An Estimation of Value at Risk using GARCH Models for the Conventional and Islamic Stock Market in Malaysia

Chin Wen Cheong,Tan Siow Hooi,Nor Azliana Aridi

doi:10.6007/ijarbss/v8-i11/5568

Chin Wen Cheong, Tan Siow Hooi + Show 1 more

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https://doi.org/10.6007/ijarbss/v8-i11/5568

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Abstract

This study attempts to estimate the value-at-risk (VaR) to forecast volatility for both conventional and Islamic stock markets in Malaysia. In particular, the purpose of the article is to investigate whether GARCH models are accurate in the evaluation of VaR in emerging stock markets such as Malaysia.The daily return of the conventional (KLCI) and Islamic (FBMS) stock market are analysed for the period 2000 – 2015. The volatility model of GARCH (1,1), TGARCH (1,1) and CGARCH (1,1) with a normal and and student-t distribution are used to model the conditional variance of the stock market returns. The VaR violations of unconditional coverage and the backtesting procedure of Kupiec test are used to check the reliability and accuracy of the volatility model used for both normal and student-t distribution. Based on the Akaike Information Criterion (AIC), the best model for modelling the conventional and Islamic stock market returns is TGARCH (1,1). The backtesting results showed that for all GARCH models used, the normal distribution gives better forecast VaR compared to the student’s t distribution.

Highlights

The modern portfolio theory (MPT) describes the strong relationship between risk and volatility where volatility generates risk associated with the level of dispersion around the mean
DATA & DESCRIPTIVE STATISTICS The data consist of approximately 3935 daily returns of FTSE Bursa Malaysia KLCI Index (KLCI) and FTSE Bursa Malaysia EMAS Shariah Index (FBMS) during trading day’s period of 2000 – 2015
The TARCH (1,1) model with normal distribution displays as the good forecast model for both conventional and Islamic Index based on the violation value violation ratio (VR) ∈ [0.8, 1.2]

Summary

Introduction

The modern portfolio theory (MPT) describes the strong relationship between risk and volatility where volatility generates risk associated with the level of dispersion around the mean. Many previous studies have found models and theories with sophisticated tools that are applicable in measuring and forecasting the stock market risk. VaR is used to calculate the maximum financial loss over a specific time frame for a given confidence level by focusing on the estimation of the tails distribution. The primary reason for the underestimation or overestimation of VaR is because numerous application in the financial field assume that stock market returns are normally distributed while in the real world it is leptokurtosis which exhibit skewness and excess kurtosis. This paper aims to explain the most accurate model to forecast volatility and analyzed the existence of empirical facts in conventional and Islamic market in Malaysia. This paper is organized into seven sections.

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