We solve the problem of mean-variance hedging for general semimartingale models via stochastic control methods. After proving that the value process of the associated stochastic control problem has a quadratic structure, we characterise its three coefficient processes as solutions of...

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...

An equivalent sigma-martingale measure (EsigmaMM) for a given stochastic process S is a probability measure R equivalent to the original measure P such that S is an R-sigma-martingale. Existence of an EsigmaMM is equivalent to a classical absence-of-arbitrage property of S, and is invariant if...

We construct portfolios with an alternative selection criterion, the Omega function, which can be expressed as the ratio of two partial moments of the returns distribution. Finding Omega-optimal portfolios, in particular under realistic constraints like cardinality restrictions, requires to...

This chapter gives an overview of current research in evolutionary finance. We mainly focus on the survival and stability properties of investment strategies associated with the Kelly rule. Our approach to the study of the wealth dynamics of investment strategies is inspired by Darwinian ideas...

This paper analyzes competition between mutual funds in a multiple funds version of the model of Hugonnier and Kaniel. We characterize the set of equilibria for this delegated portfolio management game and show that there exists a unique Pareto optimal equilibrium. The main result of this paper...

We implement a long-horizon static and dynamic portfolio allocation involving a risk-free and a risky asset. This model is calibrated at a quarterly frequency for ten European countries. We also use maximum-likelihood estimates and Bayesian estimates to account for parameter uncertainty. We find...