典型事实约束下的上海燃油期货市场动态VaR测度研究

Abstract

Abstract: The high leverage of futures means high-risk, and energy market is always concerned because of its strategic significance. So the risk measure of the energy futures market is very important to both investors and regulators. In this paper, four continuous price series are constructed to reflect different delivery period of oil futures listed in Shanghai. Based on different financial stylized facts, GARCH, GJR and FIGARCH are used to model volatility. Under the assumption of the conditional return obeying normal, student t and skewed student t (skst) distributions, dynamic VaR is measured. Then both LR (Likelihood Ratio) test and DQR (Dynamic Quantile Regression) test are used to backtest the accuracy of these models and try to extract the best valuable stylized facts. The results show that: (1) the dynamic VaR measurement with skst distribution is more accurate; (2) the GJR models based on leverage effect and FIGARCH models based on long memory do not perform better than GARCH model; (3) the average return of far futures is higher and dynamic VaR is easier to measure.

Key words: oil futures, dynamic VaR measurement, stylized facts, backtest

CLC Number:

F830

CHUN Wei-de, CHEN Wang, PAN Pan. A Study on Dynamic VaR Predicting Models for Oil Futures Market of Shanghai[J]. Chinese Journal of Management Science, 2013, (2): 24-31.

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A Study on Dynamic VaR Predicting Models for Oil Futures Market of Shanghai

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