Estimating the precision of market risk within the tiger cub economies’ region through VaR backtesting

Abstract

The purpose of this paper is to estimate the market risk exposure within the Tiger Cub Economies regions in calm and stormy market conditions. The secondary objective of the empirical research is to determine the reliability and accuracy of the market risk model used by most banking sectors within the region as the primary tool for mitigating potential systematic risk. The precision of the market risk model was assessed using the 250-day trading data of major indices from five emerging ASEAN countries or known as the Tiger Cub Economies stretching from January 2018 until December 2021. It consists of two sub-samples which are known as before and during the pandemic COVID-19. The current study contributes to the existing literature on the ability of the VaR-HS model in estimating accurate market risk exposure in light of the recent pandemic COVID19 within the Tiger Cub Economies region. Interestingly, it is also evident that inaccurate VaR-HS tend to overestimate the risk and VaR-GARCH tends to severely underestimate the measures during extreme market conditions. Finally, by recalibrating models that severely over/understate the risk during pandemic stormy market conditions in SETi and VNI indices, it is also imperative that RiskMetrics EWMA could improve the estimation measures in an extreme market event by putting more weights on the most recent volatility memory. The current study reveals new insights where in the event of a crisis, HS-VaR estimates tend to be overstated while GARCH-VaR measures could be understated where it is evident that EWMA-VaR estimates could provide a better measure of market risk exposure, particularly during stormy periods.