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鉴于波动率研究的一个重要应用是金融风险管理,提出在风险管理视角下比较各种高频波动率测度。具体考虑已实现波动、双幂次变差、中位数已实现波动、双尺度已实现波动、已实现极差和最优线性组合已实现波动,借助偏学生t分布假设下的Realized GARCH模型,预测未来一日,五日、十日和二十日的在险价值(VaR),并从统计精度、监管精度、资本运作效率和巴塞尔Ⅱ规定的市场风险资本需求四个角度,对六种不同高频波动率测度的VaR预测效果进行比较。使用沪深300指数1分钟数据的实证表明,最优线性组合已实现波动产生的VaR预测具有明显最低的市场风险资本需求,较高的监管精度和较高的资本运作效率,以及最高的统计精度,是风险管理视角下比较可靠的高频波动率测度。
As an important application of volatility research is financial risk management, it is proposed to compare various high-frequency volatility measures from the perspective of risk management. Considering the realized volatility, the bimodulus, the median has fluctuated, the double scale has realized the volatility, the optimal linear combination has been achieved and the optimal linear combination has been realized. With the help of the Realized GARCH model under the bias of t-distribution of students, Forecast the value at risk (VaR) of the next day, the 5th, the 10th and the 20th, and from the four angles of statistical accuracy, regulatory accuracy, efficiency of capital operation and market risk capital required by Basel II, VaR forecasting results of different high frequency volatility measures are compared. Empirical evidence using the Shanghai-Shenzhen 300 Index for 1-minute data shows that the VaR forecast for volatility-generated optimal linear portfolios has significantly lower capital requirements for market risk, higher regulatory accuracy and higher capital operating efficiency, as well as the highest statistical accuracy , Is a more reliable high-frequency volatility measure from the perspective of risk management.