Global adapted solution of one-dimensional backward stochastic Riccati equations, with application to the mean-variance hedging

Michael Kohlmann and Shanjian Tang

Stochastic Processes and their Applications, 2002, vol. 97, issue 2, 255-288

Abstract: Backward stochastic Riccati equations are motivated by the solution of general linear quadratic optimal stochastic control problems with random coefficients, and the solution has been open in the general case. One distinguishing difficult feature is that the drift contains a quadratic term of the second unknown variable. In this paper, we obtain the global existence and uniqueness result for a general one-dimensional backward stochastic Riccati equation. This solves the one-dimensional case of Bismut-Peng's problem which was initially proposed by Bismut (Lecture Notes in Math. 649 (1978) 180). We use an approximation technique by constructing a sequence of monotone drifts and then passing to the limit. We make full use of the special structure of the underlying Riccati equation. The singular case is also discussed. Finally, the above results are applied to solve the mean-variance hedging problem with general random market conditions.

Keywords: Backward; stochastic; Riccati; equation; Linear-quadratic; optimal; stochastic; control; problem; Regular; approximation; Mean-variance; hedging; Feynman-Kac; formula (search for similar items in EconPapers)
Date: 2002
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Citations: View citations in EconPapers (23)

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