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題名 Value-at-Risk for Long and Short Positions of Asian Stock Markets
作者 Tu, Anthony H.;Wong, Woon K.;Chang, Matthew C.
杜化宇
貢獻者 財管系
關鍵詞 Stock Market;Stocks
日期 2008-12
上傳時間 6-Oct-2015 16:33:48 (UTC+8)
摘要 Empirical research shows that stock market returns distributions can be asymmetric and the auto-correlations of its absolute returns are stronger than that of its squared returns. An asymmetric returns distribution means that the left and right tails would have different thickness, whereas higher auto-correlation of absolute returns implies that better volatility forecasts are possible. This has significant economic implication for risk management that requires accurate estimation of Value-at-Risk (VaR). In this paper, we therefore investigate the performance of VaR models that take into consideration of the skewness of the innovation process and utilize the Box-Cox transformation of conditional variance in a flexible ARCH-type model. Specifically, we use the Asymmetric Power Autoregressive Conditional Heteroscedasticity (APARCH) model based on the skewed Student density to model the VaRs of daily returns of those Asian markets found to exhibit both skewness and kurtosis in the innovation process. We apply the likelihood ratio tests of proportional failure rates to such VaR model and compare the results with other VaR models, in particular, APARCH with symmetric distributions and APARCH with skewed Student distributions. It is found that the APARCH model with skewed Student distribution performs the best for the Asian markets considered.
關聯 International Research Journal of Finance and Economics, 22, 135-143
資料類型 article
dc.contributor 財管系
dc.creator (作者) Tu, Anthony H.;Wong, Woon K.;Chang, Matthew C.
dc.creator (作者) 杜化宇zh_TW
dc.date (日期) 2008-12
dc.date.accessioned 6-Oct-2015 16:33:48 (UTC+8)-
dc.date.available 6-Oct-2015 16:33:48 (UTC+8)-
dc.date.issued (上傳時間) 6-Oct-2015 16:33:48 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/78877-
dc.description.abstract (摘要) Empirical research shows that stock market returns distributions can be asymmetric and the auto-correlations of its absolute returns are stronger than that of its squared returns. An asymmetric returns distribution means that the left and right tails would have different thickness, whereas higher auto-correlation of absolute returns implies that better volatility forecasts are possible. This has significant economic implication for risk management that requires accurate estimation of Value-at-Risk (VaR). In this paper, we therefore investigate the performance of VaR models that take into consideration of the skewness of the innovation process and utilize the Box-Cox transformation of conditional variance in a flexible ARCH-type model. Specifically, we use the Asymmetric Power Autoregressive Conditional Heteroscedasticity (APARCH) model based on the skewed Student density to model the VaRs of daily returns of those Asian markets found to exhibit both skewness and kurtosis in the innovation process. We apply the likelihood ratio tests of proportional failure rates to such VaR model and compare the results with other VaR models, in particular, APARCH with symmetric distributions and APARCH with skewed Student distributions. It is found that the APARCH model with skewed Student distribution performs the best for the Asian markets considered.
dc.format.extent 159 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) International Research Journal of Finance and Economics, 22, 135-143
dc.subject (關鍵詞) Stock Market;Stocks
dc.title (題名) Value-at-Risk for Long and Short Positions of Asian Stock Markets
dc.type (資料類型) articleen