We compare asset allocations that are derived for cumulative prospect theory (CPT) based on two different methods: maximizing CPT along the mean {variance efficient frontier and maximizing CPT without this restriction. We find that with normally distributed returns, the difference between these...

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...

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...

Contrary to conventional wisdom in nance, return prediction R2 and optimal portfolio Sharpe ratio generally increase with model parameterization, even when minimal regularization is used. We theoretically characterize the behavior of return prediction models in the high complexity regime, i.e....

This paper introduces a sparse and stable optimization approach for a multi-currency asset allocation problem. We study the benefits of joint optimization of assets and currencies as opposed to the standard industry practice of managing currency risk via so-called currency overlay strategies. In...

We introduce a model for portfolio selection with an extendable investment universe where the agent faces a trade-off between exploiting existing and exploring for new investment opportunities. An agent with mean-variance preferences starts with an existing investment universe consisting of a...

We propose a new asset-pricing framework in which all securities' signals are used to predict each individual return. While the literature focuses on each security's own- signal predictability, assuming an equal strength across securities, our framework is flexible and includes...

We study the pricing and hedging of derivative securities with uncertainty about the volatility of the underlying asset. Rather than taking all models from a prespecified class equally seriously, we penalise less plausible ones based on their "distance" to a reference local volatility model. In...