VaR的风险预测能力分析--基于沪深300指数
首发时间:2018-04-13
摘要:以沪深300指数为例,在1%分位数水平下,运用非条件覆盖检验、独立性检验以及条件覆盖检验后验分析方法,实证对比了参数法(GARCH族模型)和模拟法(历史模拟法、Monte Carlo模拟法和FHS方法)模型对VaR的预测能力的精确差异。研究结果表明:在模拟方法中,FHS方法优于历史模拟法和Monte Carlo模拟法,与参数法相比较,参数法整体优于模拟法,且参数法中TARCH模型是一个相对较优的风险测度模型,说明我国证券市场存在杠杆效应。
关键词: 投资学 后验分析 GARCH族 VaR 模拟法?????
For information in English, please click here
Risk Prediction Capability Analysis of VaR-Based on the CSI 300 Index
Abstract:Taking the Hushen 300 Index as an example, using the 1% quantile level, using the unconditional coverage test, independence test, and conditional coverage test posteriori analysis method, the empirical comparison of the parameter method (GARCH family model) and simulation method (history Precise differences in predictive power of VaR for simulation models, Monte Carlo simulations, and FHS methods). The results show that the FHS method is superior to the historical simulation method and Monte Carlo simulation method in the simulation method. Compared with the parameter method, the parameter method is better than the simulation method as a whole, and the TARCH model in the parameter method is a relatively superior risk measurement model. This shows that there is a leverage effect in China\'s securities market.?
Keywords: Investment Posterior analysis GARCH family VaR simulation
基金:
引用
No.****
同行评议
勘误表
VaR的风险预测能力分析--基于沪深300指数
评论
全部评论0/1000