SOPR metric for easy monitoring.
Background Highlights: Visual cues for bullish and bearish conditions simplify chart interpretation.
Real-Time Alerts
Bullish Alerts: Triggered when the selected SOPR crosses above 1.
Bearish Alerts: Triggered when the selected SOPR crosses below 1.
Clean Visualization
The indicator includes a horizontal reference line and clear color schemes for easy trend identification.
The SOPR Indicator is an essential tool for traders and analysts seeking to understand Bitcoin market sentiment and profitability trends. Whether used for short-term trades or long-term market analysis, this script provides actionable insights to refine your decision-making process.
-Jeffrey
Market Regime DetectorMarket Regime Detector
The Market Regime Detector is a tool designed to help traders identify and adapt to the prevailing market environment by analyzing price action in relation to key macro timeframe levels. This indicator categorizes the market into distinct regimes—Bullish, Bearish, or Reverting—providing actionable insights to set trading expectations, manage volatility, and align strategies with broader market conditions.
What is a Market Regime?
A market regime refers to the overarching state or condition of the market at a given time. Understanding the market regime is critical for traders as it determines the most effective trading approach. The three main regimes are:
Bullish Regime:
Characterized by upward momentum where prices are consistently trending higher.
Trading strategies often focus on buying opportunities and trend-following setups.
Bearish Regime:
Defined by downward price pressure and declining trends.
Traders typically look for selling opportunities or adopt risk-off strategies.
Reverting Regime:
Represents a consolidation phase where prices move within a defined range.
Ideal for mean-reversion strategies or range-bound trading setups.
Key Features of the Market Regime Detector:
Dynamic Market Regime Detection:
Identifies the market regime based on macro timeframe high and low levels (e.g., weekly or monthly).
Provides clear and actionable insights for each regime to align trading strategies.
Visual Context for Price Levels:
Plots the macro high and low levels on the chart, allowing traders to visualize critical support and resistance zones.
Enhances understanding of volatility and trend boundaries.
Regime Transition Alerts:
Sends alerts only when the market transitions into a new regime, ensuring traders are notified of meaningful changes without redundant signals.
Alert messages include clear regime descriptions, such as "Market entered a Bullish Regime: Price is above the macro high."
Customizable Visualization:
Background colors dynamically adjust to the current regime:
Blue for Reverting.
Aqua for Bullish.
Fuchsia for Bearish.
Option to toggle high/low line plotting and background highlights for a tailored experience.
Volatility and Expectation Management:
Offers insights into market volatility by showing when price action approaches, exceeds, or reverts within macro timeframe levels.
Helps traders set realistic expectations and adjust their strategies accordingly.
Use Cases:
Trend Traders: Identify bullish or bearish regimes to capture sustained price movements.
Range Traders: Leverage reverting regimes to trade between defined support and resistance zones.
Risk Managers: Use macro high and low levels as dynamic stop-loss or take-profit zones to optimize trade management.
The Market Regime Detector equips traders with a deeper understanding of the market environment, making it an essential tool for informed decision-making and strategic planning. Whether you're trading trends, ranges, or managing risk, this indicator provides the clarity and insights needed to navigate any market condition.
Simple COT ReportCOT Net Positions Indicator
Author: © Munkhtur
This indicator provides a comprehensive visualization of the Commitment of Traders (COT) report data, enabling traders to analyze market sentiment and positioning for key market participants.
Key Features:
Dashboard Display: Shows the net positions of Commercial, Noncommercial, and Nonreportable (Retail) traders.
Dynamic Position Tracking: Highlights significant changes in long and short positions for all trader categories based on customizable percentage thresholds.
COT Data Integration: Utilizes Legacy COT report data with clear segregation of long, short, and net positions.
Visual Signals:
Bullish and bearish trends are indicated with customizable colors for better chart visualization.
Displays "open" and "close" position changes directly on the price candles for easier tracking.
Flexible Configuration: Adjustable settings for dashboard location, text size, percentage thresholds, and color schemes.
How to Use:
Load the Script: Add the indicator to your Futures chart only by navigating to the TradingView indicators menu and selecting it from your saved scripts.
Customize Settings:
Dashboard: Enable or disable the dashboard, and set its position (Top Left, Top Right, etc.).
Data on Candle: Turn on/off the visualization of COT data changes on price candles and define the percentage change threshold to focus on significant moves.
Style Options: Customize bullish and bearish colors for better visual differentiation.
Select Trader Group: Choose from Commercial, Noncommercial, or Nonreportable positions in the settings menu to analyze the specific group of market participants.
Interpret Signals:
Green bars indicate opening long positions or bullish sentiment.
Red bars highlight opening short positions or bearish sentiment.
Yellow and purple bars signify the closure of long and short positions, respectively.
