Volatility Model for Financial Market Risk Management : An Analysis on JSX Index Return Covariance Matrix
In measuring risk, practitioners have practiced one of the two extreme approaches for so long, i.e. historical simulation or risk metrics. Meanwhile, academicians tend to apply methods based on the latest development in financial econometrics. In this study, we try to assess one of important issues in financial econometric development that focuses on market risk measurement and management employing asset-based models, i.e. models that apply dimensional covariance matrix, which is relevant to practice world. We compare covariance matrix model with Exponential Smoothing Model and GARCH Derivation and the Associated Derivation Models, using JSX Stock price Index data in 2000-2005. The result of this study shows how applicable the observed financial econometric instrument in Financial Market Risk Management practice.
|Date of creation:||Sep 2009|
|Date of revision:||Sep 2009|
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- Aggarwal, Reena & Inclan, Carla & Leal, Ricardo, 1999. "Volatility in Emerging Stock Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(01), pages 33-55, March.
- Tim Bollerslev, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
EERI Research Paper Series
EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
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