An analytical study on the predictability of monthly returns of stocks in the oil and mining sector using the Markov chain model for the period 2000-2008

• Main Authors: Esporlas, Carlo Antonio, Lao, Johann Kelly, Sim, Alvin Bryan, Trias, Francis Glenn
• Format: text
• Language: English
• Published: Animo Repository 2009
• Subjects: Oil industries > Philippines; Petroleum industry and trade > Philippines; Mineral industries > Finance; Stock price forecasting > Philippines
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/9407
• Institution: De La Salle University

The Markov chain model predicts the state of an object in a certain period of time in the future by virtue of profitability vector of the initial state and state transition probability matrix (Zhang and Zhang, 2009). The main goal of this research is to know if the Markov chain model is capable of predicting the behavior of the monthly returns, if it will be bearish or bullish, of the stocks in the oil and mining sector of the Philippine Stock Exchange. The study used the data from 2000-2008 for the computation while using the data for 2009 as out sample to see if the computed values and probabilities are in line with the actual data. Moreover, there were only six (6) out of sixteen (16) companies who had significant results. Considering some external factors like the recent financial crisis and the high volatility of the stock used, the resulting 37.5% significance is still a good indicator of the predictive capability of the Markov chain model.