Use Cases:
Identify market sentiment shifts by observing net position changes among different trader groups.
Spot potential trend reversals based on COT data dynamics.
Use as a complementary tool to confirm your existing trading strategies.
Disclaimer:
This indicator is a tool for educational and informational purposes only. Always combine it with your own analysis and risk management strategy when trading.
Renko Chart EmulationRenko charts are a popular tool in technical analysis, known for their ability to filter out market noise and focus purely on price movements. Unlike traditional candlestick or bar charts, Renko charts are not time-based but are constructed using bricks that represent a fixed price movement. This makes them particularly useful for identifying trends and key levels of support and resistance. While Renko charts are commonly found on platforms with specialized charting capabilities, they can also be emulated in Pine Script as a line indicator.
The Renko emulation indicator in Pine Script calculates the movement of price based on a user-defined brick size. Whenever the price moves up or down by an amount equal to or greater than the brick size, a new level is plotted, indicating a shift in price direction. This approach helps traders visualize significant price moves without the distractions of smaller fluctuations. By plotting the Renko levels as a continuous line and coloring it based on direction, this indicator provides a clean and straightforward representation of market trends.
Traders can use this Renko emulation line to identify potential entry and exit points, as well as to confirm ongoing trends. The simplicity of Renko charts makes them a favorite among those who prefer a minimalist approach to technical analysis. However, it is essential to choose an appropriate brick size that aligns with the volatility of the trading instrument. A smaller brick size may result in frequent signals, while a larger one can smooth out the chart, focusing only on the most substantial price movements. This script offers a flexible solution for incorporating Renko-style analysis into any trading strategy.
Correlation Coefficient Master TableThe Correlation Coefficient Master Table is a comprehensive tool designed to calculate and visualize the correlation coefficient between a selected base asset and multiple other assets over various time periods. It provides traders and analysts with a clear understanding of the relationships between assets, enabling them to analyze trends, diversification opportunities, and market dynamics. You can define key parameters such as the base asset’s data source (e.g., close price), the assets to compare against (up to six symbols), and multiple lookback periods for granular analysis.
The indicator calculates the covariance and normalizes it by the product of the standard deviations. The correlation coefficient ranges from -1 to +1, with +1 indicating a perfect positive relationship, -1 a perfect negative relationship, and 0 no relationship.
You can specify the lookback periods (e.g., 15, 30, 90, or 120 bars) to tailor the calculation to their analysis needs. The results are visualized as both a line plot and a table. The line plot shows the correlation over the primary lookback period (the Chart Length), which can be used to inspect a certain length close up, or could be used in conjunction with the table to provide you with five lookback periods at once for the same base asset. The dynamically created table provides a detailed breakdown of correlation values for up to six target assets across the four user-defined lengths. The table’s cells are formatted with rounded values and color-coded for easy interpretation.
This indicator is ideal for traders, portfolio managers, and market researchers who need an in-depth understanding of asset interdependencies. By providing both the numerical correlation coefficients and their visual representation, users can easily identify patterns, assess diversification strategies, and monitor correlations across multiple timeframes, making it a valuable tool for decision-making.
Fibonacci Trend - Aynet1. Inputs
lookbackPeriod: Defines the number of bars to consider for calculating swing highs and lows. Default is 20.
fibLevel1 to fibLevel5: Fibonacci retracement levels to calculate price levels (23.6%, 38.2%, 50%, 61.8%, 78.6%).
useTime: Enables or disables time-based Fibonacci projections.
riskPercent: Defines the percentage of risk for trading purposes (currently not used in calculations).
2. Functions
isSwingHigh(index): Identifies a swing high at the given index, where the high of that candle is higher than both its previous and subsequent candles.
isSwingLow(index): Identifies a swing low at the given index, where the low of that candle is lower than both its previous and subsequent candles.
3. Variables
swingHigh and swingLow: Store the most recent swing high and swing low prices.
swingHighTime and swingLowTime: Store the timestamps of the swing high and swing low.
fib1 to fib5: Fibonacci levels based on the difference between swingHigh and swingLow.
4. Swing Point Detection
The script checks if the last bar is a swing high or swing low using the isSwingHigh() and isSwingLow() functions.
If a swing high is detected:
The high price is stored in swingHigh.
The timestamp of the swing high is stored in swingHighTime.
If a swing low is detected:
The low price is stored in swingLow.
The timestamp of the swing low is stored in swingLowTime.
5. Fibonacci Levels Calculation
If both swingHigh and swingLow are defined, the script calculates the Fibonacci retracement levels (fib1 to fib5) based on the price difference (priceDiff = swingHigh - swingLow).
6. Plotting Fibonacci Levels
Fibonacci levels (fib1 to fib5) are plotted as horizontal lines using the line.new() function.
