Dynamic Market Correlation Analyzer (DMCA) v1.0Description
The Dynamic Market Correlation Analyzer (DMCA) is an advanced TradingView indicator designed to provide real-time correlation analysis between multiple assets. It offers a comprehensive view of market relationships through correlation coefficients, technical indicators, and visual representations.
Key Features
- Multi-asset correlation tracking (up to 5 symbols)
- Dynamic correlation strength categorization
- Integrated technical indicators (RSI, MACD, DX)
- Customizable visualization options
- Real-time price change monitoring
- Flexible timeframe selection
## Use Cases
1. **Portfolio Diversification**
- Identify highly correlated assets to avoid concentration risk
- Find negatively correlated assets for hedging strategies
- Monitor correlation changes during market events
2. Pairs Trading
- Detect correlation breakdowns for potential trading opportunities
- Track correlation strength for pair selection
- Monitor technical indicators for trade timing
3. Risk Management
- Assess portfolio correlation risk in real-time
- Monitor correlation shifts during market stress
- Identify potential portfolio vulnerabilities
4. **Market Analysis**
- Study sector relationships and rotations
- Analyze cross-asset correlations (e.g., stocks vs. commodities)
- Track market regime changes through correlation patterns
Components
Input Parameters
- **Timeframe**: Custom timeframe selection for analysis
- **Length**: Correlation calculation period (default: 20)
- **Source**: Price data source selection
- **Symbol Selection**: Up to 5 customizable symbols
- **Display Options**: Table position, text color, and size settings
Technical Indicators
1. **Correlation Coefficient**
- Range: -1 to +1
- Strength categories: Strong/Moderate/Weak (Positive/Negative)
2. **RSI (Relative Strength Index)**
- 14-period default setting
- Momentum comparison across assets
3. **MACD (Moving Average Convergence Divergence)**
- Standard settings (12, 26, 9)
- Trend direction indicator
4. **DX (Directional Index)**
- Trend strength measurement
- Based on DMI calculations
Visual Components
1. **Correlation Table**
- Symbol identifiers
- Correlation coefficients
- Correlation strength descriptions
- Price change percentages
- Technical indicator values
2. **Correlation Plot**
- Real-time correlation visualization
- Multiple correlation lines
- Reference levels at -1, 0, and +1
- Color-coded for easy identification
Installation and Setup
1. Load the indicator on TradingView
2. Configure desired symbols (up to 5)
3. Adjust timeframe and calculation length
4. Customize display settings
5. Enable/disable desired components (table, plot, RSI)
Best Practices
1. **Symbol Selection**
- Choose related but distinct assets
- Include a mix of asset classes
- Consider market cap and liquidity
2. **Timeframe Selection**
- Match timeframe to trading strategy
- Consider longer timeframes for strategic analysis
- Use shorter timeframes for tactical decisions
3. **Interpretation**
- Monitor correlation changes over time
- Consider multiple timeframes
- Combine with other technical analysis tools
- Account for market conditions and volatility
Performance Notes
- Calculations update in real-time
- Resource usage scales with number of active symbols
- Historical data availability may affect initial calculations
Version History
- v1.0: Initial release with core functionality
- Multi-symbol correlation analysis
- Technical indicator integration
- Customizable display options
Future Enhancements (Planned)
- Additional technical indicators
- Advanced correlation algorithms
- Enhanced visualization options
- Custom alert conditions
- Statistical significance testing
Correlation
Z-Score Pairs TradingTitle: Z-Score Pairs Trading Indicator
Description:
This indicator implements a Z-score based pairs trading strategy, allowing traders to identify potential statistical arbitrage opportunities between two selected assets.
Key Features:
- Calculates Z-score for the price difference between any two user-selected symbols
- Visualizes Z-score with customizable thresholds for signals
- Generates long and short signals based on extreme Z-score values
- Adaptable to various markets including stocks, ETFs, and commodities
How It Works:
1. The indicator calculates the price difference between two selected symbols.
2. It then computes the Z-score of this difference, showing how far the current spread deviates from its historical average.
3. When the Z-score exceeds set thresholds (default ±2), the indicator generates trading signals.
Settings:
- Symbol A and Symbol B: Select any two tradable symbols to compare
- Lookback Period: Number of periods for calculating the moving average and standard deviation
Interpretation:
- Z-score above 2: Potential short signal (pair is likely overextended)
- Z-score below -2: Potential long signal (pair is likely oversold)
- Z-score between -2 and 2: Normal trading range, no signals
Visual Aids:
- Blue line: Z-score
- Dashed lines: Threshold levels at 0, ±1, and ±2
- Green triangles: Long signals
- Red triangles: Short signals
Disclaimer:
This indicator is for educational and research purposes only. Trading carries a high level of risk. Always conduct your own analysis and manage your risk appropriately before entering any trade.
Made by @marekfleisi
[ AlgoChart ] - Pearson Index CorrelationCorrelation Indicator (Pearson Index)
The correlation indicator measures the strength and direction of the relationship between two financial assets using the Pearson Index.
Correlation values range from +100 to -100, where:
+100 indicates perfect positive correlation, meaning the two assets tend to move in the same direction.
-100 indicates perfect negative correlation, where the two assets move in opposite directions.
The neutral zone ranges from +25% to -25%, suggesting that the asset movements are independent, with no clear correlation between them.
Interpreting Correlation Levels:
Correlation above +75%: The two assets tend to move similarly and in the same direction. This may indicate a risk of overexposure if both assets are traded in the same direction, as their movements will be very similar, increasing the likelihood of double losses or gains.
Correlation below -75%: The two assets tend to move similarly but in opposite directions. This correlation level can be useful for strategies that benefit from opposing movements between assets, such as trading pairs with inverse dynamics.
Practical Use of the Indicator:
Risk management: Use the indicator to monitor asset correlations before opening positions. High correlation may indicate you are duplicating exposure, as two highly correlated assets tend to move similarly. This helps avoid excessive risk and improves portfolio diversification.
Statistical Arbitrage: During moments of temporary decorrelation between two assets, the indicator can be used for statistical arbitrage strategies. In such cases, you can take advantage of the divergence by opening positions and closing them when the correlation returns to higher or positive levels, thus potentially profiting from the reconvergence of movements.
While the correlation indicator provides valuable insights into asset relationships, it is most effective when used in conjunction with other concepts and tools. On its own, it may offer limited relevance in trading decisions.
