Testing Informational Market Efficiency on Kuala Lumpur Stock Exchange

Abstract

The primarily objective of this study is to investigate the informational efficiency of the Kuala Lumpur Security Exchange (KLSE) in terms of the daily Composite Index for the period of 1st January 1977 – 3rd May 2002. This paper concerned with the weak form test of efficient market hypo-thesis. Since its discovery in 1982 by Engel, Autoregressive Conditional Heterocedastic (ARCH) modelling , which allows the conditional variance to change over time as a function of past errors keeping the unconditional variance constant, has turn out to be a growth industry, with all sorts of variations on the original model. One that has became well-known is the Generalized Autoregressive Conditional Heterocedastic (GARCH) model that is developed by Bollerslev (1986). It has been observed that such models capture much temporal behaviour like thick tail distribution and volatility clustering of many economic and financial variables. Since, in order to explore efficiency of such growing market a non-linear GARCH model is estimated. Empirical results confirm that KLSE is predictable and thus is not informationally efficient in the weak sense and volatility of return is quite persistent when daily observation of composite index is used