Labels (e.g., "23.6%") are added near the lines to indicate the level.
Lines and labels are color-coded:
23.6% → Blue
38.2% → Green
50.0% → Yellow
61.8% → Orange
78.6% → Red
7. Filling Between Fibonacci Levels
The plot() function creates lines for each Fibonacci level.
The fill() function is used to fill the space between two levels with semi-transparent colors:
Blue → Between fib1 and fib2
Green → Between fib2 and fib3
Yellow → Between fib3 and fib4
Orange → Between fib4 and fib5
8. Time-Based Fibonacci Projections
If useTime is enabled:
The time difference (timeDiff) between the swing high and swing low is calculated.
Fibonacci time projections are added based on multiples of 23.6%.
If the current time reaches a projected time, a label (e.g., "T1", "T2") is displayed near the high price.
9. Trading Logic
Two placeholder variables are defined for trading logic:
longCondition: Tracks whether a condition for a long trade is met (currently not implemented).
shortCondition: Tracks whether a condition for a short trade is met (currently not implemented).
These variables can be extended to define entry/exit signals based on Fibonacci levels.
How It Works
Detect Swing Points: It identifies recent swing high and swing low points on the chart.
Calculate Fibonacci Levels: Based on the swing points, it computes retracement levels.
Visualize Levels: Plots the levels on the chart with labels and fills between them.
Time Projections: Optionally calculates time-based projections for future price movements.
Trading Opportunities: The framework provides tools for detecting potential reversal or breakout zones using Fibonacci levels.
Forex Hammer and Hanging Man StrategyThe strategy is based on two key candlestick chart patterns: Hammer and Hanging Man. These chart patterns are widely used in technical analysis to identify potential reversal points in the market. Their relevance in the Forex market, known for its high liquidity and volatile price movements, is particularly pronounced. Both patterns provide insights into market sentiment and trader psychology, which are critical in currency trading, where short-term volatility plays a significant role.
1. Hammer:
• Typically occurs after a downtrend.
• Signals a potential trend reversal to the upside.
• A Hammer has:
• A small body (close and open are close to each other).
• A long lower shadow, at least twice as long as the body.
• No or a very short upper shadow.
2. Hanging Man:
• Typically occurs after an uptrend.
• Signals a potential reversal to the downside.
• A Hanging Man has:
• A small body, similar to the Hammer.
• A long lower shadow, at least twice as long as the body.
• A small or no upper shadow.
These patterns are a manifestation of market psychology, specifically the tug-of-war between buyers and sellers. The Hammer reflects a situation where sellers tried to push the price down but were overpowered by buyers, while the Hanging Man shows that buyers failed to maintain the upward movement, and sellers could take control.
Relevance of Chart Patterns in Forex
In the Forex market, chart patterns are vital tools because they offer insights into price action and market sentiment. Since Forex trading often involves large volumes of trades, chart patterns like the Hammer and Hanging Man are important for recognizing potential shifts in market momentum. These patterns are a part of technical analysis, which aims to forecast future price movements based on historical data, relying on the psychology of market participants.
Scientific Literature on the Relevance of Candlestick Patterns
1. Behavioral Finance and Candlestick Patterns:
Research on behavioral finance supports the idea that candlestick patterns, such as the Hammer and Hanging Man, are relevant because they reflect shifts in trader psychology and sentiment. According to Lo, Mamaysky, and Wang (2000), patterns like these could be seen as representations of collective investor behavior, influenced by overreaction, optimism, or pessimism, and can often signal reversals in market trends.
2. Statistical Validation of Chart Patterns:
Studies by Brock, Lakonishok, and LeBaron (1992) explored the profitability of technical analysis strategies, including candlestick patterns, and found evidence that certain patterns, such as the Hammer, can have predictive value in financial markets. While their study primarily focused on stock markets, their findings are generally applicable to the Forex market as well.
3. Market Efficiency and Candlestick Patterns:
The efficient market hypothesis (EMH) posits that all available information is reflected in asset prices, but some studies suggest that markets may not always be perfectly efficient, allowing for profitable exploitation of certain chart patterns. For instance, Jegadeesh and Titman (1993) found that momentum strategies, which often rely on price patterns and trends, could generate significant returns, suggesting that patterns like the Hammer or Hanging Man may provide a slight edge, particularly in short-term Forex trading.
Testing the Strategy in Forex Using the Provided Script
The provided script allows traders to test and evaluate the Hammer and Hanging Man patterns in Forex trading by entering positions when these patterns appear and holding the position for a specified number of periods. This strategy can be tested to assess its performance across different currency pairs and timeframes.