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.
Kenji Indicator Version 2.0KenJi Indicator Version 2.0
Indicator Class : Average analysis/trend following
Trading type : Any
Time frame : Any
Purpose : Trend-based trading
Level of aggressiveness : Flexible
Introduction
The basic rule of trading is as follows: "trend is your friend." Means, it is extremely important to follow the current market sentiments rather than resisting them. Following this principle allows a trader to feel as comfortable as possible during the trading: positions typically are in a profit zone and there is no psychological pressure of a negative financial result that often leads to hasty position closures.
Despite the advantages of trend-following strategies, many traders struggle to accurately identify the prevailing trend and market sentiments, resulting in bad trading decisions and, consequently, unfavorable trading outcomes.
To address these challenges, streamline the analysis process, and enhance the overall quality of trading decisions, our team of analysts has developed The KenJi Indicator Version 2.0.
About the KenJi Indicator Version 2.0
The KenJi Indicator Version 2.0 offers a novel approach to traditional average-based analysis. Many conventional strategies relying on averages tend to generate numerous false signals, especially in “flat” markets where frequent crossovers and shifts in direction are common. This reduces the overall effectiveness of average analysis.
The KenJi Indicator Version 2.0 addresses these issues by incorporating a unique algorithm, which combines correlation and moving average analysis to avoid the pitfalls of traditional methods. It accurately identifies market conditions—indicated by colors: red for a downtrend, blue for an uptrend, and green for a “flat” market—thereby improving the quality of signals and helping traders manage trends more effectively.
The KenJi Indicator Version 2.0 indicator not only identifies optimal entry points but also assists in timing exits for profit-taking. Moreover, it assesses the aggressiveness of signals, making it suitable for both novice and experienced traders.
Trading Rules
Using the KenJi Indicator Version 2.0 is straightforward. When the price enters the buy or sell zone—represented by a blue or red area between the fast and slow averages—it generates a signal to enter a position. This position remains active until the market condition changes (such as a shift from a downtrend to “flat”) or until a close signal appears, indicated by a significant divergence shown by a blue or red cross.
Indicator Structure
The KenJi Indicator Version 2.0 consists of colored zones, level lines and stop crosses:
Trend Zones : These are color-coded (blue, red, or green) to highlight trend conditions and entry points.
Level Lines : The lines indicate the nearest support/resistance lines (red for resistance, blue for support). Available for 4H time-frame and below
Stop Crosses : Blue or Red crosses are displayed on the Chart to show the moments of extreme price divergence from the current trend. A good moment to fix profits.
For ease of use, the indicator shows buy and sell signals directly on the chart.
Signal Types:
Standard : Uses the basic lot size for trades.
Aggressive : Uses double the standard lot size for higher risk/reward trades.
Profit zones are marked by blue/red x-crosses: red x-crosses indicate "sell" take-profit zones, while blue x-crosses indicate "buy" take-profit zones.
Alerts and Notifications
The indicator includes built-in alerts and notifications, ensuring traders don’t miss any "buy" or "sell" signals.
Input Parameters
The KenJi Indicator Version 2.0 offers several input parameters for customization:
Slow Average Period : Defines the period for the slow average. Longer periods provide a more stable, conservative response to price changes.
Fast Average Period : Defines the period for the fast average. Similar to the slow average, a longer period provides more conservative signals.
Correlation Period : Used to calculate the Pearson correlation coefficient and estimate the relationship between the fast and slow averages, improving trend identification.
Divergence Sensitivity : Determines the placement of take-profit zones, with higher values increasing the distance of these zones.
Access to the KenJi Indicator Version 2.0
For more information or to request access to the Kenji 2.0 Indicator, please send inquiries via private messages.
Correlation Clusters [LuxAlgo]The Correlation Clusters is a machine learning tool that allows traders to group sets of tickers with a similar correlation coefficient to a user-set reference ticker.
The tool calculates the correlation coefficients between 10 user-set tickers and a user-set reference ticker, with the possibility of forming up to 10 clusters.
🔶 USAGE
Applying clustering methods to correlation analysis allows traders to quickly identify which set of tickers are correlated with a reference ticker, rather than having to look at them one by one or using a more tedious approach such as correlation matrices.
Tickers belonging to a cluster may also be more likely to have a higher mutual correlation. The image above shows the detailed parts of the Correlation Clusters tool.
The correlation coefficient between two assets allows traders to see how these assets behave in relation to each other. It can take values between +1.0 and -1.0 with the following meaning
Value near +1.0: Both assets behave in a similar way, moving up or down at the same time
Value close to 0.0: No correlation, both assets behave independently
Value near -1.0: Both assets have opposite behavior when one moves up the other moves down, and vice versa
There is a wide range of trading strategies that make use of correlation coefficients between assets, some examples are:
Pair Trading: Traders may wish to take advantage of divergences in the price movements of highly positively correlated assets; even highly positively correlated assets do not always move in the same direction; when assets with a correlation close to +1.0 diverge in their behavior, traders may see this as an opportunity to buy one and sell the other in the expectation that the assets will return to the likely same price behavior.
Sector rotation: Traders may want to favor some sectors that are expected to perform in the next cycle, tracking the correlation between different sectors and between the sector and the overall market.
Diversification: Traders can aim to have a diversified portfolio of uncorrelated assets. From a risk management perspective, it is useful to know the correlation between the assets in your portfolio, if you hold equal positions in positively correlated assets, your risk is tilted in the same direction, so if the assets move against you, your risk is doubled. You can avoid this increased risk by choosing uncorrelated assets so that they move independently.
Hedging: Traders may want to hedge positions with correlated assets, from a hedging perspective, if you are long an asset, you can hedge going long a negatively correlated asset or going short a positively correlated asset.
Grouping different assets with similar behavior can be very helpful to traders to avoid over-exposure to those assets, traders may have multiple long positions on different assets as a way of minimizing overall risk when in reality if those assets are part of the same cluster traders are maximizing their risk by taking positions on assets with the same behavior.
As a rule of thumb, a trader can minimize risk via diversification by taking positions on assets with no correlations, the proposed tool can effectively show a set of uncorrelated candidates from the reference ticker if one or more clusters centroids are located near 0.
🔶 DETAILS
K-means clustering is a popular machine-learning algorithm that finds observations in a data set that are similar to each other and places them in a group.
