A Smoothing Method for Stock Price Prediction with Hidden Markov Models
Soon-Ho Lee, Chang-Hyuck Oh · Journal of the Korean Data and Information Science Society · 2007
In this paper, we propose a smoothing and thus noise-reducing method of data sequences for stock price prediction with hidden Markov models, HMMs. The suggested method just uses simple moving average. A proper average size is obtained from forecasting experiments with stock prices of bank sector of Korean Exchange. Forecasting method with HMM and moving average smoothing is compared with a conventional method.