The Application of Extreme Value Theory to Risk Measurement Based on SSE-180 Index
2004; Operations Research Society of China; Linguagem: Inglês
ISSN
1007-3221
Autores Tópico(s)Grey System Theory Applications
ResumoThe accurate estimation of Value-at-Risk(VaR) is essential for risk management.In this paper,we use the General Pareto Distribution(GPD)instead of Normal distribution to describe the heavy-tailed characteristic of financial time series.We compare this model with other well-known model such as GARCH(1,1),GARCH(1,1)-t,variance-covariance method and historical simulation.Our studies indicate that the model based on GPD fit better than traditional methods for heavy-tailed distribution on forecasting high quantiles, furthermore, the forecasting results of this model is more stable. This shows that this model is a robust tool to forecast quantiles,which is practical to implement and regulate for VaR measurements.
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