Title

Forecasting Volatility in the Singapore Stock Market

Publication Type

Journal Article

Publication Date

1992

Abstract

Data from the Stock Exchange of Singapore (SES) are used to compare 3 methods of forecasting the volatility of derivative securities: 1. the naive method based on historical sample variance, 2. the exponentially weighted moving average (EWMA) method, and 3. the generalized autoregressive conditional heteroskedasticity (GARCH) model. The data used are the daily closing prices of 5 value-weighted SES indexes covering the period from March 19, 1975, to October 25, 1988. Study findings indicate that the EWMA mehtod is superior to the naive method and the GARCH model. The GARCH model, while the most sophisticated, is the poorest method, which can be partially attributed to the method's stringent data requirements. Therefore, the EWMA is particularly appealing in actual applications in the pricing of derivative securities, given its superior forecasts and simplicity.

Discipline

Asian Studies | Econometrics | Finance

Research Areas

Econometrics

Publication

Asia Pacific Journal of Management

Volume

9

Issue

1

First Page

1

ISSN

0217-4561

Publisher

Kluwer

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