Hidden Markov Model Implementation for Prediction of Stock Prices with TF-IDF features

Abstract

Stock data analysis is challenging research area. The proposed analysis works on online news data for prediction of stock market states such as high, low etc. The Hidden Markov Model along with features extracted such as TF-IDF is used to find out next day's stock market value for group of companies. The method can be further extended to adjustment of probability values to calculate tuned model for prediction.