Value-at-risk for shares of companies listed under the financial sector of Malaysian Stock Exchange (nilai berisiko untuk saham syarikat dalam sektor kewangan di Bursa Saham Malaysia)

Nur Atikah Mohamed Rozali, and Humaida Banu Samsudin, and Prevena Nambiar A/P Sridahran, (2015) Value-at-risk for shares of companies listed under the financial sector of Malaysian Stock Exchange (nilai berisiko untuk saham syarikat dalam sektor kewangan di Bursa Saham Malaysia). Journal of Quality Measurement and Analysis, 11 (1). pp. 1-10. ISSN 1823-5670

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Abstract

Risk management is essential since stock prices of a company are often exposed to high level of market risk. One way to evaluate market risk is by determining the value-at-risk, which is the maximum probable loss that a financial instrument is exposed to at a given time. In this research, the value-at-risk was evaluated for all shares of companies listed under the financial sector of Malaysian Stock Exchange using non-parametric approach and Monte Carlo simulation method. The comparisons of risk faced by the shares of companies were also done. These methods were chosen to avoid wrong estimation of the value-at-risk if the data is fitted to an inaccurate distribution. The value-at-risk was determined using the non-parametric approaches, which are basic historical simulation, bootstrap historical simulation, age-weighted historical simulation and volatility-weighted historical simulation methods. Monte Carlo simulation was applied using the Geometric Brownian Motion. Findings of this study found that the shares of all companies produced slightly different results for each of the method with different level of sensitivity. The shares of Pan Malaysia Capital Berhad are the most risky because it produced the highest value-at-risk. The shares of LPI Capital Berhad and Public Bank Berhad are the least risky as they produced the lowest value-at-risk in comparison with the shares of all the other companies.

Item Type:Article
Keywords:market risk; non-parametric method; Monte Carlo simulation method
Journal:Journal of Quality Measurement and Analysis
ID Code:9476
Deposited By: ms aida -
Deposited On:15 Jan 2016 07:35
Last Modified:14 Dec 2016 06:50

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