Estimation of Value-at-Risk under jump dynamics and asymmetric information
This paper employs three Value-at-Risk (VaR) models (GARJI, ARJI and asymmetric GARCH) to compare the performance of 1-day-ahead VaR estimates. The influences of price jumps and asymmetric information on the performance of VaR are investigated. Two stock indices (Dow Jones and S&P 500) and one exchange rate (Japanese yen) are illustrated for estimating the model-based VaR. The results suggest for asset returns which exhibit time-variant jumps and information asymmetry, the VaR estimates generated by the GARJI and ARJI models provide reliable accuracy for low and high confidence levels. Moreover, as MRSB indicated, the GARJI model is more efficient than alternative models.
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Volume (Year): 15 (2005)
Issue (Month): 15 ()
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References listed on IDEAS
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- Jose A. Lopez, 1999.
"Methods for evaluating value-at-risk estimates,"
Federal Reserve Bank of San Francisco, pages 3-17.
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- Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
- Philippe Jorion, 1988. "On Jump Processes in the Foreign Exchange and Stock Markets," Review of Financial Studies, Society for Financial Studies, vol. 1(4), pages 427-445.
- Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
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