Date of Publication

6-17-2022

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Management of Financial Institutions

Subject Categories

Finance and Financial Management

College

Ramon V. Del Rosario College of Business

Department/Unit

Financial Management Department

Thesis Advisor

Tomas Tiu

Defense Panel Chair

Edralin Lim

Defense Panel Member

Nissa Marie Toledo
Rene Cuartero

Abstract/Summary

This study compared the EVT and GARCH-EVT models to determine the most reliable model with regard to forecasting VaR during a crisis, specifically the Global Financial Crisis and the COVID-19 Pandemic. Hence, the paper analyzed the selected ASEAN indices’ daily closing prices during the said crises for 16 years, which consisted of Vietnam, Thailand, Malaysia, Indonesia, and the Philippines. The study also determined the crisis that yielded the most extreme values and the index that was the most volatile during the crises. Backtestings, such as Kupiec test and Christoffersen test, as well as descriptive statistics, normality test, and Kruskal Wallis test were used for the research. The findings showed that the EVT-BM and GARCH-EVT-BM models were the most reliable VaR model for all time periods due to its conservative estimations. On the other hand, it was determined that the GFC had the most extreme values with losses as much as -12%. The paper also discerned that Indonesia’s Jakarta Stock Exchange Composite Index (JKSE) was the most volatile during the GFC, while Thailand’s Bangkok SET50 Index (SET50) displayed the most volatility during the COVID-19 pandemic. These findings can assist investors and financial institutions on the most reliable risk models they can use pre-crises and during crises that can severely impact their investments; thereby providing them guidance as part of portfolio risk management tool.

Keywords: GARCH-EVT models, EVT models, Value-at-Risk forecasting, ASEAN stock indices, Global Financial Crisis, COVID-19 Pandemic, Kupiec test, Christoffersen test

Abstract Format

html

Language

English

Keywords

Stock price indexes—Southeast Asia; Stock exchanges—Southeast Asia; Stock price forecasting—Southeast Asia

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Embargo Period

7-10-2022

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