Mulakan

Correlation

Multi-Asset Performance [Spaghetti] - By LeviathanThis indicator visualizes the cumulative percentage changes or returns of 30 symbols over a given period and offers a unique set of tools and data analytics for deeper insight into the performance of different assets. Multi Asset Performance indicator (also called “Spaghetti”) makes it easy to monitor the changes in Price, Open Interest, and On Balance Volume across multiple assets simultaneously, distinguish assets that are overperforming or underperforming, observe the relative strength of different assets or currencies, use it as a tool for identifying mean reversion opportunities and even for constructing pairs trading strategies, detect "risk-on" or "risk-off" periods, evaluate statistical relationships between assets through metrics like correlation and beta, construct hedging strategies, trade rotations and much more. Start by selecting a time period (e.g., 1 DAY) to set the interval for when data is reset. This will provide insight into how price, open interest, and on-balance volume change over your chosen period. In the settings, asset selection is fully customizable, allowing you to create three groups of up to 30 tickers each. These tickers can be displayed in a variety of styles and colors. Additional script settings offer a range of options, including smoothing values with a Simple Moving Average (SMA), highlighting the top or bottom performers, plotting the group mean, applying heatmap/gradient coloring, generating a table with calculations like beta, correlation, and RSI, creating a profile to show asset distribution around the mean, and much more. One of the most important script tools is the screener table, which can display: 🔸 Percentage Change (Represents the return or the percentage increase or decrease in Price/OI/OBV over the current selected period) 🔸 Beta (Represents the sensitivity or responsiveness of asset's returns to the returns of a benchmark/mean. A beta of 1 means the asset moves in tandem with the market. A beta greater than 1 indicates the asset is more volatile than the market, while a beta less than 1 indicates the asset is less volatile. For example, a beta of 1.5 means the asset typically moves 150% as much as the benchmark. If the benchmark goes up 1%, the asset is expected to go up 1.5%, and vice versa.) 🔸 Correlation (Describes the strength and direction of a linear relationship between the asset and the mean. Correlation coefficients range from -1 to +1. A correlation of +1 means that two variables are perfectly positively correlated; as one goes up, the other will go up in exact proportion. A correlation of -1 means they are perfectly negatively correlated; as one goes up, the other will go down in exact proportion. A correlation of 0 means that there is no linear relationship between the variables. For example, a correlation of 0.5 between Asset A and Asset B would suggest that when Asset A moves, Asset B tends to move in the same direction, but not perfectly in tandem.) 🔸 RSI (Measures the speed and change of price movements and is used to identify overbought or oversold conditions of each asset. The RSI ranges from 0 to 100 and is typically used with a time period of 14. Generally, an RSI above 70 indicates that an asset may be overbought, while RSI below 30 signals that an asset may be oversold.) ⚙️ Settings Overview: ◽️ Period Periodic inputs (e.g. daily, monthly, etc.) determine when the values are reset to zero and begin accumulating again until the period is over. This visualizes the net change in the data over each period. The input "Visible Range" is auto-adjustable as it starts the accumulation at the leftmost bar on your chart, displaying the net change in your chart's visible range. There's also the "Timestamp" option, which allows you to select a specific point in time from where the values are accumulated. The timestamp anchor can be dragged to a desired bar via Tradingview's interactive option. Timestamp is particularly useful when looking for outperformers/underperformers after a market-wide move. The input positioned next to the period selection determines the timeframe on which the data is based. It's best to leave it at default (Chart Timeframe) unless you want to check the higher timeframe structure of the data. ◽️ Data The first input in this section determines the data that will be displayed. You can choose between Price, OI, and OBV. The second input lets you select which one out of the three asset groups should be displayed. The symbols in the asset group can be modified in the bottom section of the indicator settings. ◽️ Appearance You can choose to plot the data in the form of lines, circles, areas, and columns. The colors can be selected by choosing one of the six pre-prepared color palettes. ◽️ Labeling This input allows you to show/hide the labels and select their appearance and size. You can choose between Label (colored pointed label), Label and Line (colored pointed label with a line that connects it to the plot), or Text Label (colored text). ◽️ Smoothing If selected, this option will smooth the values using a Simple Moving Average (SMA) with a custom length. This is used to reduce noise and improve the visibility of plotted data. ◽️ Highlight If selected, this option will highlight the top and bottom N (custom number) plots, while shading the others. This makes the symbols with extreme values stand out from the rest. ◽️ Group Mean This input allows you to select the data that will be considered as the group mean. You can choose between Group Average (the average value of all assets in the group) or First Ticker (the value of the ticker that is positioned first on the group's list). The mean is then used in calculations such as correlation (as the second variable) and beta (as a benchmark). You can also choose to plot the mean by clicking on the checkbox. ◽️ Profile If selected, the script will generate a vertical volume profile-like display with 10 zones/nodes, visualizing the distribution of assets below and above the mean. This makes it easy to see how many or what percentage of assets are outperforming or underperforming the mean. ◽️ Gradient If selected, this option will color the plots with a gradient based on the proximity of the value to the upper extreme, zero, and lower extreme. ◽️ Table This section includes several settings for the table's appearance and the data displayed in it. The "Reference Length" input determines the number of bars back that are used for calculating correlation and beta, while "RSI Length" determines the length used for calculating the Relative Strength Index. You can choose the data that should be displayed in the table by using the checkboxes. ◽️ Asset Groups This section allows you to modify the symbols that have been selected to be a part of the 3 asset groups. If you want to change a symbol, you can simply click on the field and type the ticker of another one. You can also show/hide a specific asset by using the checkbox next to the field.