The process starts by randomly assigning each data point to an initial group and calculating the centroid for each. A centroid is the center of the group. K-means clustering forms the groups in such a way that the variances between the data points and the centroid of the cluster are minimized.
It's an unsupervised method because it starts without labels and then forms and labels groups itself.
🔹 Execution Window
In the image above we can see how different execution windows provide different correlation coefficients, informing traders of the different behavior of the same assets over different time periods.
Users can filter the data used to calculate correlations by number of bars, by time, or not at all, using all available data. For example, if the chart timeframe is 15m, traders may want to know how different assets behave over the last 7 days (one week), or for an hourly chart set an execution window of one month, or one year for a daily chart. The default setting is to use data from the last 50 bars.
🔹 Clusters
On this graph, we can see different clusters for the same data. The clusters are identified by different colors and the dotted lines show the centroids of each cluster.
Traders can select up to 10 clusters, however, do note that selecting 10 clusters can lead to only 4 or 5 returned clusters, this is caused by the machine learning algorithm not detecting any more data points deviating from already detected clusters.
Traders can fine-tune the algorithm by changing the 'Cluster Threshold' and 'Max Iterations' settings, but if you are not familiar with them we advise you not to change these settings, the defaults can work fine for the application of this tool.
🔹 Correlations
Different correlations mean different behaviors respecting the same asset, as we can see in the chart above.
All correlations are found against the same asset, traders can use the chart ticker or manually set one of their choices from the settings panel. Then they can select the 10 tickers to be used to find the correlation coefficients, which can be useful to analyze how different types of assets behave against the same asset.
🔶 SETTINGS
Execution Window Mode: Choose how the tool collects data, filter data by number of bars, time, or no filtering at all, using all available data.
Execute on Last X Bars: Number of bars for data collection when the 'Bars' execution window mode is active.
Execute on Last: Time window for data collection when the `Time` execution window mode is active. These are full periods, so `Day` means the last 24 hours, `Week` means the last 7 days, and so on.
🔹 Clusters
Number of Clusters: Number of clusters to detect up to 10. Only clusters with data points are displayed.
Cluster Threshold: Number used to compare a new centroid within the same cluster. The lower the number, the more accurate the centroid will be.
Max Iterations: Maximum number of calculations to detect a cluster. A high value may lead to a timeout runtime error (loop takes too long).
🔹 Ticker of Reference
Use Chart Ticker as Reference: Enable/disable the use of the current chart ticker to get the correlation against all other tickers selected by the user.
Custom Ticker: Custom ticker to get the correlation against all the other tickers selected by the user.
🔹 Correlation Tickers
Select the 10 tickers for which you wish to obtain the correlation against the reference ticker.
🔹 Style
Text Size: Select the size of the text to be displayed.
Display Size: Select the size of the correlation chart to be displayed, up to 500 bars.
Box Height: Select the height of the boxes to be displayed. A high height will cause overlapping if the boxes are close together.
Clusters Colors: Choose a custom colour for each cluster.
Relative Strength according to Oster (RSO)Overview:
Relative Strength according to Oster (RSO) is an innovative tool that redefines how traders assess an asset's market strength. Moving beyond traditional indicators, RSO offers a sophisticated and highly responsive measure of an asset's potential to continue performing well. By integrating groundbreaking methodologies, RSO equips traders with unparalleled insights into market dynamics, making it an essential tool for anyone looking to stay ahead in today's fast-paced trading environment.
Understanding RSL (Relative Strength according to Levy):
At its core, Relative Strength according to Levy (RSL) is a powerful concept rooted in the idea that an asset currently exhibiting strength is more likely to maintain or even enhance that strength in the future. RSL calculates this by comparing an asset's current price to its moving average, providing a clear picture of its relative performance over time. The further its value is above 1, the higher the market momentum and vice versa. This relationship to the moving average is crucial, as it indicates not just where the asset stands today but also its trajectory in the context of historical performance. The ability to identify assets that consistently outperform is a game-changer for traders, and RSL has long been a cornerstone in this pursuit.
RSO vs. Traditional RSL: A Leap Forward
The RSO takes the traditional RSL concept and propels it into new territory with its innovative correlation-based approach. This is where RSO truly shines, offering a unique and sophisticated analysis that goes far beyond the basics.
Why RSO is Revolutionary:
Correlation Adjustment: The RSO doesn’t just measure an asset’s strength in isolation. Instead, it adjusts its readings based on how closely the asset's price movements correlate with a chosen benchmark. This groundbreaking feature ensures that the RSO is not just reactive to past performance but also predictive of how the asset might behave relative to the broader market, adding a layer of precision that is unparalleled in traditional strength indicators.
Superior Strength Option: With the RSO, traders have the option to include superior strength factors, adding another dimension of insight. This feature allows for more stable and reliable long-term signals. On the flip side, those who prefer a more dynamic trading style can opt to exclude this factor for more frequent, shorter-term signals. This level of customization is rare and sets the RSO apart as a truly adaptable tool.
Enhanced Market Insights: RSO’s correlation-based approach doesn’t just show how strong an asset is—it reveals how that strength is likely to develop in relation to the benchmark's underlying trends. This isn’t merely about comparing performance; it’s about understanding the asset’s potential trajectory in a much broader market context. Such insight is invaluable for making informed, strategic trading decisions.
Practical Application:
The RSO isn’t just innovative in theory; it’s designed for practical, real-world trading. Traders can set customized alerts based on RSO’s readings, ensuring they’re always aware of key buy or sell signals as they occur. The flexibility to include or exclude superior strength factors means that RSO can be tailored to fit any trading style, whether focused on long-term investments or short-term opportunities.
Conclusion:
In conclusion, the Relative Strength according to Oster (RSO) is more than just an indicator; it’s a breakthrough in market analysis. By integrating correlation adjustments and offering unparalleled customization options, RSO provides traders with insights that are both deeper and more actionable than ever before. This innovative tool is designed to empower traders, giving them the edge they need to succeed in an increasingly complex market landscape. Whether you’re a seasoned trader or just starting out, the RSO is a must-have tool for navigating market trends with confidence and precision.
Intermarket Correlation TableThe Correlation Coefficient is used to measure the correlation between two sets of data. In the trading world, the Correlation Coefficient is a measure of the correlation between two data sets of financial instruments. The correlation between two financial instruments is the degree in which they are related. Correlation is based on a scale of 1 to -1. The closer the Correlation Coefficient is to 1, the higher their positive correlation. The instruments will move up and down together. The closer the Correlation coefficient is to -1, the more they move in opposite directions. A value at 0 indicates that there is no correlation.
