Alternative Asymmetric Stochastic Volatility Models
Alternative Asymmetric Stochastic Volatility Models
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DOI：
10.1080/07474938.2011.553156
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发表时间：
2009-08
影响因子：
1.2
通讯作者：
Manabu Asai;Michael McAleer
中科院分区：
文献类型：
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作者：
Manabu Asai;Michael McAleer
随机波动率模型通常通过引入创新收益与波动率之间的负相关关系来引入不对称效应。本文提出了一种新的基于杠杆效应和规模效应的非对称随机波动模型。该模型是对Nelson（1991）的指数GARCH （EGARCH）模型的推广。我们考虑了不对称效应的类别，它描述了EGARCH模型的不对称效应、Glosten等人（1992）的阈值效应指标函数以及收益创新与波动率之间的负相关之间的差异。采用Liesenfeld和Richard（2003）的有效重要抽样方法对新模型进行估计，并利用数值模拟研究了估计器的有限样本性质。使用四个金融时间序列来估计非对称随机波动率（SV）模型，发现经验不对称效应在每种情况下都具有统计显著性。标准普尔500指数和日元/美元收益率的实证结果表明，杠杆效应和规模效应显著，支持一般模型。对于东京股票价格指数（TOPIX）和美元/澳元收益，规模效应不显著，收益创新与波动率呈负相关。我们还考虑标准化的t分布来捕捉尾部行为。日元/美元回报的结果表明该模型是正确指定的，而其他三个数据集的结果表明有改进的余地。
The stochastic volatility model usually incorporates asymmetric effects by introducing the negative correlation between the innovations in returns and volatility. In this paper, we propose a new asymmetric stochastic volatility model, based on the leverage and size effects. The model is a generalization of the exponential GARCH (EGARCH) model of Nelson (1991). We consider categories for asymmetric effects, which describes the difference among the asymmetric effect of the EGARCH model, the threshold effects indicator function of Glosten et al. (1992), and the negative correlation between the innovations in returns and volatility. The new model is estimated by the efficient importance sampling method of Liesenfeld and Richard (2003), and the finite sample properties of the estimator are investigated using numerical simulations. Four financial time series are used to estimate the alternative asymmetric stochastic volatility (SV) models, with empirical asymmetric effects found to be statistically significant in each case. The empirical results for S&P 500 and Yen/USD returns indicate that the leverage and size effects are significant, supporting the general model. For Tokyo stock price index (TOPIX) and USD/AUD returns, the size effect is insignificant, favoring the negative correlation between the innovations in returns and volatility. We also consider standardized t distribution for capturing the tail behavior. The results for Yen/USD returns show that the model is correctly specified, while the results for three other data sets suggest there is scope for improvement.