Penunjuk Pine Script™
oleh LeviathanCapital
73
Advanced Weighted Residual Arbitrage AnalyzerThe Advanced Weighted Residual Arbitrage Analyzer is a sophisticated tool designed for traders aiming to exploit price deviations between various asset pairs. By examining the differences in normalized price relations and their weighted residuals, this indicator provides insights into potential arbitrage opportunities in the market. Key Features: Multiple Relation Analysis: Analyze up to five different asset relations simultaneously, offering a comprehensive view of potential arbitrage setups. Normalization Functions: Choose from a variety of normalization techniques like SMA, EMA, WMA, and HMA to ensure accurate comparisons between different price series. Dynamic Weighting: Residuals are weighted based on their correlation, ensuring that stronger correlations have a more pronounced impact on the analysis. Weighting can be adjusted using several functions including square, sigmoid, and logistic. Regression Flexibility: Incorporate linear, polynomial, or robust regression to calculate residuals, tailoring the analysis to different market conditions. Customizable Display: Decide which plots to display for clarity and focus, including normalized relations, weighted residuals, and the difference between the screen relation and the average weighted residual. Usage Guidelines: Configure the asset pairs you wish to analyze using the Symbol Relations group in the settings. Adjust the normalization, volatility, regression, and weighting functions based on your preference and the specific characteristics of the asset pairs. Monitor the weighted residuals for deviations from the mean. Larger deviations suggest stronger arbitrage opportunities. Use the difference plot (between the screen relation and average weighted residual) as a quick visual cue for potential trade setups. When this plot deviates significantly from zero, it indicates a possible arbitrage opportunity. Regularly update and adjust the parameters to account for changing market conditions and ensure the most accurate analysis. In the Advanced Weighted Residual Arbitrage Analyzer , the value set in Alert Threshold plays a crucial role in delineating a normalized band. This band serves as a guide to identify significant deviations and potential trading opportunities. When we observe the plots of the green line and the purple line, the Alert Threshold provides a boundary for these plots. The following points explain the significance: Breach of the Band: When either the green or purple line crosses above or below the Alert Threshold , it indicates a significant deviation from the mean. This breach can be interpreted as a potential trading signal, suggesting a possible arbitrage opportunity. Convergence to the Mean: If the green line converges with the purple line , it denotes that the price relation has reverted to its mean. This convergence typically suggests that the arbitrage opportunity has been exhausted, and the market dynamics are returning to equilibrium. Trade Execution: A trader can consider entering a trade when the lines breach the Alert Threshold . The return of the green line to align closely with the purple line can be seen as a signal to exit the trade, capitalizing on the reversion to the mean. By monitoring these plots in conjunction with the Alert Threshold , traders can gain insights into market imbalances and exploit potential arbitrage opportunities. The convergence and divergence of these lines, relative to the normalized band, serve as valuable visual cues for trade initiation and termination. When you're analyzing relations between two symbols (for instance, BINANCE:SANDUSDT/BINANCE:NEARUSDT ), you're essentially looking at the price relationship between the two underlying assets. This relationship provides insights into potential imbalances between the assets, which arbitrage traders can exploit. Breach of the Lower Band: If the purple line touches or crosses below the lower Alert Threshold , it indicates that the first symbol (in our example, SANDUSDT ) is undervalued relative to the second symbol ( NEARUSDT ). In practical terms: Action: You would consider buying the first symbol ( SANDUSDT ) and selling the second symbol ( NEARUSDT ). Rationale: The expectation is that the price of the first symbol will rise, or the price of the second symbol will fall, or both, thereby converging back to their historical mean relationship. Breach of the Upper Band: Conversely, if the difference plot touches or crosses above the upper Alert Threshold , it suggests that the first symbol is overvalued compared to the second. This implies: Action: You'd consider selling the first symbol ( SANDUSDT ) and buying the second symbol ( NEARUSDT ). Rationale: The anticipation here is that the price of the first symbol will decrease, or the price of the second will increase, or both, bringing the relationship back to its historical average. Convergence to the Mean: As mentioned earlier, when the green line aligns closely with the purple line, it's an indication that the assets have returned to their typical price relationship. This serves as a signal for traders to consider closing out their positions, locking in the gains from the arbitrage opportunity. It's important to note that when you're trading based on symbol relations, you're essentially betting on the relative performance of the two assets. This strategy, often referred to as "pairs trading," seeks to capitalize on price imbalances between related financial instruments. By taking opposing positions in the two symbols, traders aim to profit from the eventual reversion of the price difference to the mean.
