Dynamic Mean-Variance Optimisation Problems with Deterministic Information
30 Pages Posted: 12 Oct 2017 Last revised: 23 Feb 2018
Date Written: September 29, 2017
Abstract
We solve the problems of mean-variance hedging (MVH) and mean-variance portfolio selection (MVPS) under restricted information. We work in a setting where the underlying price process S is a semimartingale, but not adapted to the filtration G which models the information available for constructing trading strategies. We choose as G = Fdet the zero-information filtration and assume that S is a time-dependent affine transformation of a square-integrable martingale. This class of processes includes in particular arithmetic and exponential Lévy models with suitable integrability. We give explicit solutions to the MVH and MVPS problems in this setting, and we show for the Lévy case how they can be expressed in terms of the Lévy triplet.
Keywords: Mean-Variance Hedging, Mean-Variance Portfolio Selection, Restricted Information, Partial Information, Deterministic Strategies, Quadratic Optimisation Problems, Nancial Markets, Type (A) Semimartingales
JEL Classification: G11, G13, C61, C60
Suggested Citation: Suggested Citation