1. Testing on Different Timeframes:
• The effectiveness of candlestick patterns can vary across different timeframes, as market dynamics change with the level of detail in each timeframe. Shorter timeframes may provide more frequent signals, but with higher noise, while longer timeframes may produce more reliable signals, but with fewer opportunities. This multi-timeframe analysis could be an area to explore to enhance the strategy’s robustness.
2. Exit Strategies:
• The script incorporates an exit strategy where positions are closed after holding them for a specified number of periods. This is useful for testing how long the reversal patterns typically take to play out and when the optimal exit occurs for maximum profitability. It can also help to adjust the exit logic based on real-time market behavior.
Conclusion
The Hammer and Hanging Man patterns are widely recognized in technical analysis as potential reversal signals, and their application in Forex trading is valuable due to the market’s high volatility and liquidity. This strategy leverages these candlestick patterns to enter and exit trades based on shifts in market sentiment and psychology. Testing and optimization, as offered by the script, can help refine the strategy and improve its effectiveness.
For further refinement, it could be valuable to consider combining candlestick patterns with other technical indicators or using multi-timeframe analysis to confirm patterns and increase the probability of successful trades.
References:
• Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation. The Journal of Finance, 55(4), 1705-1770.
• Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. The Journal of Finance, 47(5), 1731-1764.
• Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
This provides a theoretical basis for the use of candlestick patterns in trading, supported by academic literature and research on market psychology and efficiency.
Center of Candle Trendline### **Center of Candle Trendline**
This script dynamically plots a trendline through the center of each candlestick's body. The "center" is calculated as the average of the open and close prices for each candle. The trendline updates in real-time as new candles form, providing a clean and straightforward way to track the market's midline movement.
#### **Features:**
1. **Dynamic Trendline:** The trendline connects the center points of consecutive candlestick bodies, giving a clear visual representation of price movements.
2. **Accurate Center Calculation:** The center is determined as `(open + close) / 2`, ensuring the trendline reflects the true midpoint of each candlestick body.
3. **Real-Time Updates:** The trendline updates automatically as new bars form, keeping your chart up to date with the latest price action.
4. **Customization-Ready:** Adjust the line’s color, width, or style easily to fit your chart preferences.
#### **How to Use:**
- Add this script to your chart to monitor the price movement relative to the center of candlestick bodies.
- Use the trendline to identify trends, reversals, or price consolidation zones.
#### **Applications:**
- **Trend Analysis:** Visualize how the market trends around the center of candlesticks.
- **Reversal Identification:** Detect potential reversal zones when the price deviates significantly from the trendline.
- **Support and Resistance Zones:** Use the trendline as a dynamic support or resistance reference.
This tool is perfect for traders who want a clean and minimalistic approach to tracking price action. Whether you're a beginner or an experienced trader, this script provides valuable insights without overwhelming your chart.
#### **Note:**
This is not a standalone trading strategy but a visual aid to complement your analysis. Always combine it with other tools and techniques for better trading decisions.
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Feel free to tweak this description based on your preferences or style!
Position sizerPosition Sizer Indicator
The "Position Sizer" indicator is a practical tool for traders who need to quickly and accurately calculate position sizes based on their account balance, risk tolerance, and stop-loss level. It ensures real-time updates and supports multiple asset classes like Forex, Indexes, Metals, and Crypto.
Key Features
Dynamic Position Sizing: Automatically calculates position sizes based on the current market price and stop-loss level.
Stop-Loss Adjustment: Allows users to drag the stop-loss level directly on the chart, dynamically updating the position size.
Interactive Table: A single click on the table activates the draggable stop-loss level for easy adjustments.
Multi-Asset Compatibility: Fully supports Forex, Indexes, Metals, and Crypto trading pairs.
How to Use
Deactivate the Indicator:
Turn off the indicator to make it inactive.
Set the Stop-Loss Price:
Copy the stop-loss price or use a price near the current market price.
Reactivate the indicator after inserting the stop-loss price.
Adjust the Stop-Loss Level if needed:
Click once on the table to enable the stop-loss level for dragging.
Move the stop-loss line as needed—position sizes will automatically recalculate.
Important Disclaimer
Verification Required: Always verify the calculated position size before executing trades.
Broker Confirmation: Double-check the point size for your trading symbol with your broker to avoid errors in calculations.
User Responsibility: The creator assumes no responsibility for any trading decisions made based on this indicator.
This tool helps streamline position management, ensuring you can focus on executing your trades with accuracy and speed. Always confirm your calculations before trading.
Enhanced Renko Channel with Emulation and SMA by Dr DevendraThis indicator combines a dynamic Renko-based channel with emulated Renko bricks and a customizable Simple Moving Average (SMA). It provides traders with a powerful tool for identifying trends, visualizing price movement within a Renko framework, and overlaying critical moving average signals.
Features:
Renko Channel:
A Gaussian-based midline with adjustable poles and sampling periods.