Penunjuk Pine Script™
oleh facundomartinezescoda
1
Price and Indicator CorrelationFIRST, CHANGE SOURCE OF INDICATOR FROM CLOSE TO WHATEVER INDICATOR YOU ARE COMPARING TO PRICE!!!! Confirming Indicator Validity: By calculating the correlation coefficient between the price and a specific indicator, you can assess the degree to which the indicator and price move together. If there is a high positive correlation, it suggests that the indicator tends to move in the same direction as the price, increasing confidence in the indicator's validity. On the other hand, a low or negative correlation may indicate a weaker relationship between the indicator and price, signaling caution in relying solely on that indicator for trading decisions. Identifying Divergence: Divergence occurs when the price and the indicator move in opposite directions. By monitoring the correlation coefficient, you can identify periods of divergence between the price and the selected indicator. Divergence may signal a potential reversal or significant price move, providing an opportunity to enter or exit trades. Enhancing Trading Strategies: The correlation coefficient can be used to enhance trading strategies by incorporating the relationship between the price and the indicator. For example, if the correlation coefficient consistently shows a strong positive correlation, you may use the indicator as a confirmation tool for price-based trading signals. Conversely, if the correlation is consistently negative, it may indicate an inverse relationship that could be used for contrarian trading strategies. Indicator Optimization : The correlation coefficient can help traders compare the effectiveness of different indicators. By calculating the correlation coefficient for multiple indicators against the price, you can identify which indicators have a stronger or weaker relationship with price movements. This information can guide the selection and optimization of indicators in your trading strategy. Example:
Penunjuk Pine Script™
oleh Kill_Streak
Linear Correlation Coefficient W/ MAs and Significance TestsThis Linear CC takes into account the log-normal distribution of stock prices and performs Pearson correlation on that data set. It also smoothens the results into an easy to read oscillator, and performs a two-tail t-test on the correlation coefficient data (with a = 0.05) to determine the significance of the coefficients. Significant results are shown in a solid yellow color while insignificant results are shown in a dark yellow color (you can eyeball this with a normal LCC by looking at results around -0.5 to +0.5). Two MAs are provided as well for a quick trend analysis. You can reduce the lookback period, but it defaults to 31 for the sake of statistical standards.
Penunjuk Pine Script™
oleh jsalemfinancial
Correlation TrackerCorrelation Tracker Indicator The Correlation Tracker indicator calculates and visualizes the correlation between two symbols on a chart. It helps traders and investors understand the relationship and strength of correlation between the selected symbol and another symbol of their choice. Indicator Features: - Correlation Calculation: The indicator calculates the correlation between two symbols based on the provided lookback period. - Correlation Scale: The correlation value is normalized to a scale ranging from 0 to 1 for easy interpretation. - Table Display: A table is displayed on the chart showing the correlation value and a descriptive label indicating the strength of the correlation. - Customization Options: Users can customize the text color, table background color, and choose whether to display the Pearson correlation value. - The Correlation Tracker indicator utilizes a logarithmic scale calculation, making it particularly suitable for longer timeframes such as weekly charts, thereby providing a more accurate and balanced measure of correlations across a wide range of values. How to Use: 1. Select the symbol for which you want to track the correlation (default symbol is "SPX"). 2. Adjust the lookback period to define the historical data range for correlation calculation. 3. Customize the text color and table background color according to your preference. 4. Choose whether to display the Pearson correlation value or a descriptive label for correlation strength. 5. Observe the correlation line on the chart, which changes color based on the strength of the correlation. 6. Refer to the correlation table for the exact correlation value or the descriptive label indicating the correlation strength. Note: The indicator can be applied to any time frame chart and is not limited to logarithmic scale.