This indicator uses the built in ta.correlation function to calculate the correlation coefficient between DXY and NQ, ES, YM, US10Y, and ZN respectively. It then presents the data in a customizable table that is view as an overlay on your chart.
Adjust the length of the correlation factor to calculate higher time frame correlation.
Asset background changes based on current candle direction.
Coefficient background color changes based on whether the assets are properly correlated.
DXY is inversely correlated to NQ, ES, YM, and ZN.
DXY is directly correlated to US10Y.
The colors are reflected as such.
Symbol CorrelationThe "Symbol Correlation" indicator calculates and displays the correlation between the chosen symbol's price and another selected source over a specified period. It also includes a moving average (SMA) of this correlation to provide a smoothed view of the relationship.
Why SMA and Table Display ?
The inclusion of SMA (Simple Moving Average) with adjustable length (SMA Length) enhances the indicator's utility by smoothing out short-term fluctuations in correlation, allowing for clearer trend identification. The SMA helps to visualize the underlying trend in correlation, making it easier to spot changes and patterns over time.
The table display of the correlation SMA value offers a concise summary of this trend. By showcasing the current correlation SMA alongside its historical values, traders can quickly gauge the relationship's strength relative to previous periods.
Interpreting the Indicator:
1. Correlation Values: The primary plot shows the raw correlation values between the symbol's price and the specified source. A value of 1 indicates a perfect positive correlation, -1 signifies a perfect negative correlation, and 0 suggests no linear relationship.
2. Correlation SMA: The SMA line represents the average correlation over a defined period (SMA Length). Rising SMA values indicate strengthening correlation trends, while declining values suggest weakening correlations.
3. Choosing SMA Length: Traders can adjust the SMA Length parameter to tailor the moving average to their specific analysis horizon. Shorter SMA lengths react quickly to price changes but may be more volatile, while longer SMA lengths smooth out noise but respond slower to recent changes.
In summary, the "Symbol Correlation" indicator is a valuable tool for assessing the evolving relationship between a symbol's price and an external source. Its use of SMA and tabular presentation facilitates a nuanced understanding of correlation trends, aiding traders in making informed decisions based on market dynamics.
Calculus Free Trend Strategy for Crypto & StocksObjective :
The Correlation Channel Trading Strategy is designed to identify potential entry points based on the relationship between price movements and a correlation channel. The strategy aims to capture trends within the channel while managing risk effectively.
Parameters :
Length: Determines the period for calculating moving averages and the true range, influencing the sensitivity of the strategy to price movements.
Multiplier: Adjusts the width of the correlation channel, providing flexibility to adapt to different market conditions.
Inputs :
Asset Symbol: Allows users to specify the financial instrument for analysis.
Timeframe: Defines the timeframe for data aggregation, enabling customization based on trading preferences.
Plot Correlation Channel: Optional input to visualize the correlation channel on the price chart.
Methodology :
Data Acquisition: The strategy fetches OHLC (Open, High, Low, Close) data for the specified asset and timeframe. In this case we use COINBASE:BTCUSD
Calculation of Correlation Channel: It computes the squared values for OHLC data, calculates the average value (x), and then calculates the square root of x to derive the source value. Additionally, it calculates the True Range as the difference between high and low prices.
Moving Averages: The strategy calculates moving averages (MA) for the source value and the True Range, which form the basis for defining the correlation channel.
Upper and Lower Bands: Using the MA and True Range, the strategy computes upper and lower bands of the correlation channel, with the width determined by the multiplier.
Entry Conditions: Long positions are initiated when the price crosses above the upper band, signaling potential overbought conditions. Short positions are initiated when the price crosses below the lower band, indicating potential oversold conditions.
Exit Conditions: Stop-loss mechanisms are incorporated directly into the entry conditions to manage risk. Long positions are exited if the price falls below a predefined stop-loss level, while short positions are exited if the price rises above the stop-loss level.
Strategy Approach: The strategy aims to capitalize on trends within the correlation channel, leveraging systematic entry signals while actively managing risk through stop-loss orders.
Backtest Details : For the purpose of this test I used the entire data available for BTCUSD Coinbase, with 10% of capital allocation and 0.1% comission for entry/exit(0.2% total). Can be also used with other both directly correlated with current settings of BTC or with new ones
Advantages :
Provides a systematic approach to trading based on quantifiable criteria.
Offers flexibility through customizable parameters to adapt to various market conditions.
Integrates risk management through predefined stop-loss mechanisms.
Limitations :
Relies on historical price data and technical indicators, which may not always accurately predict future price movements.
May generate false signals during periods of low volatility or erratic price behavior.
Requires continuous monitoring and adjustment of parameters to maintain effectiveness.
Conclusion :
The Correlation Channel Trading Strategy offers traders a structured framework for identifying potential entry points within a defined price channel. By leveraging moving averages and true range calculations, the strategy aims to capture trends while minimizing risk through stop-loss mechanisms. While no strategy can guarantee success in all market conditions, the Correlation Channel Trading Strategy provides a systematic approach to trading that can enhance decision-making and risk management for traders.
Inflation CorrelationHeyo fellas,
In today’s dynamic economic landscape, understanding the relationship of market prices to other economical factors like inflation rate is crucial. The Inflation Correlation Indicator is designed to provide traders with a clear visualization of this relationship. By correlating average inflation rates from selected countries with market closing prices, this indicator offers a unique perspective on potential market movements influenced by inflationary trends.
Features:
Country Selection: Choose from the European Union (EU), Germany (DE), or the United States (US) to tailor the correlation analysis to your specific market interest.
Correlation Length Customization: Adjust the correlation length to refine the sensitivity of the indicator to recent inflation data.
Visual Clarity: The correlation histogram changes color based on the direction of the correlation, providing an intuitive understanding of the inflation correlation.
Whether you’re a fundamental analyst seeking to incorporate macroeconomic indicators into your strategy or a trader looking for an edge in inflation-sensitive markets, the Inflation Correlation Indicator is an indispensable tool in your TradingView arsenal.
Thanks for checking this out!
Best regards,
simwai
Historical Correlation [LuxAlgo]The Historical Correlation tool aims to provide the historical correlation coefficients of up to 10 pairs of user-defined tickers starting from a user-defined point in time.