True Range-based dynamic channel boundaries.
Visual trend identification with color-coded channel fills.
Renko Emulation:
Emulated Renko brick levels with adjustable brick sizes.
Dynamic brick plotting based on price action.
Simple Moving Average (SMA):
Configurable length and source (e.g., close, hlc3, etc.).
Dynamic color changes based on SMA slope (uptrend or downtrend).
Customizable Inputs:
Adjustable parameters for the channel, Renko emulation, and SMA settings.
Options for reduced lag and fast response modes in the Renko channel.
Improved RSI Trend Sniper | JeffreyTimmermansImproved RSI Trend Sniper
This indicator, the "Improved RSI Trend Sniper" is a sophisticated tool designed to enhance market trend analysis by integrating customizable RSI thresholds with advanced moving average options and refined visual enhancements.
Key Features
Advanced Moving Average Options:
The indicator now supports multiple moving average types: SMA, EMA, SMMA, WMA, VWMA, LSMA, HMA, and ALMA, offering greater flexibility in trend analysis.
Users can customize the moving average length for precise momentum detection.
Enhanced Momentum Detection:
Upgraded to allow dynamic calculation of momentum based on user-selected moving averages.
Conditions for bullish or bearish momentum now consider changes in the chosen moving average rather than a fixed EMA, improving accuracy.
Visual Upgrades:
A gradient-based trend fill with multiple opacity layers provides a visually appealing representation of bullish and bearish trends.
New dashboard integration displays key market information, including the ticker, timeframe, and current trend (bullish or bearish).
Improved Signal Customization:
Customizable colors and labels for bullish and bearish signals ensure easy identification on the chart.
Enhanced settings for showing or hiding labels and trend fills
Refined Alerts System:
Alerts are now generated for bullish and bearish conditions with customized messages for better responsiveness.
Alerts can be triggered once per bar close, making them more reliable.
What's New:
RSI and MA Customization: Users can define thresholds and moving average settings, providing more control over trend analysis.
Dashboard Integration: Displays real-time updates directly on the chart for improved situational awareness.
Visual Enhancements: Introduced gradient fills for trend regions, making trends more distinct.
Expanded Moving Average Options: Allows for tailored strategies using various MA calculation methods.
Alert Messaging: Streamlined notifications for actionable insights.
How It Works
Momentum Analysis:
Bullish momentum is detected when the RSI crosses above the bullish threshold and the moving average is increasing.
Bearish momentum is flagged when the RSI falls below the bearish threshold, and the moving average is decreasing.
Trend Visualization:
Bullish trends are highlighted with gradient shades of green, while bearish trends use shades of red.
Labels appear on the chart to mark key turning points.
Tailored for Different Trading Styles
The Improved RSI Trend Sniper is versatile and adaptable, catering to traders with various time horizons:
Long-Term Adjustments: For traders focusing on long-term trends, increasing the RSI length and moving average period allows the indicator to smooth out minor price fluctuations and highlight sustained momentum. Selecting slower-moving averages like the SMA or LSMA further filters out short-term noise, ensuring signals align with broader market trends.
Medium-Term Adjustments: Swing traders can use a balanced RSI length (e.g., 14–20) and a medium moving average period (e.g., 20–50) to capture actionable signals within the mid-range market cycles. The inclusion of options like EMA or SMMA ensures quicker reactions to price changes while maintaining moderate sensitivity to reversals.
Short-Term Adjustments: For day traders or scalpers, using a shorter RSI period (e.g., 7–10) alongside faster moving averages such as the HMA or ALMA can provide quicker signals for high-frequency trading. These adjustments enhance the ability to react swiftly to immediate market shifts, ideal for fast-paced trading environments.
By customizing the indicator’s settings to align with your trading timeframe, the Improved RSI Trend Sniper ensures accurate and relevant insights, empowering traders to optimize their strategies across any market condition.
Dashboard Details
Provides an at-a-glance view of market data for the current ticker and timeframe.
The Improved RSI Trend Sniper takes the original tool to the next level, offering a more comprehensive, customizable, and visually intuitive approach to market trend analysis. Perfect for traders looking to refine their strategies with actionable insights.
-Jeffrey
Relative Performance Indicator by ComLucro - 2025_V01The "Relative Performance Indicator by ComLucro - 2025_V01" is a powerful tool designed to analyze an asset's performance relative to a benchmark index over multiple timeframes. This indicator provides traders with a clear view of how their chosen asset compares to a market index in short, medium, and long-term periods.
Key Features:
Customizable Lookback Periods: Analyze performance across three adjustable periods (default: 20, 50, and 200 bars).
Relative Performance Analysis: Calculate and visualize the difference in percentage performance between the asset and the benchmark index.
