## The Annals of Applied Probability

### Cone-constrained continuous-time Markowitz problems

#### Abstract

The Markowitz problem consists of finding, in a financial market, a self-financing trading strategy whose final wealth has maximal mean and minimal variance. We study this in continuous time in a general semimartingale model and under cone constraints: trading strategies must take values in a (possibly random and time-dependent) closed cone. We first prove existence of a solution for convex constraints by showing that the space of constrained terminal gains, which is a space of stochastic integrals, is closed in $L^{2}$. Then we use stochastic control methods to describe the local structure of the optimal strategy, as follows. The value process of a naturally associated constrained linear-quadratic optimal control problem is decomposed into a sum with two opportunity processes $L^{\pm}$ appearing as coefficients. The martingale optimality principle translates into a drift condition for the semimartingale characteristics of $L^{\pm}$ or equivalently into a coupled system of backward stochastic differential equations for $L^{\pm}$. We show how this can be used to both characterize and construct optimal strategies. Our results explain and generalize all the results available in the literature so far. Moreover, we even obtain new sharp results in the unconstrained case.

#### Article information

Source
Ann. Appl. Probab., Volume 23, Number 2 (2013), 764-810.

Dates
First available in Project Euclid: 12 February 2013

https://projecteuclid.org/euclid.aoap/1360682029

Digital Object Identifier
doi:10.1214/12-AAP855

Mathematical Reviews number (MathSciNet)
MR3059275

Zentralblatt MATH identifier
1268.91162

#### Citation

Czichowsky, Christoph; Schweizer, Martin. Cone-constrained continuous-time Markowitz problems. Ann. Appl. Probab. 23 (2013), no. 2, 764--810. doi:10.1214/12-AAP855. https://projecteuclid.org/euclid.aoap/1360682029

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