Earning forecasts disclosed by financial analysts are known to be overly optimistic. Since an investor relies on their expertise, the question arises whether he would take analyst recommendations at face value or instead structure consultation with differently upward-biased analysts in a way...

Many optimization-based portfolio rules fail to beat the simple 1/N rule out-of-sample because of parameter uncertainty. In this paper we suggest a grouping strategy in which we first form groups of equally weighted stocks and then optimize over the resulting groups only. This strategy aims at...

We analyze the relation between earning forecast accuracy and expected profitability of financial analysts. Modeling forecast errors with a multivariate Gaussian distribution, a complete characterization of the payoff of each analyst is provided. In particular, closed-form expressions for the...

Stochastic linear programming is a suitable numerical approach for solving practical asset-liability management problems. In this paper, we consider a multi-stage setting under time-varying investment opportunities and propose a decomposition of the benefits in dynamic re-allocation and...

We investigate whether the returns of some industry portfolios predict the returns of other industry portfolios. We find a strong lead-lag structure which is statistically and economically significant. These findings suggest that information diffuses only gradually across industries. Moreover,...