Forecasting Stock Prices Using Reported Earnings and Past Prices

  • Cesar G. Saldana U.P. Ceasar EA Virata School of Business
  • Jose S. Victoria U.P. Ceasar EA Virata School of Business


This study explores the use of corporate income and past prices as bases for predicting stock prices, leading to well-informed investment decisions.  The regression model is used to show a significant relationship between reported earnings and the stock price (using San Miguel Corporation as example).  This result provides support for the use of Price-Earnings multiples by practitioners in the Philippine stock market in estimating the long-term or intrinsic value of a security.

 Likewise, the use of time series modelling as a prediction tool for SMC stock price is analysed.  The study intends to find out whether the price of San Miguel shares would have a long term influence on its present price.  Upon examination of a few autoregressive models fitted on weekly SMC price data, only the auto regressive model of order one is found to be a valid predictor.  This means that only the most immediate past value of share price is useful in predicting the present share price.