THE VAR EVALUATION OF SHARIAH STOCK MARKET IN MALAYSIA DURING COVID-19 PANDEMIC BY USING CONDITIONAL EVT METHOD

Authors

  • Nor Azliana Aridi Faculty of Management, Multimedia University, Selangor, Malaysia
  • Tan Siow Hooi Faculty of Management, Multimedia University, Selangor, Malaysia
  • Chin Wen Cheong School of Mathematics and Physics, Xiamen University, Selangor, Malaysia

DOI:

https://doi.org/10.33736/ijbs.6403.2023

Keywords:

Conditional EVT, Heavy-tailed, POT method, Value-at-risk

Abstract

In the current financial market, the Islamic stock market faced with a significant challenge to sustain and maintain its stability in intensified market volatility and unexpected extreme events. It can reduce the intensity and occurrence of financial crises by eliminating the primary vulnerabilities of the conventional system. This paper aims to identify the most effective method in risk evaluation by presenting the risk evaluation performance between conventional and Islamic stock market that focusing on extreme events in stock market returns. The data analysis is divided into two periods: normal and crisis COVID-19 periods. The empirical analysis, conducted within the sample employs the conditional extreme value theory (EVT) method that combine the filtered series of GARCH and EGARCH models. This filtered series will be used to generate the threshold by using the peak-over-threshold (POT) method. This threshold then will be used to estimate the generalized Pareto distribution (GPD) distribution to forecast the one-day ahead value-at-risk (VaR). The findings indicate that, in Shariah stock markets, the conditional EVT model demonstrates superior performance in forecasting stock market risk compared to the standard GARCH and EGARCH models.

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Published

2023-12-26

How to Cite

Nor Azliana Aridi, Tan Siow Hooi, & Chin Wen Cheong. (2023). THE VAR EVALUATION OF SHARIAH STOCK MARKET IN MALAYSIA DURING COVID-19 PANDEMIC BY USING CONDITIONAL EVT METHOD. International Journal of Business and Society, 24(3), 1079–1098. https://doi.org/10.33736/ijbs.6403.2023