Mean-Variance Hedging and Forward-Backward Stochastic Differential Filtering Equations
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-Marko...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2011-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2011/310910 |
| Summary: | 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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| ISSN: | 1085-3375 1687-0409 |