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	基于广义谱和MCS检验的VaR模型预测绩效评估; Evaluating Predictive Performance of Value-at-Risk Models Based on Generalized Spectrum and MCS Tests
	张玉鹏 ; 洪永淼
	2015-07-20
关键词	VaR模型 预测绩效 涨跌停板制度 广义谱检验 MCS检验 VaR model predictive performance price limit system generalized spectral test MCS test
英文摘要	条件VAr模型的正确设定检验等价于检验均值化的“撞击序列“是否服从鞅差分序列,然而通常的反馈检验方法只检验了该序列的部分性质。采用对该鞅差分性质进行直接检验的广义谱检验方法,全面考察中国股票市场(香港恒生指数、上证综合指数和台湾加权指数)上各参数、非参数和半参数共22个VAr模型在采用滚动窗口预测机制时的样本外预测绩效。鉴于条件VAr模型正确设定检验无法反映超过某VAr水平的尾部风险信息,为避免极端损失的发生以及增加结果的稳健性,同时采用模型置信集检验方法。研究结果表明,采用通常的反馈检验方法常会得出错误的结论;在1%和5%置信水平,与历史模拟法、极值理论模型、CAVIAr模型和CArE模型相比,误差项为T分布的gArCH模型族在金融危机期间具有较好的样本外预测绩效;涨跌停板制度对于选取预测绩效最优的VAr模型具有重要影响。; Conditional VaR models' correct specification test is equivalent to testing the de-meaned hit sequence following a martingale difference sequence( m.d.s),however the commonly used backtesting techniques only test some properties of the sequence.Using generalized spectral test which directly tests the m.d.s property of the de-meaned hit sequence,we evaluate the out-of-sample predictive performance of various parametric,nonparametric and semi-parametric VaR models with a total of 22 models calculated by using rolling predictive method for China's stock markets including Shanghai Composite Index,Hang Seng Index and Taiwan Weighted Index.Because conditional VaR models' correct specification test can not reflect the tail risk information exceeding one specific VaR level,in order to avoid the occurrence of extreme losses as well as to increase the robustness of the results,we adopt MCS( model confidence set) test simultaneously by selecting the asymmetric loss functions proposed by Koenker and Bassett and the magnitude loss function proposed by Lopez.Comparing with SPA( Superior Predictive Ability) test,the main advantage of MCS test is that it does not require a benchmark model to be specified as is the case for SPA tests.It characterizes the entire set of models that are not significantly outperformed by other models,while a test for SPA only provides evidence about the relative performance of a single model( the benchmark).The empirical results imply the following three conclusions: 1it would cause wrong results using the commonly applied backtesting techniques such as Kupiec likelihood ratio test,Christoffersen likelihood ratio test and Engle and Manganelli dynamic quantile test.However adopting generalized spectral test and MCS test with Lopez loss function simultaneously would give us more accurate and robust results.2Comparing with historical simulation models,extreme value theory models,CAViaR and CARE models,the out-of-sample predictive performance of the GARCH family with student-t distribution is the best at 1% and 5% significant level during the financial crisis for these three stock indexes.This implies that the risk characteristics of mainland stock market is getting closer and closer to the mature stock markets of Hong Kong and Taiwan after more than 20 years development.3At 1% significant level,the optimal VaR predictive models of Hang Seng Index include one of the CARE models which can be used to measure extreme loss situation with small probability.This implies that price limit system implemented by Hong Kong yet not by mainland and Taiwan will make Hong Kong's stock market face more risk during the financial crisis.; 国家自然科学基金(71301053); 教育部人文社会科学研究青年基金项目(13YJC790211)~~
语种	zh_CN
内容类型	期刊论文
源URL	[http://dspace.xmu.edu.cn/handle/2288/121249]
专题	王亚南院－已发表论文
推荐引用方式 GB/T 7714	张玉鹏,洪永淼. 基于广义谱和MCS检验的VaR模型预测绩效评估, Evaluating Predictive Performance of Value-at-Risk Models Based on Generalized Spectrum and MCS Tests[J],2015.
APA	张玉鹏,&洪永淼.(2015).基于广义谱和MCS检验的VaR模型预测绩效评估..
MLA	张玉鹏,et al."基于广义谱和MCS检验的VaR模型预测绩效评估".(2015).

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