Penunjuk Pine Script™
oleh Julien_Eche
4
Correlation Coefficient - DXY & XAUPublishing my first indicator on TradingView. Essentially a modification of the Correlation Coefficient indicator, that displays a 2 ticker symbols' correlation coefficient vs, the chart presently loaded.. You can modify the symbols, but the default uses DXY and XAU, which have been displaying strong negative correlation. As with the built-in CC (Correlation Coefficient) indicator, readings are taken the same way: Positive Correlation = anything above 0 | stronger as it moves up towards 1 | weaker as it moves back down towards 0 Negative Correlation = anything below 0 | stronger moving down towards -1 | weaker moving back up towards 0 This is primarily created to work with the Bitcoin weekly chart, for comparing DXY and Gold (XAU) price correlations (in advance, when possible). If you change the chart timeframe to something other than weekly, consider playing with the Length input, which is set to 35 by default where I think it best represents correlations with Bitcoin's weekly timeframe for DXY and Gold. The intention is that you might be able to determine future direction of Bitcoin based on positive or negative correlations of Gold and/or the US Dollar Index. DXY has been making peaks and valleys prior to Bitcoin since after March 2020 black swan event, where it peaked just after instead. In the future, it may flip over again and Bitcoin may hit major highs or lows prior to DXY, again. So, keep an eye on the charts for all 3, as well as the indicator correlations. Currently, we've moved back into negative correlation between Bitcoin and DXY, and positive correlation with Bitcoin and Gold: Negative Correlation b/w Bitcoin and DXY - if DXY moves up, Bitcoin likely moves down, or if DXY moves down, Bitcoin likely moves up (or if Bitcoin were to move first before DXY, as it did on March 2020, instead) Positive Correlation b/w Bitcoin and Gold - Bitcoin and Gold will likely move up or down with each other. DXY is represented by the green histogram and label, Gold is represented by the yellow histogram and label. Again, you can modify the tickers you want to check against, and you can modify the colors for their histograms / labels. The inspiration from came from noticing areas of same date or delayed negative correlation between Bitcoin and DXY, here is one of my most recent posts about that: Please let me know if you have any questions, or would like to see updates to the indicator to make it easier to use or add more useful features to it. I hope this becomes useful to you in some way. Thank you for your support! Cheers, dudebruhwhoa :)
Penunjuk Pine Script™
oleh dudebruhwhoa
2
MA Correlation CoefficientThis script helps you visualize the correlation between the price of an asset and 4 moving averages of your choice. This indicator can help you identify trendy markets as well as trend-shifts. Disclaimer Bear in mind that there is always some lag when using Moving-Averages, hence the purpose of this indicator is as a trend identification tool rather than an entry-exit strategy. Working Principle The basic idea behind this indicator is the following: In a trendy market you will find high correlation between price and all kinds of Moving-Averages. This works both ways, no matter bull or bear trend. In sideways markets you might find a mix of correlations accross timeframes (2018) or high correlation with Low-Timeframe averages and low correlation with High-Timeframe averages (2021/2022). Trend shifts might be characterised by a 'staircase' type of correlation (yellow), where the asset regains correlation with higher timeframe averages Indicator Options 1. Source : data used for indicator calculation 1. Correlation Window : size of moving window for correlation calculation 2. Average Type : Simple-Moving-Average (SMA) Exponential-Moving-Average (EMA) Hull-Moving-Average (HMA) Volume-Weighted-Moving-Average (VWMA) 3. Lookback : number of past candles to calculate average 4. Gradient : modify gradient colors. colors relate to correlation values. Plot Explanation The indicator plots, using colors, the correlation of the asset with 4 averages. For every candle, 4 correlation values are generated, corresponding to 4 colors. These 4 colors are stacked one on top of the other generating the patterns explained above. These patterns may help you identify what kind of market you're in.
