| Summary: | 碩士 === 國立高雄第一科技大學 === 金融營運所 === 93 === This study analyses the influence of skewness and kurtosis on VaR. The risky assets are TAIEX and Options. We loose the assumption of normal distribution for the underlying assets and then use Cornish-Fisher expansion to determine the distribution of risk factors. On the other side, we used second order Taylor expansion to estimate the VaR of options. Moreover, we add factors of vega and theta for VaR model of options.
We used three models to estimate VaR. The model considers the first two moments only, which neglect the skewness and kurtosis, the model considers the first three moments which adds the skewness, and the model consider the first four moments, which also adds the kurtosis. Volatilities are estimated by moving average (MA) and exponential weight moving average (EWMA). We also compared these results with historical simulation method. We determined the VaRs of the closest delivery month futures contract and near-the-money calls. We found the model considering first four moments performs best. Considering skewness but neglecting kurtosis will not increase the accuracy of VaR determination. This may be because the skewness and kurtosis are highly correlated.
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