Probabilistic Properties of Stochastic Volatility Models
Probabilistic Properties of Stochastic Volatility Models
复制标题
随机波动率模型的概率性质
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
T. Mikosch
中科院分区：
文献类型：
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作者：
R. Davis;T. Mikosch
我们收集了一些严格平稳随机波动率过程的概率性质。这些包括有关混合，协方差和相关性，矩和尾部行为的属性。我们还研究了随机波动过程的自协方差和自相关函数及其幂的性质，以及这些函数的相应样本版本的渐近理论。与Gynecal模型（见Lindner（2008））相比，随机波动率模型具有更简单的概率结构，这有助于其普及。
We collect some of the probabilistic properties of a strictly stationary stochastic volatility process. These include properties about mixing, covariances and correlations, moments, and tail behavior. We also study properties of the autocovariance and autocorrelation functions of stochastic volatility processes and its powers as well as the asymptotic theory of the corresponding sample versions of these functions. In comparison with the GARCH model (see Lindner (2008)) the stochastic volatility model has a much simpler probabilistic structure which contributes to its popularity.