Library "SimilarityMeasures" Similarity measures are statistical methods used to quantify the distance between different data sets or strings. There are various types of similarity measures, including those that compare: - data points (SSD, Euclidean, Manhattan, Minkowski, Chebyshev, Correlation, Cosine, Camberra, MAE, MSE, Lorentzian, Intersection, Penrose...
Experimental: Compares the similarity of two instruments price patterns.
Library "FunctionCosineSimilarity" Cosine Similarity method. function(sample_a, sample_b) Measure the similarity of 2 vectors. Parameters: sample_a : float array, values. sample_b : float array, values. Returns: float. diss(cosim) Dissimilarity helper function. Parameters: cosim : float, cosine similarity value (0 > 1) Returns: float
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...