Mean-Variance Hedging and Forward-Backward Stochastic Differential Filtering Equations | Zendy

Guangchen Wang | Zendy; Zhen Wu | Zendy

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Mean-Variance Hedging and Forward-Backward Stochastic Differential Filtering Equations

Author(s) -

Guangchen Wang,

Zhen Wu

Publication year - 2011

Publication title -

abstract and applied analysis

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.228

H-Index - 56

eISSN - 1687-0409

pISSN - 1085-3375

DOI - 10.1155/2011/310910

Subject(s) - mathematics , stochastic differential equation , variance (accounting) , stochastic control , markov chain , optimal control , quadratic equation , partial differential equation , mathematical economics , mathematical optimization , mathematical analysis , economics , statistics , geometry , accounting

This paper is concerned with a mean-variance hedging problem with partial information, where the initial endowment of an agent may be a decision and the contingent claim is a random variable. This problem is explicitly solved by studying a linear-quadratic optimal control problem with non-Markov control systems and partial information. Then, we use the result as well as filtering to solve some examples in stochastic control and finance. Also, we establish backward and forward-backward stochastic differential filtering equations which are different from the classical filtering theory introduced by Liptser and Shiryayev (1977), Xiong (2008), and so forth

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