Penunjuk Pine Script™
oleh nonamealgo
Crypto Correlation MatrixA crypto correlation matrix or table is a tool that displays the correlation between different cryptocurrencies and other financial assets. The matrix provides an overview of the degree to which various cryptocurrencies move in tandem or independently of each other. Each cell represents the correlation between the row and column assets respectively. The correlation matrix can be useful for traders and investors in several ways: First, it allows them to identify trends and patterns in the behavior of different cryptocurrencies. By looking at the correlations between different assets, traders can gain insight into the intra-relationships of the crypto market and make more informed trading decisions. For example, if two cryptocurrencies have a high positive correlation, meaning that they tend to move in the same direction, a trader may want to diversify their portfolio by choosing to invest in only one of the two assets. Additionally, the correlation matrix can help traders and investors to manage risk. By analyzing the correlations between different assets, traders can identify opportunities to hedge their positions or limit their exposure to particular risks. For example, if a trader holds a portfolio of cryptocurrencies that are highly correlated with each other, they may be at greater risk of losses if the market moves against them. By diversifying their portfolio with assets that are less correlated with each other, they can reduce their overall risk. Some of the unique properties for this specific script are the correlation strength levels in conjunction with the color gradient of cells, intended for clearer readability. Features: Supports up to 64 different crypto assets. Dark/Light mode. Correlation strength levels and cell coloring. Adjustable positioning on the chart. Alerts at the close of a bar. (Daily timeframe or higher recommended)
Penunjuk Pine Script™
oleh EliCobra
3
Stock Data Table█  OVERVIEW This is a table that shows some information about stocks. It is divided into four sections:  1) Correlation  2) Shares  3) Daily Data  4) Extended Session Data The table is completely modular, which means you can add or remove each element from the settings menu, and it will automatically rearrange its spaces. It is also highly customizable, to the extent that you can change almost any color, remove or change titles, invert section rows, and much more. 1) Correlation The script checks if the stock is listed on NASDAQ, and if so, uses the QQQ (Nasdaq-100 ETF) as the reference index in the first cell; otherwise, it uses the SPY (S&P 500 ETF). The length of the correlation is shown in the second cell. The table then displays the correlation between the reference index and the other index, and the correlation between the reference index and the stock. To make it easier to interpret the correlation values, each row's last cell is color-coded with a gradient to highlight the type of correlation, and the direction of the gradient can be customized. The correlation coefficient is a statistical measure that quantifies the strength and direction of the relationship between two variables, indicating how changes in one variable are associated with changes in the other variable, so it can be used to identify patterns and trends. If you are interested in correlation, I suggest taking a look at my dedicated indicator: 2) Shares This feature provides you with quick access to key information about shares and market capitalization. On one row, you can view the total shares outstanding and the market capitalization for the fiscal year or the quarterly year. The total shares outstanding represents the total number of shares of the stock that have been issued and are currently outstanding, regardless of whether they are held by insiders or public investors. The market capitalization is a widely used measure of the company's value as determined by the stock market, calculated by multiplying its current stock price with the total number of outstanding shares. The other row shows the float, which is the number of shares of a company that are available for public trading, and the corresponding free-float market cap, calculated by multiplying the company's current stock price with the float. Because Pine Script does not allow retrieving information about quarterly year float, you can view the float and the free-float market cap of the fiscal year only. The data can be displayed at all times or only when the difference between the total shares outstanding and the float is significant enough to result in a difference between the market cap and free-float market cap. The classification for market cap and free-float market cap is set in this way: Mega Cap: $200 billion or more Large Cap: between $10 billion and $200 billion Mid Cap: between $2 billion and $10 billion Small Cap: between $300 million and $2 billion Micro Cap: less than $300 million Penny Stocks: less than $5 (customizable) Comparing the free-float market cap to the market cap can provide insights into the liquidity of a stock. In fact, if the float is relatively small compared to the total shares outstanding, it may be more difficult to find buyers or sellers, which could lead to increased volatility. On the other hand, a larger float indicates that the stock is more liquid and may be easier to trade, potentially resulting in lower volatility. However, market conditions can change quickly and significantly, especially for intraday traders, and the free-float can also change as insiders or other large shareholders buy or sell shares. Therefore, comparing the data of the fiscal year with that of the quarterly year may not provide the most up-to-date and accurate information for making trading decisions. This limitation can be mitigated by combining those data with other indicators and tools, such as technical analysis or news events, to gain a better understand of the stock's performance and potential trading opportunities. 