Users can choose to display the historical values as lines or the most recent correlation values as a heat map.
🔶 USAGE
This tool provides historical correlation coefficients, the correlation coefficient between two assets highlight their linear relationship and is always within the range (-1, 1).
It is a simple and easy to use statistical tool, with the following interpretation:
Positive correlation (values close to +1.0): the two assets move in sync, they rise and fall at the same time.
Negative correlation (values close to -1.0): the two assets move in opposite directions: when one goes up, the other goes down and vice versa.
No correlation (values close to 0): the two assets move independently.
The user must confirm the selection of the anchor point in order for the tool to be executed; this can be done directly on the chart by clicking on any bar, or via the date field in the settings panel.
For the parameter Anchor period , the user can choose between the following values NONE, HOURLY, DAILY, WEEKLY, MONTHLY, QUARTERLY and YEARLY. If NONE is selected, there will be no resetting of the calculations, otherwise the calculations will start from the first bar of the new period.
There is a wide range of trading strategies that make use of correlation coefficients between assets, some examples are:
Pair Trading: Traders may wish to take advantage of divergences in the price movements of highly positively correlated assets; even highly positively correlated assets do not always move in the same direction; when assets with a correlation close to +1.0 diverge in their behavior, traders may see this as an opportunity to buy one and sell the other in the expectation that the assets will return to the likely same price behavior.
Sector rotation: Traders may want to favor some sectors that are expected to perform in the next cycle, tracking the correlation between different sectors and between the sector and the overall market.
Diversification: Traders can aim to have a diversified portfolio of uncorrelated assets. From a risk management perspective, it is useful to know the correlation between the assets in your portfolio, if you hold equal positions in positively correlated assets, your risk is tilted in the same direction, so if the assets move against you, your risk is doubled. You can avoid this increased risk by choosing uncorrelated assets so that they move independently.
Hedging: Traders may want to hedge positions with correlated assets, from a hedging perspective, if you are long an asset, you can hedge going long a negative correlated asset or going short a positive correlated asset.
Traders generally need to develop awareness, a key point is to be aware of the relationships between the assets we hold or trade, the historical correlation is an invaluable tool in our arsenal which allows us to make better informed decisions.
On this chart we have an example of historical correlations for several futures markets.
We can clearly see how positively correlated the Nasdaq100 and Dow30 are with the SP500 over the whole period, or how the correlation between the Euro and the SP500 falls from almost +85% to almost -4% since 2021.
As we can see, correlations, like everything else in the market, are not static and vary over time depending on many factors, from macro to technical and everything in between.
🔹 Heatmap
The chart above shows the tool with the default settings and the Drawing Mode set to 'HEATMAP'.
We can see the current correlation between the assets, in this case the FX pairs.
The highest positive correlation is +90% (+0.90) between EURUSD and GBPUSD.
The highest negative correlation is -78% (-0.78) between EURUSD and USDJPY.
The pair with no correlation is AUDUSD and EURCAD with 1% (0.01)
On the above chart we can see the current correlations for the futures markets.
Currently, the assets that are less correlated to the SP500 are NaturalGas and the Euro, the more positive correlations are Nasdaq100 and Dow20, and the more negative correlations are the Yen, Treasury Bonds and 10-Year Notes.
🔶 DETAILS
🔹 Anchor Period
This chart shows the standard FX correlations with the Anchor Period set to `MONTHLY`.
We can clearly see how the calculations restart with the new month, in this case we can clearly see the differences between the correlations from month to month.
Let us look at the correlation coefficient between GBPUSD and USDJPY
In January, their correlation started at close to -100%, rose to close to +50%, only to fall to close to 0% and remain there for the second half of the month.
In February it was -90% in the first few days of the month and is now around -57%.
And between AUDUSD and EURCAD
Last month their correlation was negative for most of the month, reaching -70% and ending around -14%.
This month their correlation has never gone below +21% and at the time of writing is close to +53%.
🔶 SETTINGS
Anchor point: Starting point from which the tool is executed
Anchor period: At the beginning of each new period, the tool will reset the calculations
Pairs from 1 to 10: For each pair of tickers, you can: enable/disable the pair, select the color and specify the two tickers from which you wish to obtain the correlation
🔹 Style
Drawing Mode: Output style, `LINES` will show the historical correlations as lines, `HEATMAP` will show the current correlations with a color gradient from green for correlations near 1 to red for correlations near -1.
Open Interest Inflows & Outflows [LuxAlgo]The Open Interest Inflows & Outflows indicator focuses on highlighting alterations in the overall count of active contracts associated with a specific financial instrument.
The indicator also includes an oscillator highlighting the price sentiment to use in conjunction with the open interest flow sentiment and also includes a rolling correlation of the open interest flow sentiment with a user-selected source.
🔶 USAGE
Open Interest (OI) indicates the total number of active contracts, encompassing both long and short positions, for a specific financial instrument at any given moment. This key indicator helps traders and analysts assess market activity and sentiment.
An increase in open interest generally indicates new money flowing into the market, suggesting increased activity and the potential for a trending market. Conversely, a decrease in open interest indicates that traders are closing their positions, suggesting less interest in that particular contract.
Open Interest Flow Sentiment assesses the correlation between the initiation of new positions (inflows) and the closure of existing positions (outflows) for a particular instrument. Positive values suggest a prevalence of inflows, while negative values signify a prevalence of outflows.
The magnitude of the deviation from zero reflects the extent of dominance, either in inflows or outflows.
Price Sentiment estimates the relationship between the strength of bulls (buyers) and bears (sellers) on an instrument. Positive values indicate higher bull power and negative values indicate higher bear power.
The correlation feature is a key component of the indicator and helps analyze the relationship between trading volume and Open Interest changes. If volume increases along with rising Open Interest, it supports the validity of the price trend.
A divergence between price movement, volume, and Open Interest may signal potential reversals.
🔶 DETAILS
This indicator, based on Dr. Alexander Elder's acclaimed Elder-Ray concept, aids traders in evaluating the strength of both bulls and bears by delving beneath the surface of the markets. It uncovers data not immediately apparent from a superficial glance at prices. The indicator comprises two components: Bull Power and Bear Power.
Considering that the high price of any candle signifies the maximum power of buyers and the low price represents the maximum power of sellers, Elder employs the 13-period Exponential Moving Average (EMA) to depict the average consensus of price value. Bull Power assesses whether buyers can drive prices above the average consensus of value, while Bear Power assesses whether sellers can push prices below this average.
