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Similarity

Multi Asset Similarity MatrixProvides a unique and visually stunning way to analyze the similarity between various stock market indices. This script uses a range of mathematical measures to calculate the correlation between different assets, such as indices, forex, crypto, etc.. Key Features: Similarity Measures: The script offers a range of similarity measures to choose from, including SSD (Sum of Squared Differences), Euclidean Distance, Manhattan Distance, Minkowski Distance, Chebyshev Distance, Correlation Coefficient, Cosine Similarity, Camberra Index, Mean Absolute Error (MAE), Mean Squared Error (MSE), Lorentzian Function, Intersection, and Penrose Shape. Asset Selection: Users can select the assets they want to analyze by entering a comma-separated list of tickers in the "Asset List" input field. Color Gradient: The script uses a color gradient to represent the similarity values between each pair of indices, with red indicating low similarity and blue indicating high similarity. How it Works: The script calculates the source method (Returns or Volume Modified Returns) for each index using the sec function. It then creates a matrix to hold the current values of each index over a specified window size (default is 10). For each pair of indices, it applies the selected similarity measure using the select function and stores the result in a separate matrix. The script calculates the maximum and minimum values of the similarity matrix to normalize the color gradient. Finally, it creates a table with the index names as rows and columns, displaying the similarity values for each pair of indices using the calculated colors. Visual Insights: The indicator provides an intuitive way to visualize the relationships between different assets. By analyzing the color-coded tables, traders can gain insights into: Which assets are highly correlated (blue) or uncorrelated (red) The strength and direction of these correlations Potential trading opportunities based on similarities and differences between assets Overall, MASM is a powerful tool for market analysis and visualization, offering a unique perspective on the relationships between various assets. ~llama3
อินดิเคเตอร์ Pine Script™
โดย RicardoSantos
1
Similar Price ActionDescription: The indicator tries to find an area of N candles in history that has the most similar price action to the latest N candles. The maximum search distance is limited to 5000 candles. It works by calculating a coefficient for each candle and comparing it with the coefficient of the latest candle, thus searching for two closest values. The indicator highlights the latest N candles, as well as the most similar area found in the past, and also tries to predict future price based on the latest price and price directly after the most similar area that was found in the past. Inputs: - Length -> the area we are searching for is comprised of this many candles - Lookback -> maximum distance in which a similar area can be found - Function -> the function used to compare latest and past prices Notes: - The indicator is intended to work on smaller timeframes where the overall price difference is not very high, but can be used on any
อินดิเคเตอร์ Pine Script™
โดย sabricat
1
The Echo Forecast [LuxAlgo]This indicator uses a simple time series forecasting method derived from the similarity between recent prices and similar/dissimilar historical prices. We named this method "ECHO". This method originally assumes that future prices can be estimated from a historical series of observations that are most similar to the most recent price variations. This similarity is quantified using the correlation coefficient. Such an assumption can prove to be relatively effective with the forecasting of a periodic time series. We later introduced the ability to select dissimilar series of observations for further experimentation. This forecasting technique is closely inspired by the analogue method introduced by Lorenz for the prediction of atmospheric data. 1. Settings Evaluation Window: Window size used for finding historical observations similar/dissimilar to recent observations. The total evaluation window is equal to "Forecast Window" + "Evaluation Window" Forecast Window: Determines the forecasting horizon. Forecast Mode: Determines whether to choose historical series similar or dissimilar to the recent price observations. Forecast Construction: Determines how the forecast is constructed. See "Usage" below. Src: Source input of the forecast Other style settings are self-explanatory. 2. Usage This tool can be used to forecast future trends but also to indicate which historical variations have the highest degree of similarity/dissimilarity between the observations in the orange zone. The forecasting window determines the prices segment (in orange) to be used as a reference for the search of the most similar/dissimilar historical price segment (in green) within the gray area. Most forecasting techniques highly benefit from a detrended series. Due to the nature of this method, we highly recommend applying it to a detrended and periodic series. You can see above the method is applied on a smooth periodic oscillator and a momentum oscillator. The construction of the forecast is made from the price changes obtained in the green area, denoted as w(t) . Using the "Cumulative" options we construct the forecast from the cumulative sum of w(t) . Finally, we add the most recent price value to this cumulated series. Using the "Mean" options will add the series w(t) with the mean of the prices within the orange segment. Finally the "Linreg" will add the series w(t) to an extrapolated linear regression fit to the prices within the orange segment.
อินดิเคเตอร์ Pine Script™
โดย LuxAlgo
112