3) Daily Data This section is available on daily charts only due to the lack of accuracy of real-time daily data on other time frames. Here, you can view the Average Daily Volume (ADV) over a preferred time range (20 days by default), and the Daily Change, which represents the percentage difference between the closing price on two consecutive trading days. ADV is useful in measuring the stock's volatility, as it provides an indication of how much trading activity there is in it. Generally speaking, stocks with higher trading volume tend to be less volatile than stocks with lower trading volume. High trading volume means there are more buyers and sellers actively trading the stock, which makes it easier for investors to buy and sell shares at fair prices. This increased liquidity can help to stabilize the stock price, reducing the potential for large swings in either direction. On the other hand, stocks with lower trading volume may experience greater volatility, as there are fewer buyers and sellers actively trading the stock. This can result in larger price swings, as it may be more difficult for investors to buy or sell shares at fair prices. The daily percentage change can provide an indication of the stock's volatility, with larger values indicating greater volatility and risk. It can also be compared to that of a benchmark such an index or other stocks in the same sector, helping to determine whether the stock is outperforming or underperforming relative to them. 4) Extended Session Data The fourth section is available on intraday charts only. This section provides two pieces of information: the Extended Session Change and the Pre-Market Volume. The Extended Session Change indicates the percentage difference between the previous day's closing price and the latest price in the extended session. This gives you the extent and the direction of the price gap that occurred during extended trading hours. The Pre-Market Volume shows the sum of all shares traded during the pre-market session. This can be helpful in understanding how much interest the stock gained before the market opened. By default, the two rows will be visible at all times. They will stop updating after the end of their respective time range, and resume updating when it starts again. However, you can choose to automatically hide them outside of their time ranges. Both the extended session and pre-market time ranges can be customized. Please note that if you select time ranges outside of the regular market session (as set by default), you must enable the extended session to view the corresponding rows. █  GENERAL NOTES  • Total Shares Outstanding, Float, Average Daily Volume and Pre-Market Volume cells use a customizable color system based on two thresholds, to help you quickly identify whether the value is "too low/acceptable/too high" or "too low/not enough high/acceptable".  • If you cannot see certain data, that simply means it is not available.
Penunjuk Pine Script™
oleh valpatrad
2
Bitcoin Correlation MapHello everyone, This indicator shows the correlation coefficients of altcoins with bitcoin in a table. What is the correlation coefficient? The correlation coefficient is a value that takes a value between 0 and 1 when a parity makes similar movements with the reference parity, and takes a value between 0 and -1 when it makes opposite movements. In order to obtain more meaningful and real-time results in this indicator, the weighted average of the correlation values of the last 200bar was used. You can change the bar length as you wish. With the correlation value, you can see the parities that have similar movements with bitcoin and integrate them into your strategy. You can change the coin list as you wish, and you can also calculate their correlation with etherium instead of bitcoin . The indicator shows the correlation value of 36 altcoins at the moment. The indicator indicates the color of the correlated parities as green and the color of the inversely correlated parities as red. Cheers
Penunjuk Pine Script™
oleh Milvetti
6
Correlation Coefficient: Visible Range Dynamic Average R -Correlation Coefficient with Dynamic Average R (shows R average for the visible chart only, changes as you zoom in or out) -Label: Vis-Avg-R = Visable Average R -the Correlation Coefficient function for Pearson's R is taken from "BA🐷 CC" indicator by @balipour (highly recommended; more thorough treatment of R and other stats, but without the dynamic average) -I wrote this primarily to add a dynamic Average R, showing correlation for arbitrary start times/end times; whether it be the last month, last year, of some specific period from the past (backtest mode) -I have been using this to get an idea of correlation regimes over time between Bonds vs Stocks (ZB1! vs ES1!). -As you see from the above, most of 2022 has seen an unusually strong positive correlation between Bonds and Stocks ~~inputs: -lookback length for calculation of R -Backtest mode (true by default): displays Average R for ONLY the visible range displayed on any part of chart history (LHS to RHS of screen only) -source for both Ticker and compared Asset (close, open, high, low, ohlc4.. etc) ~~some other assets worth comparing: Aussie vs Gold; Aussie vs ES; Btc vs ES; Copper vs ES
Penunjuk Pine Script™
oleh twingall
3
Correlated ATR MA | AdulariHow do I use it? Never use this indicator as standalone trading signal, it should be used as confluence. When the price is above the moving average this shows the bullish trend is strong. When the price is below the moving average this shows the bearish trend is strong. When the moving average is purple, the trend is bullish, when it is gray, the trend is bearish. Features: Purple line for bullish trend and gray line for bearish trend. Custom formula combining an ATR and Hull MA to clearly indicate trend strength and direction. Unique approach to moving averages by taking the average of 3 types of MA's combined with custom ATR's. How does it work? 1 — ATR value is calculated, then the correlation between the source and ATR is calculated. 2 — Signal value is calculated from the difference between the previous source and ATR values. 3 — Final value is being calculated using the following formula: cor * target + (1 - cor) * nz(atr , target) 4 — Moving average is calculated by getting the average of 3 values: a normal HMA, HMA plus final value, and HMA minus final value.
