Comparisons of the Portfolio Value-at-Risk Estimation Methods

• Main Authors: Min-Shan Wu, 吳旻珊
• Other Authors: Jyh-Jiuan Lin
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/42074812963471202376

碩士 === 淡江大學 === 統計學系碩士班 === 96 === The objective of the research is to study the risk measurement Value-at-Risk (VaR) that is most relevant to financial institutions worldwide. Modeling and estimating techniques for measuring risks is quite a challenge. Four VaR estimation methods are studied in this research and they are (1) Historical simulation, (2) Variance-covariance method incorporating the exponential weighted moving average (EWMA) method, (3) Monte Carlo simulation under normal distribution incorporating Cholesky decomposition and (4) Monte Carlo simulation under generalized error distribution (GED), correspondingly. Backtesing and Christoffersen (1998) tests are adapted to validate the accuracy of the four estimation approaches. At last, a case study of the mutual fund is provided to increase clarity of the VaR estimation methods and deliver actionable results. The empirical results obtained shows that exponential weighted moving average (EWMA) model in variance-covariance method out performs the GED model in Monte Carlo method and the historical simulation method.