Dynamic Summary Label: Displays a detailed breakdown of the asset's and index's performance for the latest bar.
User-Friendly Interface: Includes customizable colors and display options for clear visualization.
How It Works:
The script fetches closing prices of both the asset and a benchmark index.
It calculates percentage changes over the selected lookback periods.
The indicator then computes the relative performance difference between the asset and the index, plotting it on the chart for easy trend analysis.
Who Is This For?:
Traders and investors who want to compare an asset’s performance against a benchmark index.
Those looking to identify trends and deviations between an asset and the broader market.
Disclaimer:
This tool is for educational purposes only and does not constitute financial or trading advice. Always use it alongside proper risk management strategies and backtest thoroughly before applying it to live trading.
Chart Recommendation:
Use this script on clean charts for better clarity. Combine it with other technical indicators like moving averages or trendlines to enhance your analysis. Ensure you adjust the lookback periods to match your trading style and the timeframe of your analysis.
Additional Notes:
For optimal performance, ensure the benchmark index's data is available on your TradingView subscription. The script uses fallback mechanisms to avoid interruptions when index data is unavailable. Always validate the settings and test them to suit your trading strategy.
Crypto Market Caps / Global GDP %This indicator compares the total market capitalization of various crypto sectors to the global Gross Domestic Product (GDP), expressed as a percentage. The purpose of this indicator is to provide a visual representation of the relative size of the crypto market compared to the global economy, allowing traders and analysts to understand how the market is growing in relation to the overall economy.
Key Features
Crypto Market Caps -
TOTAL: Represents the total market capitalization of all cryptocurrencies.
TOTAL3: Represents the market capitalization of all cryptocurrencies, excluding Bitcoin and Ethereum.
OTHERS: Represents the market capitalization of all cryptocurrencies excluding the top 10.
Global GDP -
The indicator uses a combination of GDP data from multiple regions across the world, including:
GDP from the EU, North America (NA), and other regions.
GDP data from Asia, Latin America (LATAM), and the Middle East & North Africa (MENA).
Percentage Representation -
The market caps (TOTAL, TOTAL3, OTHERS) are compared to the global GDP, and the result is expressed as a percentage. This allows you to easily see how the size of the cryptocurrency market compares to the entire global economy at any given time.
Plotting and Visualization
The indicator plots the market cap to global GDP ratio for each category (TOTAL, TOTAL3, OTHERS) on the chart.
You can choose which plots to display through user inputs.
The percentage scale makes it easy to compare how much of the global GDP is represented by different parts of the crypto market.
Labels can be added for additional clarity, showing the exact percentage value on the chart.
How to Use
The indicator provides a clear view of the cryptocurrency market's relative size compared to the global economy.
Higher values indicate that the crypto market (or a segment of it) is becoming a larger portion of the global economy.
Lower values suggest the crypto market is still a smaller segment of the global economic activity.
User Inputs
TOTAL/GlobalGDP: Toggle visibility for the total market capitalization of all cryptocurrencies.
TOTAL3/GlobalGDP: Toggle visibility for the market cap of cryptocurrencies excluding Bitcoin and Ethereum.
OTHERS/GlobalGDP: Toggle visibility for the market cap of cryptocurrencies excluding the top 10.
Labels: Enable or disable the display of labels showing the exact percentage values.
Practical Use Cases
Market Sentiment: Gauge the overall market sentiment and potential growth relative to global economic conditions.
Investment Decisions: Help identify when the crypto market is becoming more or less significant in the context of the global economy.
Macro Analysis: Combine this indicator with other macroeconomic indicators to gain deeper insights into the broader economic landscape.
By providing an easy-to-understand percentage representation, this indicator offers valuable insights for anyone interested in tracking the relationship between cryptocurrency market cap and global economic activity.
GL_Prev Week HighThe GL_Prev Week High Indicator is a powerful tool designed to enhance your trading analysis by displaying the previous week's high price directly on your chart. With clear and customizable visuals, this indicator helps traders quickly identify critical price levels, enabling more informed decision-making.
Key Features:
Previous Week's High Line:
Displays the previous week's high as a red line on your chart for easy reference.
Customizable Horizontal Line:
Includes a white horizontal line for enhanced clarity, with adjustable length, color, and width settings.
All-Time High Tracking:
Automatically tracks the all-time high from the chart's history and places a dynamic label above it.
Real-Time Updates:
The indicator updates in real-time to ensure accuracy as new bars are added.
User Inputs for Personalization:
Adjust the left and right span of the horizontal line.
Customize line width and color to suit your preferences.
Use Case:
This indicator is ideal for traders looking to integrate the previous week's high as a key support or resistance level in their trading strategy. Whether you are analyzing trends, identifying breakout zones, or planning entry/exit points, this tool provides valuable insights directly on the chart.