Penunjuk Pine Script™
oleh Adulari
2
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:
Penunjuk Pine Script™
oleh tartigradia
Volatility Inverse Correlation CandleThis is an educational tool that can help you find direct or inverse relations between two assets. In this case I am using VIX and SPX . The way it works is the next one : So I am looking at the current open value of VIX in comparison with the previous close ( if it either above or below) and after on the SPX I am looking into the history and see for example which type of candle we had in respect with the opening value from VIX . So for example, lets imagine that today is monday, and the weekly open value from VIX was higher than previous friday close value. Now I am going to see with the inverse correlation , if based on this idea, the current weekly candle from SPX finished in a bear candle. The same can be applied for the bearish situation, so if we had an open from VIX lower than previous close, we are looking to check the SPX bull candle accuracy. At the same time, for a different type of calculation I have added an internal lookup into heikin ashi values. If you have any questions please let me know !
Penunjuk Pine Script™
oleh exlux
[PlayBit]Correlation-Co _OI Correlation-Co _OI This Indicator uses a Correlation Coefficient to compare a Crypto Currency to the Binance Open Interest feed if the data is provided A move in the same direction is indicated with a positive value (the indicator will move up) A move in the opposite direction the indicator will indicate with a negative value (the indicator will move down) If both are moving in the same direction and are converging or diverging this will be shown by larger values for divergence and smaller for convergence but will be a positive value Negative values are shown when price and _OI are moving opposite each other You can toggle the auto Open Interest option in the settings to use something other than Open Interest if you would like I still need to add a visual showing when longs are unwinding or opening and when shorts are covering or opening This is a concept that I made for @Johnny a while back and I'm republishing public from private This can be useful when comparing a Asset with its Open Interest The main bit of code was taken from: by @mortdiggiddy Let me know if you have any Ideas or suggestions or if I overlooked something Hope you enjoy, @FFriZz | @FrizLabz
Penunjuk Pine Script™
oleh FFriZz
SpreadTrade - Auto-Cointegration (ps5)Decsription: Auto-Cointegration-Based Pair Trading Strategy (revised version) To review, there are three popular styles of Pair trading: distance-based pair trading, correlation-based pair trading and cointegration-based pair trading. Typically, they require preliminary statistical estimation of the viability of the corresponding strategy. Basically a pair trade strategy boils down to shorting the outperforming instrument and going long on the underperforming instrument whenever the temporary correlation weakens which means one instrument is going up and another is going down. Apart from the typical cointegration strategy which employs two cointegrated instruments, this script uses just one instrument, in base timeframe and in lagged timeframe, actually making it an auto-cointegration, or better still, an auto-correlation strategy. Notice that each moving average function may require different Threshold settings.The orange cross symbol indicates the exit points. To filter out the signals use higher values for the LongWindow and the Threshold parameters. Also pay attention that in some cases with some moving averages the color of the signals has to be inverted.
