Modeling Philippine Stock Exchange Composite Index Using Time Series Analysis

[摘要] This study was conducted to develop a time series model of the Philippine Stock Exchange Composite Index and its volatility using the finite mixture of ARIMA model with conditional variance equations such as ARCH, GARCH, EG ARCH, TARCH and PARCH models. Also, the study aimed to find out the reason behind the behaviorof PSEi, that is, which of the economic variables - Consumer Price Index, crude oil price, foreign exchange rate, gold price, interest rate, money supply, price-earnings ratio, Producers' Price Index and terms of trade - can be used in projecting future values of PSEi and this was examined using Granger Causality Test. The findings showed that the best time series model for Philippine Stock Exchange Composite index is ARIMA(1,1,5) - ARCH(1). Also, Consumer Price Index, crude oil price and foreign exchange rate are factors concluded to Granger cause Philippine Stock Exchange Composite Index.

[发布机构] Department of Mathematics and Statistics, College of Science, Polytechnic University of the Philippines, Sta. Mesa, Manila, Philippines^1

[效力级别] 化学

[关键词] Conditional variance;Consumer price index;Crude oil prices;Economic variables;Foreign exchange rates;Granger causality test;Terms of trades;Time series modeling