Optimal investment problems and volatility homogenization approximations. (English) Zbl 1104.91302

Jonsson, Mattias; Sircar, Ronnie

Bourlioux, Anne (ed.) et al., Modern methods in scientific computing and applications. Proceedings of the NATO Advanced Study Institute and Séminaire de Mathématiques Supérieures on modern methods in scientific computing and applications, Montréal, Québec, Canada, July 9–20, 2001. Dordrecht: Kluwer Academic Publishers (ISBN 1-4020-0782-5/pbk). NATO Sci. Ser. II, Math. Phys. Chem. 75, 255-281 (2002).

Summary: We describe some stochastic control problems in financial engineering arising from the need to find investment strategies to optimize some goal. Typically, these problems are characterized by nonlinear Hamilton-Jacobi-Bellman partial differential equations, and often they can be reduced to linear PDEs with the Legendre transform of convex duality. One situation where this cannot be achieved is in a market with stochastic volatility. In this case, we discuss an approximation using asymptotic analysis in the limit of fast mean-reversion of the process driving volatility. Simulations illustrate that marginal improvement can be achieved with this approach even when volatility is not fluctuating that rapidly.
For the entire collection see [Zbl 1045.65001].

MSC:

91G10	Portfolio theory
93E20	Optimal stochastic control

Keywords:

stochastic control problems; Hamilton-Jacobi-Bellman partial differential equations; stochastic volatility