Penunjuk Pine Script™
oleh capissimo
1
Correlation ZonesThis indicator highlights zones with strong, weak and negative correlation. Unlike standard coefficient indicator it will help to filter out noise when analyzing dependencies between two assets. With default input setting Correlation_Threshold=0.5: - Zones with correlation above 0.5, will be colored in green (strong correlation) - Zones with correlation from -0.5 to 0.5 will be colored grey (weak correlation) - Zones with correlation below -0.5 will be colore red (strong negative correlation) Input parameter "Correlation_Threshold" can be modified in settings. Provided example demonstrates BTCUSD correlation with NASDAQ Composite . I advice to use weekly timeframe and set length to 26 week for this study
Penunjuk Pine Script™
oleh dkaravaev
Kendall Rank Correlation Coefficient (alt)This is a non-parametric correlation statistical test, which is less sensitive to magnitude and more to direction, hence why some people call this a "concordance test". This indicator was originally created by Alex Orekhov (everget), if you like this one, please show the original author some love: This version is extended by tartigradia (2022) to make it more readily useable: * Update to pinescript v5 * Default compare to current symbol (instead of only fixed symbols) * Add 1.0, 0.0 and -1.0 correlation levels lines. This indicator plots both the Kendall correlation in orange, and the more classical parametric Pearson correlation in purple for comparison. Either can be disabled in the Style tab.
Penunjuk Pine Script™
oleh tartigradia
Correlation with P-Value & Confidence Interval (alt)Shows the Pearson correlation between two symbols, including statistical significance test. This is a fork of the original script by Balipour, with the addition of EMA that can be used instead of SMA in the Pearson correlation as an attempt to capture correlation trend changes more quickly, and conversion to pinescript v5. In the end, the EMA does not help much, for a faster capture of correlation trend changes, another kind of correlation is necessary, such as sign test correlation (another one of my indicators implement this idea). Please show the original indicator's author some love if you appreciate this work:
Penunjuk Pine Script™
oleh tartigradia
7
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:
Penunjuk Pine Script™
oleh tartigradia
2
CFB-Adaptive Trend Cipher Candles [Loxx]CFB-Adaptive Trend Cipher Candles is a candle coloring indicator that shows both trend and trend exhaustion using Composite Fractal Behavior price trend analysis. To do this, we first calculate the dynamic period outputs from the CFB algorithm and then we injection those period inputs into a correlation function that correlates price input price to the candle index. The closer the correlation is to 1, the lighter the green color until the color turns yellow, sometimes, indicating upward price exhaustion. The closer the correlation is to -1, the lighter the red color until it reaches Fuchsia color indicating downward price exhaustion. Green means uptrend, red means downtrend, yellow means reversal from uptrend to downtrend, fuchsia means reversal from downtrend to uptrend. What is Composite Fractal Behavior ( CFB )? All around you mechanisms adjust themselves to their environment. From simple thermostats that react to air temperature to computer chips in modern cars that respond to changes in engine temperature, r.p.m.'s, torque, and throttle position. It was only a matter of time before fast desktop computers applied the mathematics of self-adjustment to systems that trade the financial markets. Unlike basic systems with fixed formulas, an adaptive system adjusts its own equations. For example, start with a basic channel breakout system that uses the highest closing price of the last N bars as a threshold for detecting breakouts on the up side. An adaptive and improved version of this system would adjust N according to market conditions, such as momentum, price volatility or acceleration. Since many systems are based directly or indirectly on cycles, another useful measure of market condition is the periodic length of a price chart's dominant cycle, (DC), that cycle with the greatest influence on price action. The utility of this new DC measure was noted by author Murray Ruggiero in the January '96 issue of Futures Magazine. In it. Mr. Ruggiero used it to adaptive adjust the value of N in a channel breakout system. He then simulated trading 15 years of D-Mark futures in order to compare its performance to a similar system that had a fixed optimal value of N. The adaptive version produced 20% more profit! This DC index utilized the popular MESA algorithm (a formulation by John Ehlers adapted from Burg's maximum entropy algorithm, MEM). Unfortunately, the DC approach is problematic when the market has no real dominant cycle momentum, because the mathematics will produce a value whether or not one actually exists! Therefore, we developed a proprietary indicator that does not presuppose the presence of market cycles. It's called CFB (Composite Fractal Behavior) and it works well whether or not the market is cyclic. CFB examines price action for a particular fractal pattern, categorizes them by size, and then outputs a composite fractal size index. This index is smooth, timely and accurate Essentially, CFB reveals the length of the market's trending action time frame. Long trending activity produces a large CFB index and short choppy action produces a small index value. Investors have found many applications for CFB which involve scaling other existing technical indicators adaptively, on a bar-to-bar basis. Included Loxx's Expanded Source Types Related indicators: Adaptive Trend Cipher loxx] Dynamic Zones Polychromatic Momentum Candles RSI Precision Trend Candles
Penunjuk Pine Script™
oleh loxx
5