Downside Risk Measurement of Thailand Equity Mutual Funds
(2011)Department of Business Administration
- Abstract
- Abstract Value at Risk (VaR) is a simple, transparent and consistent measure that summarizes all sources of downside risk. VaR has gained acceptance in the banking industry in accordance to Basel II rules which require banks to use VaR in calculations of market risk. VaR as a risk measure is not as widely accepted in the investment industry. This thesis embraces five different VaR models to 20 equity mutual funds in Thailand. That is done to analyze if these equity mutual funds have considerable downside risk in terms of VaR. A comparative analysis of parametric, semi-parametric and non-parametric approaches is used to find the model that is the most suitable for the sample. The parametric approaches are student-t distribution and... (More)
- Abstract Value at Risk (VaR) is a simple, transparent and consistent measure that summarizes all sources of downside risk. VaR has gained acceptance in the banking industry in accordance to Basel II rules which require banks to use VaR in calculations of market risk. VaR as a risk measure is not as widely accepted in the investment industry. This thesis embraces five different VaR models to 20 equity mutual funds in Thailand. That is done to analyze if these equity mutual funds have considerable downside risk in terms of VaR. A comparative analysis of parametric, semi-parametric and non-parametric approaches is used to find the model that is the most suitable for the sample. The parametric approaches are student-t distribution and log-normal distribution and the non-parametric approach is basic historical simulation. The semi-parametric approaches are EWMA (exponentially weighted moving average model) and volatility weighted historical simulation using a GARCH(1,1) model for volatility. To test robustness and predictive ability three backtesting models are applied on all the approaches and all the equity mutual funds. The backtesting models are Bernoulli trial approach, Kupiec test and Christoffersen framework. Backtesting results for the models demonstrate that volatility weighted historical simulation using a GARCH(1,1) model is the most accurate measure of downside risk for both VaR at 95% and 99% confidence interval. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/2369878
- author
- Sigmundsdóttir, Hulda and Udomsapsanti, Ploenpit
- supervisor
- organization
- year
- 2011
- type
- H1 - Master's Degree (One Year)
- subject
- keywords
- Value at Risk, equity mutual funds, Thailand, student-t distribution, log-normal distribution, EWMA, volatility weighted historical, GARCH(1, 1), historical simulation, backtesting, Bernoulli, Kupiec, Christoffersen., Management of enterprises, Företagsledning, management
- language
- Swedish
- id
- 2369878
- date added to LUP
- 2011-06-03 00:00:00
- date last changed
- 2012-04-02 18:51:14
@misc{2369878,
abstract = {{Abstract Value at Risk (VaR) is a simple, transparent and consistent measure that summarizes all sources of downside risk. VaR has gained acceptance in the banking industry in accordance to Basel II rules which require banks to use VaR in calculations of market risk. VaR as a risk measure is not as widely accepted in the investment industry. This thesis embraces five different VaR models to 20 equity mutual funds in Thailand. That is done to analyze if these equity mutual funds have considerable downside risk in terms of VaR. A comparative analysis of parametric, semi-parametric and non-parametric approaches is used to find the model that is the most suitable for the sample. The parametric approaches are student-t distribution and log-normal distribution and the non-parametric approach is basic historical simulation. The semi-parametric approaches are EWMA (exponentially weighted moving average model) and volatility weighted historical simulation using a GARCH(1,1) model for volatility. To test robustness and predictive ability three backtesting models are applied on all the approaches and all the equity mutual funds. The backtesting models are Bernoulli trial approach, Kupiec test and Christoffersen framework. Backtesting results for the models demonstrate that volatility weighted historical simulation using a GARCH(1,1) model is the most accurate measure of downside risk for both VaR at 95% and 99% confidence interval.}},
author = {{Sigmundsdóttir, Hulda and Udomsapsanti, Ploenpit}},
language = {{swe}},
note = {{Student Paper}},
title = {{Downside Risk Measurement of Thailand Equity Mutual Funds}},
year = {{2011}},
}