How to Use:
Add the indicator to your chart.
Customize the settings (line length, width, and color) through the input panel to match your preferences.
Use the red line to track the previous week's high and the label to monitor all-time highs effortlessly.
License:
This script is shared under the Mozilla Public License 2.0. Feel free to use and adapt the script as per the license terms.
Adaptive Momentum Reversion StrategyThe Adaptive Momentum Reversion Strategy: An Empirical Approach to Market Behavior
The Adaptive Momentum Reversion Strategy seeks to capitalize on market price dynamics by combining concepts from momentum and mean reversion theories. This hybrid approach leverages a Rate of Change (ROC) indicator along with Bollinger Bands to identify overbought and oversold conditions, triggering trades based on the crossing of specific thresholds. The strategy aims to detect momentum shifts and exploit price reversions to their mean.
Theoretical Framework
Momentum and Mean Reversion: Momentum trading assumes that assets with a recent history of strong performance will continue in that direction, while mean reversion suggests that assets tend to return to their historical average over time (Fama & French, 1988; Poterba & Summers, 1988). This strategy incorporates elements of both, looking for periods when momentum is either overextended (and likely to revert) or when the asset’s price is temporarily underpriced relative to its historical trend.
Rate of Change (ROC): The ROC is a straightforward momentum indicator that measures the percentage change in price over a specified period (Wilder, 1978). The strategy calculates the ROC over a 2-period window, making it responsive to short-term price changes. By using ROC, the strategy aims to detect price acceleration and deceleration.
Bollinger Bands: Bollinger Bands are used to identify volatility and potential price extremes, often signaling overbought or oversold conditions. The bands consist of a moving average and two standard deviation bounds that adjust dynamically with price volatility (Bollinger, 2002).
The strategy employs two sets of Bollinger Bands: one for short-term volatility (lower band) and another for longer-term trends (upper band), with different lengths and standard deviation multipliers.
Strategy Construction
Indicator Inputs:
ROC Period: The rate of change is computed over a 2-period window, which provides sensitivity to short-term price fluctuations.
Bollinger Bands:
Lower Band: Calculated with a 18-period length and a standard deviation of 1.7.
Upper Band: Calculated with a 21-period length and a standard deviation of 2.1.
Calculations:
ROC Calculation: The ROC is computed by comparing the current close price to the close price from rocPeriod days ago, expressing it as a percentage.
Bollinger Bands: The strategy calculates both upper and lower Bollinger Bands around the ROC, using a simple moving average as the central basis. The lower Bollinger Band is used as a reference for identifying potential long entry points when the ROC crosses above it, while the upper Bollinger Band serves as a reference for exits, when the ROC crosses below it.
Trading Conditions:
Long Entry: A long position is initiated when the ROC crosses above the lower Bollinger Band, signaling a potential shift from a period of low momentum to an increase in price movement.
Exit Condition: A position is closed when the ROC crosses under the upper Bollinger Band, or when the ROC drops below the lower band again, indicating a reversal or weakening of momentum.
Visual Indicators:
ROC Plot: The ROC is plotted as a line to visualize the momentum direction.
Bollinger Bands: The upper and lower bands, along with their basis (simple moving averages), are plotted to delineate the expected range for the ROC.
Background Color: To enhance decision-making, the strategy colors the background when extreme conditions are detected—green for oversold (ROC below the lower band) and red for overbought (ROC above the upper band), indicating potential reversal zones.
Strategy Performance Considerations
The use of Bollinger Bands in this strategy provides an adaptive framework that adjusts to changing market volatility. When volatility increases, the bands widen, allowing for larger price movements, while during quieter periods, the bands contract, reducing trade signals. This adaptiveness is critical in maintaining strategy effectiveness across different market conditions.
The strategy’s pyramiding setting is disabled (pyramiding=0), ensuring that only one position is taken at a time, which is a conservative risk management approach. Additionally, the strategy includes transaction costs and slippage parameters to account for real-world trading conditions.
Empirical Evidence and Relevance
The combination of momentum and mean reversion has been widely studied and shown to provide profitable opportunities under certain market conditions. Studies such as Jegadeesh and Titman (1993) confirm that momentum strategies tend to work well in trending markets, while mean reversion strategies have been effective during periods of high volatility or after sharp price movements (De Bondt & Thaler, 1985). By integrating both strategies into one system, the Adaptive Momentum Reversion Strategy may be able to capitalize on both trending and reverting market behavior.
Furthermore, research by Chan (1996) on momentum-based trading systems demonstrates that adaptive strategies, which adjust to changes in market volatility, often outperform static strategies, providing a compelling rationale for the use of Bollinger Bands in this context.
