Stock Forecasting using Hidden Markov Processes

We define these region of time as a regime whose mean and variance are explicitly different from other region of time. This regime can represent economic situation. If we can figure out this regime, in other words, current economic situation, we can forecast better than using constant mean and variance. In this project, we would like to construct this regime and utilize it for the stock forecasting using one of the machine learning algorithms.