Here are the formulas for Bull Power and Bear Power:
bull_power = high - ema(close, 13)
bear_power = low - ema(close, 13)
This concept is utilized to calculate Open Interest Flow Sentiment and Price Sentiment. The Open Interest Flow Sentiment estimates the relationship between new positions (inflows) and positions being closed (outflows), providing insights into market dynamics. The Price Sentiment, on the other hand, gauges the correlation between price movements and the Elder-Ray components, aiding traders in identifying potential shifts in market sentiment and momentum.
🔶 SETTINGS
🔹Open Interest Inflows & Outflows
OI Sentiment Correlation: toggles the visibility of Open Interest correlation with a variety of sources.
Money Flow Estimates: toggles the visibility of Money Flow Estimates calculated for the last bar.
🔹Style
OI Flow Sentiment: toggles the visibility of Open Interest Flow Sentiment, along with color customization options.
Price Sentiment: toggles the visibility of Price Sentiment, along with color customization options.
Correlation Colors: color customization option for the Correlation Area.
🔹Others
Smoothing: smoothing length applicable for Open Interest Flow Sentiment and Price Sentiment.
🔶 RELATED SCRIPTS
Open-Interest-Chart
Liquidation-Estimates
Thanks to our community for recommending this script. For more conceptual scripts and related content, we welcome you to explore by visiting >>> LuxAlgo-Scripts .
Test - Most correlated assetThis is a simple test to find the most and least correlated assets in a list.
Multi-Market Correlation Explorer [kikfraben]Multi-Market Correlation Explorer
The Multi-Market Correlation Explorer (MMCE) is a powerful tool designed to provide insights into the correlations and relative strength of various financial instruments across different markets. This indicator allows traders and investors to assess the intermarket relationships and potential opportunities by analyzing a set of ten symbols, including indices, commodities, and currencies.
Key Features:
Source Selection:
Choose your preferred data source (e.g., close, open, high, low) for all calculations.
Base Symbol for Correlations:
Define a base symbol (default: BTC/USD) for correlation calculations. The indicator evaluates how other symbols correlate with this base symbol.
Customizable Colors:
Easily identify trends with customizable colors for up and down movements, text, background, and table elements.
Length Inputs:
Tailor the analysis to your needs by adjusting the lengths for correlation calculations and RSI (Relative Strength Index).
Symbols:
Select up to ten symbols from various markets, such as stock indices, bond yields, commodities, and currencies.
Correlation Scores:
Gain insights into the strength and direction of correlations between the base symbol and selected symbols over different time lengths.
Scoring System:
Assign scores based on RSI conditions (1 for RSI > 50, -1 for RSI < 50) to each symbol.
Total Score Calculation:
Calculate a total score for each symbol by combining correlation averages and RSI scores.
Color Formatting:
Visualize correlation strengths through a color-coded system for better interpretation.
How to Use:
Positive total scores suggest potential bullish opportunities, while negative scores may indicate bearish tendencies. Combined with the visual representation of correlation strengths, traders can make informed decisions.
The Multi-Market Correlation Explorer enhances your ability to understand complex market relationships, enabling you to stay ahead of trends and identify potential trading or investment opportunities.
Sector relative strength and correlation by KaschkoThis script provides a quick overview of the relative strength and correlation of the symbols in a sector by showing a line chart of the close prices on a percent scale with all symbols starting at zero at the left side of the chart. It allows a great deal of flexibility in the configuration of the sectors and symbols in it. The standard preset sectors cover the most important futures markets and their symbols.
However, up to ten sectors with up to ten symbols each can be freely configured. Each sector is defined by a single line that has the following format:
Sector name:Symbol suffix:List of comma separated symbols
For example, the first predefined sector is defined as follows.
Energies:1!:CL,HO,NG,RB
1. The name of the sector is "Energies"
2. The suffix is "1!", i.e., to each symbol in the list "1!" is appended to get the continous future for the given symbol root. When using stock, forex or other symbols, simply leave the suffix empty.
3. The list of comma separated symbols is "CL,HO,NG,RB", i.e. crude oil, heating oil, natural gas and gasoline. As the suffix is "1!", the actual symbols whose prices are shown are "CL1!","HO1!","NG1!" and "RB1!"
You can choose to use settlement-as-close and back-adjusted contracts. The sector can also be determined automatically ("Auto-select"). In this case, it is determined to which sector the symbol currently displayed in the main chart belongs and the script displays it in the context of the other symbols in the sector.
By selecting a suitable chart time frame and time range, you can quickly determine which symbols in the sector are stronger or weaker and which are more or less strongly correlated.
The following symbols are best suited for a quick trial, as the sectors are preset for these:
CL1!,ES1!,6A1!,6B1!,6c1!,6E1!,6J1!,6M1!,6N1!,6S1!,GC1!,GF1!,HE1!,HG1!,HO1!,LBR1!,LE1!,NG1!,NQ1!,PA1!,PL1!,RB1!,SI1!,YM1!,ZB1!,ZC1!,ZF1!,ZL1!,ZM1!,ZN1!,ZO1!,ZR1!,ZS1!,ZT1!,ZW1!,CC1!,CT1!,DX1!,KC1!,OJ1!,SB1!,RTY1!
You can also use the script to compare any symbols (e.g. different shares) with each other. Preferably use the "Custom" sector for this.
Quantitative Risk Navigator [kikfraben]📊 Quantitative Risk Navigator - Your Financial Performance GPS
Navigate the complexities of financial markets with confidence using the Quantitative Risk Navigator. This indicator provides you with a comprehensive dashboard to assess and understand the risk and performance of your chosen asset.
📈 Key Features:
Alpha and Beta Analysis: Uncover the outperformance (Alpha) and risk exposure (Beta) of your asset compared to a selected benchmark. Know where your investment stands in the market.
Correlation Insights: Understand the relationship between your asset and its benchmark through a clear visualization of correlation trends over different time lengths.
Risk-Return Metrics: Evaluate risk and return simultaneously with Sharpe and Sortino ratios. Make informed decisions by assessing the reward-to-risk ratio of your investment.
Omega Ratio: Gain deeper insights into your asset's performance by analyzing the Omega Ratio, which highlights the distribution of positive and negative returns.
Customizable Visualization: Tailor your chart to focus on specific metrics and time frames. Choose which metrics to display, allowing you to concentrate on the aspects that matter most to you.
