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CONTINUOUS TIME WISHART PROCESS FOR STOCHASTIC RISK

机译:连续时间Wishart随机风险过程

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摘要

Risks are usually represented and measured by volatility-covolatility matrices. Wishart processes are models for a dynamic analysis of multivariate risk and describe the evolution of stochastic volatility-covolatility matrices, constrained to be symmetric positive definite. The autoregressive Wishart process (WAR) is the multivariate extension of the Cox, Ingersoll, Ross (CIR) process introduced for scalar stochastic volatility. As a CIR process it allows for closed-form solutions for a number of financial problems, such as term structure of T-bonds and corporate bonds, derivative pricing in a multivariate stochastic volatility model, and the structural model for credit risk. Moreover, the Wishart dynamics are very flexible and are serious competitors for less structural multivariate ARCH models.
机译:风险通常由波动率-波动率矩阵表示和度量。 Wishart过程是动态分析多元风险的模型,描述了随机波动率-波动率矩阵的演化,约束为对称正定。自回归Wishart过程(WAR)是为标量随机波动率引入的Cox,Ingersoll,Ross(CIR)过程的多元扩展。作为CIR流程,它允许解决许多财务问题的封闭式解决方案,例如T债券和公司债券的期限结构,多元随机波动率模型中的衍生产品定价以及信用风险的结构模型。此外,Wishart动力学非常灵活,并且是结构较少的多元ARCH模型的有力竞争者。

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