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投资风格漂移是把双刃剑,基金在获取短期超额收益的同时,其背后也折射出巨大的漂移风险。本文以2004年成立的8只开放式股票型基金为研究样本,在量化基金投资风格漂移收益及分析其序列呈尖峰、厚尾与有偏特征的基础上,通过引入skt分布来刻画新生变量的分布,构建ARFIMA-HYGARCH-VaR模型来测度基金投资风格漂移风险值,并与skt分布下的RiskMetrics及GARCH族等5种VaR模型的风险测度能力做了比较实证分析,同时对各种VaR模型进行失败频率回测检验与动态分位数测试。研究结果表明:在不同显著性水平下,skt分布下的各种模型基本都有较好的风险测度能力,但ARFIMA-HYGARCH模型的VaR风险测度更加精确与稳定;Person吻合度检验也证实了skt分布能较好刻画投资风格漂移日收益序列的分布。本研究为控制较严重的投资风格漂移及规范基金产品创新设计与发行无疑具有重要的理论价值与现实意义。
Investment style drift is double-edged sword, the fund in obtaining short-term excess returns, but also reflects the back of a huge drift risk. In this paper, eight open-ended equity funds, established in 2004, are used as research samples. Based on quantifying the return of fund investment style drift and analyzing its spikes, thick tails and biased features, we introduce the skt distribution to characterize the new variables Distribution, and build ARFIMA-HYGARCH-VaR model to measure the value of fund investment style drift risk, and with the skt distribution of RiskMetrics and GARCH family of five kinds of VaR models such as the ability to measure the risk of a comparative empirical analysis of various VaR models at the same time Failure frequency backtesting test and dynamic quantile test. The results show that under different levels of significance, all models under the skt distribution have better risk measurement ability, but the VaR risk measure of ARFIMA-HYGARCH model is more accurate and stable. The fit test of Person also confirms that skt The distribution can well characterize the distribution of income-style earnings drifts. This study undoubtedly has important theoretical and practical significance for controlling the more serious investment style drift and for standardizing the innovative design and distribution of fund products.