Volatility modeling in a Markovian environment: Two Ornstein-Uhlenbeck-related approaches

Anita Behme
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Abstract

We introduce generalizations of the COGARCH model of Kl\"uppelberg et al. from 2004 and the volatility and price model of Barndorff-Nielsen and Shephard from 2001 to a Markov-switching environment. These generalizations allow for exogeneous jumps of the volatility at times of a regime switch. Both models are studied within the framework of Markov-modulated generalized Ornstein-Uhlenbeck processes which allows to derive conditions for stationarity, formulas for moments, as well as the autocovariance structure of volatility and price process. It turns out that both models inherit various properties of the original models and therefore are able to capture basic stylized facts of financial time-series such as uncorrelated log-returns, correlated squared log-returns and non-existence of higher moments in the COGARCH case.
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马尔可夫环境中的波动建模:两种与奥恩斯坦-乌伦贝克相关的方法
我们将 2004 年 Kl\"uppelberg 等人的 COGARCH 模型以及 2001 年 Barndorff-Nielsen 和 Shephard 的波动率和价格模型推广到马尔可夫转换环境中。这些概括允许在制度转换时出现波动率的前向跳跃。这两个模型都是在马尔可夫调制广义奥恩斯坦-乌伦贝克过程的框架内进行研究的,因此可以推导出静止性条件、公式方程以及波动率和价格过程的自协方差结构。结果表明,这两种模型都继承了原始模型的各种特性,因此能够捕捉金融时间序列的基本风格化事实,如不相关的对数收益率、相关的平方对数收益率以及 COGARCH 情况下不存在高阶矩。
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