Stock Market Prediction using Hidden Markov Model and Neural Network

Ali Sasani, Stephanie Tibado

Stock Market, Prediction using Hidden Markov, Model and Neural Network

Luxury and comfort always comes after wealth. It is crucial and challenging task to completely understand the stock market and predict the future price. It has been proven that predicting future stock price with time series analysis is not reliable. It is known that Neural network has ability to extract valuable features for processing from data. In this paper, we applied some of machine learning techniques on stock market and tried to predict its trend and make profit based on that prediction. We applied multiple combination of feature extraction methods with NN and HMM. Among feature extraction methods we got the best results from DCT and PCA on raw data.

https://dx.doi.org/10.31873/IJEAS.7.04.07