In this post we’ll be discussing the potential avenues for using supervised learning in finance for stock market prediction.
Dynamic Time Warping (DTW) is an intelligent, dynamically adjusted metric that allows more flexibility when used in combination with any distance dependent algorithm. This flexibility allows for better classification results in many different time-series analyses.
DTW allows us to retain the temporal dynamics by directly modeling the time-series. As its names suggests, the usual Euclidean distance in problems is replaced with a dynamically adjusted metric.