Conclusion
The Adaptive Momentum Reversion Strategy provides a robust framework for trading based on the dual concepts of momentum and mean reversion. By using ROC in combination with Bollinger Bands, the strategy is capable of identifying overbought and oversold conditions while adapting to changing market conditions. The use of adaptive indicators ensures that the strategy remains flexible and can perform across different market environments, potentially offering a competitive edge for traders who seek to balance risk and reward in their trading approaches.
References
Bollinger, J. (2002). Bollinger on Bollinger Bands. McGraw-Hill Professional.
Chan, L. K. C. (1996). Momentum, Mean Reversion, and the Cross-Section of Stock Returns. Journal of Finance, 51(5), 1681-1713.
De Bondt, W. F., & Thaler, R. H. (1985). Does the Stock Market Overreact? Journal of Finance, 40(3), 793-805.
Fama, E. F., & French, K. R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research.
Improved Target Oscillator | JeffreyTimmermansImproved Target Oscillator
The Improved Target Oscillator is a versatile technical indicator that identifies trends, reversals, and market momentum. Designed to work effectively across various markets, this oscillator excels at capturing longer-term market trends, making it ideal for traders focused on sustained price movements. By using advanced mathematical techniques and dynamic visualization, the oscillator provides actionable insights, helping traders navigate complex market environments with confidence.
Key features include:
A dynamic oscillator line to reflect market momentum and reversals.
Clear gradient-based coloring to distinguish between bullish and bearish conditions.
Signal highlights for potential entry and exit points based on trend shifts.
This tool is particularly useful for identifying extended trends and provides a clean, intuitive interface for assessing market dynamics.
Improvements in the Improved Target Oscillator
Smoothing Feature:
Added an optional smoothing toggle, allowing the use of SMA or EMA for reducing noise.
Provides flexibility through adjustable smoothing length, enhancing clarity in choppy markets.
Alerts for Trade Opportunities:
Built-in alert conditions for bullish and bearish signals.
Allows traders to receive notifications when critical trend changes occur, ensuring they never miss an opportunity.
Customizable to integrate seamlessly into trading workflows.
Enhanced Visualization:
Introduced dynamic gradients for bullish and bearish conditions with improved customization options.
Provides clearer differentiation of momentum changes, improving interpretability.
Signal Highlights:
Improved visual cues for bullish and bearish signals with precise dot indicators.
Offers better alignment with oscillator momentum shifts, ensuring actionable insights.
Adaptability:
Tuned for use in capturing longer-term market trends, emphasizing its effectiveness in identifying sustained movements.
Adjusted oscillator sensitivity with a levels multiplier for better scalability across various market conditions.
Level Markers:
Clearer delineation of key oscillator levels, including half and full normalized levels for improved context.
A neutral line explicitly plotted for easier trend and momentum identification.
Summary
The Improved Target Oscillator combines a sophisticated mathematical foundation with practical visualization enhancements to deliver a more intuitive and precise tool for market analysis. With added flexibility, improved signals, and tailored features for longer-term trends, this oscillator is an essential resource for traders looking to refine their strategies.
-Jeffrey
Candle Counter by ComLucro - Multi-Timefram - 2025_V01Candle Counter by ComLucro - Multi-Timeframe - 2025_V01
The Candle Counter by ComLucro - Multi-Timeframe is a highly customizable tool designed to help traders monitor the number of candles across various timeframes directly on their charts. Whether you're analyzing trends or tracking specific market behaviors, this indicator provides a seamless and efficient way to enhance your technical analysis.
Key Features:
Flexible Timeframe Selection: Track candle counts on yearly, monthly, weekly, daily, or hourly intervals to suit your trading style.
Dynamic Label Positioning: Choose to display labels above or below candles, offering greater control over your chart layout.
Customizable Colors: Adjust label text colors to match your chart's aesthetics and improve visibility.
Clean and Organized Visualization: Automatically generates labels for each candle without overcrowding your chart.
How It Works:
Select a Timeframe: Choose from yearly, monthly, weekly, daily, or hourly intervals based on your analysis needs.
Automatic Counting: The indicator calculates and displays the number of candles for the selected period directly on your chart.
Label Customization: Adjust the position (above or below the candles) and color of the labels to align with your preferences.
Why Use This Indicator?
This script is perfect for traders who need a clear and visual representation of candle counts in specific timeframes. Whether you're monitoring trends, evaluating price action, or developing strategies, the Candle Counter by ComLucro adapts to your needs and helps you make informed decisions.
Disclaimer:
This script is intended for educational and informational purposes only. It does not constitute financial advice. Always practice responsible trading and ensure this tool aligns with your strategies and risk management practices.
About ComLucro:
ComLucro is dedicated to providing traders with practical tools and educational resources to improve decision-making in the financial markets. Discover other scripts and strategies developed to enhance your trading experience.
