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. © 2011 Guangchen Wang and Zhen Wu.
CITATION STYLE
Wang, G., & Wu, Z. (2011). Mean-variance hedging and forward-backward stochastic differential filtering equations. Abstract and Applied Analysis, 2011. https://doi.org/10.1155/2011/310910
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