Forecasting stock prices using hidden Markov models and support vector regression with firefly algorithm

• Main Authors: Cantuba, Joshua Reno S., Nicolas, Patrick Emilio U.
• Format: text
• Language: English
• Published: Animo Repository 2016
• Subjects: Stocks > Prices > Philippines; Markov processes; Hidden Markov models; Box-Jenkins forecasting; MAD (Computer program language); Regression analysis; Algorithms; Mathematics
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/18393
• Institution: De La Salle University

Many models have been proposed for forecasting stock prices. One is the Autoregressive Integrated Moving Average (ARIMA) model which is extensively used in the fields of economics and finance (Ariyo et al., 2014). In the Philippines, the Philippine Stock Exchange (PSE) forecasts future stock price m...