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題名：緩長記憶波動模型之風險值計算--以臺灣加權股價指數為例
書刊名：東吳經濟商學學報
作者：張揖平 引用關係／洪明欽 引用關係／林彥豪
作者(外文)：Chang, Yi-ping／Hung, Ming-chin／Lin, Yen-hao
出版日期：2003
卷期：43
頁次：頁79-103
主題關鍵詞：緩長記憶；FIGARCH模型；風險值；Value at risk；Long memory；FIGARCH model
原始連結：連回原系統網址new window
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風險值 (Value-at-Risk) 是目前廣為國際金融機構接受的一個風險管理機制，因此，風險值的精準估算已經成為金融機構免除危機的重要關鍵。在計算風險值時，若可以精準估計金融資產的波動度，應較能精確估算風險值，並有效控制金融市場的風險。由於許多實證研究發現金融資產報酬率之波動常具有緩長記憶 (long memory) 性，因此本研究將在資產報酬率之波動具有緩長記憶的假設下，探討Baillie、Bollerslev及Mikkelsen (1996) 提出的部分整合自迴歸條件異質變異數 (fractionally integrated generalized autoregressive conditional heteroskedasticity；簡稱FIGARCH) 模型之風險值計算法。最後，以台灣加權股價指數為標的資產，發現報酬率之波動度具有緩長記憶現象，且FIGARCH模型之風險值計算法的表現亦不錯。
The volatility of financial time series plays an important role in many applications, especially in the field of risk management. More recently, many studies suggest that the long memory phenomenon do exist in the conditional volatility of financial data. The new class of fractionally integrated generalized autoregressive conditional heteroskedasticity (FIGARCH) model proposed by Baillie, Bollerslev, and Mikkeisen (1996) can allow for this long memory property in the conditional variance. In this paper, we use the FIGARCH model to compute Value at Risk (VaR) measure for daily stock returns. The empirical examples with stock returns show that FIGARCH model provides a good representation in VaR framework.
期刊論文
1.Bollerslev, T.、Mikkelsen, H. O.(1999)。Long-term equity anticipation securities and stock market volatility dynamics。Journal of Econometrics，92(1)，75-99。  new window
2.Beine, M.、Laurent, S.、Lecourt, C.(2002)。Accounting for conditional leptokurtosis and closing days effects in FIGARCH models of daily exchange rates。Applied Financial Economics，12(8)，589-600。  new window
3.Hull, John C.、White, Alan D.(1998)。Value at risk when daily changes in market variables are not normally distributed。Journal of Derivatives，5(3)，9-19。  new window
4.Ding, Z.、Granger, C. W. J.(1996)。Modeling volatility persistence of speculative returns: a new approach。Journal of Econometrics，73，185-215。  new window
5.洪明欽、王德仁(20010600)。臺股加權指數風險值評估--分位數迴歸法之探討。東吳經濟商學學報，33，19-39。new window  延伸查詢new window
6.Berndt, Ernst R.、Hall, Bronwyn H.、Hall, Robert E.、Hausman, Jerry A.(1974)。Estimation and Inference in Nonlinear Structural Models。Annals of Economic and Social Measurement，3(4)，653-665。  new window
7.Engle, Robert F.、Bollerslev, Tim(1986)。Modelling the Persistence of Conditional Variances。Econometric Reviews，5(1)，1-50。  new window
8.Bollerslev, Tim(1986)。Generalized Autoregressive Conditional Heteroskedasticity。Journal of Econometrics，31(3)，307-327。  new window
9.Bollerslev, Tim(1987)。A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return。The Review of Economics and Statistics，69(3)，542-547。  new window
10.Bollerslev, Tim、Mikkelsen, Hans Ole(1996)。Modeling and Pricing Long Memory in Stock Market Volatility。Journal of Econometrics，73(1)，151-184。  new window
11.Bollerslev, Tim、Chou, Ray Y.、Kroner, Kenneth F.(1992)。ARCH Modeling in Finance: A Review of the Theory and Empirical Evidence。Journal of Econometrics，52(1/2)，5-59。  new window
12.Bollerslev, Tim、Wooldridge, Jeffrey M.(1992)。Quasi Maximum Likelihood Estimation and Inference in Dynamic Models with Time Varying Covariances。Econometric Reviews，11(2)，143-172。  new window
13.Andersen, Torben G.、Bollerslev, Tim、Diebold, Francis X.、Ebens, Heiko(2001)。The Distribution of Realised Stock Return Volatility。Journal of Financial Economics，61(1)，43-76。  new window
14.Andersen, Torben G.、Bollerslev, Tim、Diebold, Francis X.、Labys, Paul(2001)。The Distribution of Realized Exchange Rate Volatility。Journal of the American Statistical Association，96(453)，42-55。  new window
15.Baillie, Richard T.、Bollerslev, Tim、Mikkelsen, Hans O.(1996)。Fractionally Integrated Generalize Autoregressive Conditional Heteroskedasticity。Journal of Econometrics，74(1)，3-30。  new window
16.Ding, Zhuanxin、Granger, Clive W. J.、Engle, Robert F.(1993)。A long memory property of stock market returns and a new model。Journal of Empirical Finance，1(1)，83-106。  new window
17.Engle, Robert F.(1982)。Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation。Econometrica，50(4)，987-1008。  new window
18.Nelson, Daniel B.(1991)。Conditional Heteroskedasticity in Asset Returns: A New Approach。Econometrica: Journal of the Econometric Society，59(2)，347-370。  new window
圖書
1.Morgan, J. P.(1996)。Riskmetrics Technical Document。New York, NY：Morgan Guaranty Trust Company。  new window
2.Penza, P.、Bansal, V. K.(2001)。Measuring Market Risk with Value at Risk。New York：Wiley。  new window
其他
1.洪明欽(2002)。結合類神經網路與分位元數迴歸模型之風險值估計。new window  延伸查詢new window
2.Baillie, R. T., A. A. Cecen, and Y. W. Han(2000)。High Frequency Deutsche Mark-US Dollar Returns: FIGARCH Representations and Nonlinearities。  new window
3.Beltratti, A. and C. Morana(1999)。Computing Value at Risk with High Frequency Data。  new window
4.Breidt, F. J., N. Crato, and P. De Lima(1998)。The Detection and Estimation of Long Memory in Stochastic Volatility。  new window
5.Brunetti, C. and C. L. Gilbert(2000)。Bivariate FIGARCH and Fractional Cointegration。  new window
6.Caporin, M.(2002)。FIGARCH model: Stationarity, Estimation Methods and the Identidication Problem。  new window
7.Chung, C, F.(1999)。Estimating the Fractionnally Intergrated GARCH Model。  new window
8.Jorion, P(2000)。Value at Risk: the New Banchmark for Controlling Market Risk，Chicago：McGraw-Hill。  new window
9.Lee, S. W. and B. E Hansen(1994)。Asymptotic Theory for the GARCH Quasi-Maximum Likelihood Estimator。  new window
10.Vilasuso, J.(2002)。Forecasting Exchange Rate Volatility。  new window
 
 
 
 
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