Interactive Metrics Table: A user-friendly metrics table provides a quick overview of key values, including average metrics, enabling you to grasp the financial health of your asset at a glance.
Color-Coded Clarity: The indicator employs color-coded visualizations, making it easy to identify bullish and bearish trends, helping you make rapid and informed decisions.
🛠️ How to Use:
Symbol Selection: Choose your base symbol and preferred data source for analysis.
Risk-Free Rate: Input your risk-free rate to fine-tune calculations.
Length Customization: Adjust the lengths for different metrics to align with your analysis preferences.
Whether you're a seasoned trader or just stepping into the financial world, the Quantitative Risk Navigator empowers you to make strategic decisions by providing a comprehensive view of your asset's risk and return profile. Stay in control of your investments with this powerful financial GPS.
🚀 Start Navigating Your Financial Journey Today!
Supertrend Multiasset Correlation - vanAmsen Hello traders!
I am elated to introduce the "Supertrend Multiasset Correlation" , a groundbreaking fusion of the trusted Supertrend with multi-asset correlation insights. This approach offers traders a nuanced, multi-layered perspective of the market.
The Underlying Concept:
Ever pondered over the term Multiasset Correlation?
In the intricate tapestry of financial markets, assets do not operate in silos. Their movements are frequently intertwined, sometimes palpably so, and at other times more covertly. Understanding these correlations can unlock deeper insights into overarching market narratives and directional trends.
By melding the Supertrend with multi-asset correlations, we craft a holistic narrative. This allows traders to fathom not merely the trend of a lone asset but to appreciate its dynamics within a broader market tableau.
Strategy Insights:
At the core of this indicator is its strategic approach. For every asset, a signal is generated based on the Supertrend parameters you've configured. Subsequently, the correlation of daily price changes is assessed. The ultimate signal on the selected asset emerges from the average of the squared correlations, factoring in their direction. This indicator not only accounts for the asset under scrutiny (hence a correlation of 1) but also integrates 12 additional assets. By default, these span U.S. growth ETFs, value ETFs, sector ETFs, bonds, and gold.
Indicator Highlights:
The "Supertrend Multiasset Correlation" isn't your run-of-the-mill Supertrend adaptation. It's a bespoke concoction, tailored to arm traders with an all-encompassing view of market intricacies, fortified with robust correlation metrics.
Key Features:
- Supertrend Line : A crystal-clear visual depiction of the prevailing market trajectory.
- Multiasset Correlation : Delve into the intricate interplay of various assets and their correlation with your primary instrument.
- Interactive Correlation Table : Nestled at the top right, this table offers a succinct overview of correlation metrics.
- Predictive Insights : Leveraging correlations to proffer predictive pointers, adding another layer of conviction to your trades.
Usage Nuances:
- The bullish Supertrend line radiates in a rejuvenating green hue, indicative of potential upward swings.
- On the flip side, the bearish trajectory stands out in a striking red, signaling possible downtrends.
- A rich suite of customization tools ensures that the chart resonates with your trading ethos.
Parting Words:
While the "Supertrend Multiasset Correlation" bestows traders with a rejuvenated perspective, it's paramount to embed it within a comprehensive trading blueprint. This would include blending it with other technical tools and adhering to stringent risk management practices. And remember, before plunging into live trades, always backtest to fine-tune your strategies.
Quantum Market Strength Indicator (MSI)The Market Strength Indicator (MSI) is yet another in our stable of volume-based indicators, and as such, is a must-have tool for trading virtually any type of market and across a myriad of applications from trend trading to swing trading, scalping, and much more. While its sister indicator, the Currency Strength Indicator (CSI), helps you analyze which currencies are oversold, overbought, correlating, and trending, the MSI or Market Strength Indicator does this also, but in this case, for all markets, including stocks, ETFs, futures, and cryptocurrencies, but with one key difference – VOLUME.
As with our core methodology of volume price analysis, volume adds an entirely new dimension to trading analysis as it reveals the driving pressure behind the price action, be it strong or weak, which are all factored into the algorithm that drives the Market Strength Indicator. But with the MSI indicator, its use and application is only limited by your imagination.
For example, we can use it to see which markets are correlating and which are not so that we might use it as an intraday tool for index futures. And, of course, with knowledge gained from the stock trading and investing program, we could then further validate any analysis by setting each against the top five market cap stocks, for confirmation of strength and to give us more confidence in trading an index future.
And not just index futures, but any futures you care to consider, such as energy, metals, softs, currencies or anything else.
For day traders of stocks, you might wish to see which are correlating with one another and which are not, for example, if you are pairs trading, and also whether a particular stock is moving with the primary futures index. If not, this may be a warning sign. And of course, for ETF traders, we have the SPY, a host of ETFs, and alongside them, the sectors, such as the XLK, the XLE, and more, giving you an instant and powerful insight into sentiment across the entire market complex.
The Market Strength Indicator has much to offer; whether you are a stock investor or day trading scalper, index or ETF trader, swing trader or trend trader, it is all here as the indicator signals in a clear and intuitive way when a stock, future or ETF is overbought or oversold in all timeframes, giving you that potent insight into potential reversals from strong to weak and back again. If you enjoy getting into a trend early and trading reversals, then this is the indicator for you, but if you prefer trading trends – no problem, just jump aboard once the move has some momentum and is underway as displayed by the steepness of the line on the indicator.
It’s all here and so much more, from market correlations to market strength and weakness and in all the timeframes from seconds to months.
And just like its sister indicator, the CSI, the MSI is an oscillator that moves seamlessly from overbought to oversold and back again between a value of 100 at the top and zero at the bottom, with each instrument or market represented with a single-colored line. To help further, we’ve included two regions on the indicator to represent these states at 70 and 30, respectively, but you can change these accordingly and perhaps extend them further to 80 and 20. These levels are purely intended as guides to help provide additional information as to the market state and a potential reversal in due course.
Now, in a single indicator, you have the opportunity to gauge sentiment across multiple markets, whether these are correlating or not, and from there develop a myriad of trading opportunities, or alternatively give you that all-important confidence to dive in, or maintain an existing position. Through its unique algorithm based on volume, it is another indicator only limited by your imagination, and like all our other indicators, one we urge you to use in multiple timeframes.
Triple Ehlers Market StateClear trend identification is an important aspect of finding the right side to trade, another is getting the best buying/selling price on a pullback, retracement or reversal. Triple Ehlers Market State can do both.
