Portfolio optimization approaches inevitably rely on multivariate modeling of markets and the economy. In this paper, we address three sources of error related to the modeling of these complex systems: 1.oversimplifying hypothesis; 2. uncertainties resulting from parameters' sampling error; 3....

While common machine learning algorithms focus on minimizing the mean-square errors of model fit, we show that genetic programming, GP, is well-suited to maximize an economic objective, the Sharpe ratio of the usual spread portfolio in the cross-section of expected stock returns. In contrast to...

We present a novel tool for generating speculative and hedging foreign exchange (FX) trading policies. Our solution provides a schedule that determines trades in each rebalancing period based on future currency prices, net foreign account positions, and incoming (outgoing) flows from business...