基于改进的GARCH模型对VaR风险研究

Research on VaR Risk Based on Improved GARCH Model

当前,GARCH模型普遍地被应用在金融资产序列波动性的预测,以及在险价值VaR的计算及市场风险管理中。针对股票市场的特点,采用将交易量与价格极差加入传统的GARCH模型中的方法对上证综合指数进行研究,发现不仅可以改善部分GARCH模型的拟合和预测结果,而且对于金融市场中标的资产的GARCH效应的解释能力逐渐降低,甚至有些资产标的物GARCH效应直接消失了,其中交易量和价格极差作为重要代理变量在关于收益率波动持续性方面表现出良好的解释作用,同时计算向前一步预测的在险价值VaR并对计算出的结果进行检验。实证研究表明,改进后的GARCH模型预测的VaR值相比于传统的GARCH模型计算结果更加准确,降低了VaR失效的概率,使得预测得到的VaR值与实际结果更加接近。

Currently,the GARCH model is widely used in the prediction of the volatility of financial asset sequences and the calculation of VaR at risk and market risk management.According to the characteristics of the stock market,using the method of adding the trading volume and price range difference to the traditional GARCH model to study the Shanghai Composite Index,we found that not only the fitting and forecasting results of some GARCH models can be improved,but also the assets of the underlying financial market.The GARCH effect's explanatory ability gradually decreases and even some asset objects GARCH effect disappears directly.Among them,the trading volume and price difference show a good explanation for the persistence of the yield volatility.At the same time,the VaR value of the forward one step prediction is calculated and calculated.The results are backtested.The results show that the VaR value predicted by the improved GARCH model is more accurate than the traditional GARCH model,reducing the probability of VaR failure and making the estimated VaR closer to the actual results.