Three is always better
Ehlers’ original formulation produces bullish, bearish and trendless signals. The indicator presented here gate stages three correlation cycles of adjustable lengths and degree thresholds, displaying a more refined view of bullish, bearish and trendless markets, in a compact and novel way.
Stick with the default settings, or experiment with the cycle period and threshold angle of each cycle, then choose whether ‘Recent trend weighting’ is included in candle colouring.
John Ehlers is a highly respected trading maths head who may need no introduction here. His idea for Market State was published in TASC June 2020 Traders Tips. The awesome interpretation of Ehlers’ work on which Triple Ehlers Market State’s correlation cycle calculations are based can be found at:
DISCLAIMER: None of this is financial advice.
K's Reversal Indicator IIIK's Reversal Indicator III is based on the concept of autocorrelation of returns. The main theory is that extreme autocorrelation (trending) that coincide with a technical signals such as one from the RSI, may result in a powerful short-term signal that can be exploited.
The indicator is calculated as follows:
1. Calculate the price differential (returns) as the current price minus the previous price.
2. the correlation between the current return and the return from 14 periods ago using a lookback of 14 periods.
3. Calculate a 14-period RSI on the close prices.
To generate the signals, use the following rules:
* A bullish signal is generated whenever the correlation is above 0.60 while the RSI is below 40.
* A bearish signal is generated whenever the correlation is above 0.60 while the RSI is above 60.
Robust Bollinger Bands with Trend StrengthThe "Robust Bollinger Bands with Trend Strength" indicator is a technical analysis tool designed assess price volatility, identify potential trading opportunities, and gauge trend strength. It combines several robust statistical methods and percentile-based calculations to provide valuable information about price movements with Improved Resilience to Noise while mitigating the impact of outliers and non-normality in price data.
Here's a breakdown of how this indicator works and the information it provides:
Bollinger Bands Calculation: Similar to traditional Bollinger Bands, this indicator calculates the upper and lower bands that envelop the median (centerline) of the price data. These bands represent the potential upper and lower boundaries of price movements.
Robust Statistics: Instead of using standard deviation, this indicator employs robust statistical measures to calculate the bands (spread). Specifically, it uses the Interquartile Range (IQR), which is the range between the 25th percentile (low price) and the 75th percentile (high price). Robust statistics are less affected by extreme values (outliers) and data distributions that may not be perfectly normal. This makes the bands more resistant to unusual price spikes.
Median as Centerline: The indicator utilizes the median of the chosen price source (either HLC3 or VWMA) as the central reference point for the bands. The median is less affected by outliers than the mean (average), making it a robust choice. This can help identify the center of price action, which is useful for understanding whether prices are trending or ranging.
Trend Strength Assessment: The indicator goes beyond the standard Bollinger Bands by incorporating a measure of trend strength. It uses a robust rank-based correlation coefficient to assess the relationship between the price source and the bar index (time). This correlation coefficient, calculated over a specified length, helps determine whether a trend is strong, positive (uptrend), negative (down trend), or non-existent and weak. When the rank-based correlation coefficient shifts it indicates exhaustion of a prevailing trend. Trend Strength" indicator is designed to provide statistically valid information about trend strength while minimizing the impact of outliers and data distribution characteristics. The parameter choices, including a length of 14 and a correlation threshold of +/-0.7, considered to offer meaningful insights into market conditions and statistical validity (p-value ,0.05 statistically significant). The use of rank-based correlation is a robust alternative to traditional Pearson correlation, especially in the context of financial markets.
Trend Fill: Based on the robust rank-based correlation coefficient, the indicator fills the area between the upper and lower Bollinger Bands with different colors to visually represent the trend strength. For example, it may use green for an uptrend, red for a down trend, and a neutral color for a weak or ranging market. This visual representation can help traders quickly identify potential trend opportunities. In addition the middle line also informs about the overall trend direction of the median.
Cross Correlation [Kioseff Trading]Hello!
This script "Cross Correlation" calculates up to ~10,000 lag-symbol pair cross correlation values simultaneously!
Cross correlation calculation for 20 symbols simultaneously
+/- Lag Range is theoretically infinite (configurable min/max)
Practically, calculate up to 10000 lag-symbol pairs
Results can be sorted by greatest absolute difference or greatest sum
Ability to "isolate" the symbol on your chart and check for cross correlation against a list of symbols
Script defaults to stock pairs when on a stock, Forex pairs when on a Forex pair, crypto when on a crypto coin, futures when on a futures contract.
A custom symbol list can be used for cross correlation checking
Can check any number of available historical data points for cross correlation
Practical Assessment
Ideally, we can calculate cross correlation to determine if, in a list of assets, any of the assets frequently lead or lag one another.
Example
Say we are comparing the log returns for the previous 10 days for SPY and XLU.
*A single time-interval corresponds to the timeframe of your chart i.e. 1-minute chart = 1-minute time interval. We're using days for this example.
(Example Results)
A lag value (k) +/-3 is used.
The cross correlation (normalized) for k = +3 is -0.787
The cross correlation (normalized) for k = -3 is 0.216
A positive "k" value indicates the correlation when Asset A (SPY) leads Asset B (XLU)
A negative "k" value indicates the correlation when Asset B (XLU) leads Asset A (SPY)
A normalized cross correlation of -0.787 for k = +3 indicates an "adequately strong" negative relationship when SPY leads XLU by 3 days.
When SPY increases or decreases - XLU frequently moves in the opposite direction 3 days later.
A cross correlation value of 0.216 at k = −3 indicates a "weak" positive correlation when XLU leads SPY by 3 days.
There's a slight tendency for SPY to move in the same direction as XLU 3 days later.
After the cross-correlation score is normalized it will fall between -1 and 1.
A cross-correlation score of 1 indicates a perfect directional relationship between asset A and asset B at the corresponding lag (k).
A cross correlation of -1 indicates a perfect inverse relationship between asset A and asset B at the corresponding lag (k).
A cross correlation of 0 indicates no correlation at the corresponding lag (k).
The image above shows the primary usage for the script!
The image above further explains the data points located in the table!
The image above shows the script "isolating" the symbol on my chart and checking the cross correlation between the symbol and a list of symbols!
Wrapping Up
With this information, hopefully you can find some meaningful lead-lag relationships amongst assets!
Thank you for checking this out (:
