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.
Coefficient
Comprehensive Correlation Meter with Multiple MarketsThe Comprehensive Correlation Meter is designed to provide traders and investors with insights into the relationships between multiple financial instruments. This script expands upon an existing idea on TradingView about correlation by introducing the ability to analyze the correlation between three markets, offering deeper insights into market relationships. It helps users understand how these markets move in relation to each other, aiding in risk management and portfolio diversification.
Key Features:
Multiple Market Analysis: This script allows you to analyze the correlation between your primary market and two other selected markets.
Customizable Inputs: Users can select any symbols for the reference and third markets, and these selections must be confirmed before use.
Correlation Coefficients: Calculates and plots the correlation coefficients for:
Current Market vs. Reference Market
Third Market vs. Reference Market
Current Market vs. Third Market
An average correlation of all three markets combined.
Visual Aids: Plots reference lines at +1, 0, and -1 to indicate maximum positive correlation, no correlation, and maximum negative correlation.
How It Works:
Input Symbols: Select the symbols for the reference and third markets. The current market is based on the chart you are viewing.
Data Collection: The script collects the closing prices of the selected markets and calculates the percentage changes.
Correlation Calculation: Using the collected data, the script computes the covariance and standard deviations to determine the correlation coefficients.
Visualization: The correlation coefficients and covariances are plotted for visual analysis.
How to Use:
Select Symbols:
Use the input fields to specify the reference and third market symbols. Confirm your selections to proceed.
Customize Display:
Choose whether to display the covariance, reference market, current market, and third market.
Select which correlation coefficients to display.
Interpret Results:
A correlation coefficient close to +1 indicates a strong positive correlation.
A coefficient close to -1 indicates a strong negative correlation.
A coefficient around 0 indicates little to no correlation.
Use these insights to manage risk and diversify your portfolio effectively.
Example Use Case:
Suppose you are trading the S&P 500 and want to understand its correlation with the NASDAQ 100 and a particular stock, such as Apple. By setting the S&P 500 as the reference market, the NASDAQ 100 as the third market, and observing the current market (Apple), you can see how these instruments move in relation to each other. This can help you decide on hedging strategies or identify opportunities for diversification. However this is Not a Financial advise
Multi Delta-Agnostic Correlation Coefficient (tartigradia)Display three DACC plots simultaneously, to visualize both directional (up on top, down at bottom) and adirectional DACC (in the middle) simultaneously.
Delta Agnostic Correlation calculates a correlation between two symbols based only on the sign of their changes using a Sign Test (en.m.wikipedia.org), regardless of the amplitude of price change. Compared to a standard Pearson correlation (quantitative test), Sign Test correlations (discrete test) are highly sensitive to directional change with 0 lag, at the expense of lacking sensitivity to quantity correlation (ie, it does not matter if changes are big or small).
Hence, this Delta-Agnostic Correlation Coefficient (DCC or DACC) indicator is better used to detect early changes in correlations, and then confirmation with a typical Pearson correlation or a non-parametric Spearman test or Mutual Information (all three are quantitative tests, hence accounting for quantity and not just direction) can allow to be more sensitive to quantities too and hence be a robust combination to demonstrate strong correlations both in direction and amplitude.
Adequate statistical significance testing, using a two-sided binomial statistical test, is also implemented. Note however that one assumption of the sign test may here be violated: independence of observations for each symbol. If you assume the market is not acting on a random walk, then there is a temporal autocorrelation, and this biases the sign test. However, in practice, the test works well enough.
The directional variants of the test allow to test the correlation hypothesis only if the index symbol goes into one direction. For example, if we suspect that the index symbol is correlated with the current symbol but only when the index symbol is bullish, we can select "Up" to test this hypothesis. Note that given the specificities of how directional and adirectional tests differ in how they work, the default fill is different: zero-value fill for adirectional test to simulate how price action tend to lose momentum during market close periods, previous DCC_MA (= no change in DCC value) during both market close periods and when the direction is opposite for the directional variants of the test, so that while the market is moving opposite, we don't lose the statistical significance built up to now, otherwise it would be nonsensical (for the directional tests).
For more information on the theory behind, see the original DACC indicator, which is the same script but with only one plot:
Delta-Agnostic Correlation Coefficient (alt)Calculate a sort of correlation between two symbols based only on the sign of their changes, regardless of the amplitude of price change.
When positive, the two symbols tend to move together. When negative, the symbols move in opposite directions.
Since there is no significance calculation, and that the result is binary, keep in mind that correlation will always tend to go towards 1 or -1 even when there is no correlation. To reduce this issue, an EMA or SMA is applied to smooth out transitions: SMA smoothes over the selected length period but adds lag, whereas EMA smoothes amplitude without any additional lag. Hence, to know if the correlation is true or not, try to look at the amplitude and the number of consecutive days the correlation is maintained (both quantities are related), because when the correlation is spurious, it will tend to switch more or less alternatively between 1 and -1 and hence will hover around 0, whereas if the correlation is true, it will get further away from 0 and closer to 1 or -1.
In addition, since there is some time lag for the correlation to switch sign, the area is colored to know the current candle's correlation, regardless of past data's correlation: blue is a positive correlation (1), yellow is negative. The coloring can allow to know a trend reversal early on, but it's noisy.
Finally, symbols with closing days are better accounted for, with the correlation set to 0 on closed days (e.g., on week-ends), and the area is then colored in gray to signal that there is no new correlation data.
This is an improved fork over the original indicator by alexjvale, please show him some love if you like this work:
Correlation with Matrix TableCorrelation coefficient is a measure of the strength of the relationship between two values. It can be useful for market analysis, cryptocurrencies, forex and much more.
Since it "describes the degree to which two series tend to deviate from their moving average values" (1), first of all you have to set the length of these moving averages. You can also retrieve the values from another timeframe, and choose whether or not to ignore the gaps.
After selecting the reference ticker, which is not dependent from the chart you are on, you can choose up to eight other tickers to relate to it. The provided matrix table will then give you a deeper insight through all of the correlations between the chosen symbols.
Correlation values are scored on a scale from 1 to -1
A value of 1 means the correlation between the values is perfect.
A value of 0 means that there is no correlation at all.
A value of -1 indicates that the correlation is perfectly opposite.
For a better view at a glance, eight level colors are available and it is possible to modify them at will. You can even change level ranges by setting their threshold values. The background color of the matrix's cells will change accordingly to all of these choices.
The default threshold values, commonly used in statistics, are as follows:
None to weak correlation: 0 - 0.3
Weak to moderate correlation: 0.3 - 0.5
Moderate to high correlation: 0.5 - 0.7
High to perfect correlation: 0.7 - 1
Remember to be careful about spurious correlations, which are strong correlations without a real causal relationship.
(1) www.tradingview.com
Delta Agnostic Correlation CoefficientVisually see how well a symbol tracks another's movements, without taking price deltas into account.
For example, a 1% move on the index and a 5% move on the target will return a DCC value of 1. An index move of 0.5% on the index and a 10% move on the target will also return a DCC value of 1. The same happens for downward moves.
The SMA value can be set to smooth the curve. A larger value creates a smoother curve.
Ehlers Distance Coefficient Filter [CC]The Distance Coefficient Filter was created by John Ehlers and this is one of his more unknown moving averages. It works well because in an uptrend or downtrend it behaves more like a trailing stop system but it also deals with issues like pullbacks pretty quickly. I think it works well with the default values but let me know if you find a more profitable system. Buy when the indicator turns green and sell when it turns red.
Let me know if there are any other indicators you would like to see me publish!
Ehlers Hurst Coefficient [CC]The Hurst Coefficient was created by John Ehlers (Cycle Analytics For Traders pgs 67-68) and this is a very useful indicator to tell you if the stock is in a uptrend or downtrend. Feel free to change the length to experiment and to adjust to your needs. Buy when the indicator line is green and sell when it is red.
Let me know if there are other indicators you would like to see me publish or if you want something custom done!
Hashem Correlation CoefficientCorrelation Coefficient
Core Code from: www.tradingview.com
This indicator Show Correlation between the Current Ticker & timeframe and a Customizable Ticker. After adding the indicator you can change the second ticker in the settings.
The Correlation Coeff is between -1 to 1 which 1 means 100% correlation and -1 means -100% correlation ( Inverse Correlation ).
The color of the area changes when:
Blue : CC > 0.5
Aqua : CC > 0.75
Purple : CC < -0.5
Red : CC < -0.75
Correlation Matrix by DaveattHi everyone
A co-pinescripter friend told me this was impossible to do and we bet a free dinner tomorrow. Guess who's going to be invited to a very fancy restaurant tomorrow :) :) :) (hint: not him)
What's the today script is about?
This script is based on this MT4 correlation matrix
Asset correlation is a measure of how investments move in relation to one another and when. ... Under what is known as modern portfolio theory, you can reduce the overall risk in an investment portfolio and even boost your overall returns by investing in asset combinations that are not correlated.
I did it because it wasn't existing before with this format. What I discovered was only correlations shown as plot lines... #this #is #not #pretty
How does it work?
The correlation matrix will not be based on the current asset of the chart BUT will be based on the current timeframe (confusing? if yes, read it again until you'll get it)
- Numbers of bars back: numbers of bars used for the correlation calculation
- High correlation level: Correlation upper threshold. If above, then the correlation will be green
- Low correlation level: Correlation lower threshold. If below, then the correlation will be red
If the correlation is between the high and low levels, then it will be displayed in orange
- FOREX/INDEX: You can choose between displaying the correlation matrix between 3 FOREX or 3 INDEX assets
Also...
So far the scale doesn't respond too well to the matrix so you'll have to adapt the scale manually. I'll publish a V2 if I'll find a way to solve this issue from the code directly #new #challenge
A quick final note on why I'm sharing so much?
It challenges me to think out of the norm, get out of my bubble and explore areas of Pinescript that I still don't know. This "a script a day" challenge allows me to speed up my learning curve on Pinescript by a billion factor (and I get a few interesting gigs as well)
Let's bring this indicator to 100 LIKES guys !!!!! I think it deserves it, don't you think? :)
PS
Before all copy/pasters will add a version with crypto tomorrow, don't bother, I already did it and will post it in a few minutes for FREE :p
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Be sure to hit the thumbs up as it shows me that I'm not doing this for nothing and will motivate to deliver more quality content in the future.
- I'm an officially approved PineEditor/LUA/MT4 approved mentor on codementor. You can request a coaching with me if you want and I'll teach you how to build kick-ass indicators and strategies
Jump on a 1 to 1 coaching with me
- You can also hire for a custom dev of your indicator/strategy/bot/chrome extension/python
Ehlers Distance Coefficient FilterThis indicator was described by John F. Ehlers in his book "Rocket Science for Traders" (2001, Chapter 18: Ehlers Filters).
Correlate 3 - Correlation IndicatorThe code in contains a simple correlation indicator that can be used as an alternative to Tradingview’s built-in “Correlation Coefficient” indicator. The indicator allows users to correlate up to 3 separate instruments on the same subplot. This allows you, for example, to easily see the correlation of your instrument with stocks, bonds and FX. Alternatively, a user can also see the correlation with sector, industry peers or any other data available in Tradingview.
Features
Level Guides to easily see the key correlation coefficient levels
Multi-instrument:
Coefficient of Variation [DW]This is a simple gauge of volatility using the Coefficient of Variation.
COV is calculated by dividing standard deviation of price by the expected (average) price.
Custom color scheme indicates increases and decreases in volatility, which is indicated when the COV forms new half period highs and lows.
CorrelationGraph shows level of correlation between current source and another one and track current value of it. User can select source for comparison, graph period and number of candles for calculation, enter level of significal correlation (+-0.65 by default). Grapf contains 4 plots: Correlation - current level of correlation, Zero line , +Corr_level - minimum level of significant positive correlation, -Corr_level -maximum level of significant negative correlation between 2 sources.
