Modeling Philippine Stock Exchange Composite Index Using Time Series Analysis

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 b...

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Bibliographic Details
Published in:Journal of physics. Conference series 2015-06, Vol.622 (1), p.12022
Main Authors: Gayo, W S, Urrutia, J D, Temple, J M F, Sandoval, J R D, Sanglay, J E A
Format: Article
Language:English
Subjects:
Arches
Autoregressive models
Consumer Price Index
Crude oil
Crude oil prices
Foreign exchange rates
Physics
Stock exchanges
Time series
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Summary: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.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/622/1/012022