马尔可夫过程的多变量时间变换及其金融应用

MULTIVARIATE SUBORDINATION OF MARKOV PROCESSES WITH FINANCIAL APPLICATIONS

Mathematical Finance · 2014
被引 33
ABS 3

中文导读

提出多变量时间变换方法,用独立马尔可夫过程与多维时间变化构建新过程,允许状态依赖跳跃和违约,为金融中的多资产模型(如信用-权益统一模型、相关商品模型)提供灵活架构。

Abstract

This paper develops the procedure of multivariate subordination for a collection of independent Markov processes with killing. Starting from d independent Markov processes with killing and an independent d ‐dimensional time change , we construct a new process by time, changing each of the Markov processes with a coordinate . When is a d ‐dimensional Lévy subordinator, the time changed process is a time‐homogeneous Markov process with state‐dependent jumps and killing in the product of the state spaces of . The dependence among jumps of its components is governed by the d ‐dimensional Lévy measure of the subordinator. When is a d ‐dimensional additive subordinator, Y is a time‐inhomogeneous Markov process. When with forming a multivariate Markov process, is a Markov process, where each plays a role of stochastic volatility of . This construction provides a rich modeling architecture for building multivariate models in finance with time‐ and state‐dependent jumps, stochastic volatility, and killing (default). The semigroup theory provides powerful analytical and computational tools for securities pricing in this framework. To illustrate, the paper considers applications to multiname unified credit‐equity models and correlated commodity models.

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