In this paper, we propose multi-stage stochastic linear programming for asset-liability management under time-varying investment opportunities. We use a first-order unrestricted vector autoregressive process to model predictability in the asset returns and the state variables, where - additional...

In this paper, we propose multi-stage stochastic linear programming for asset-liability management under time-varying investment opportunities. We use a first-order unrestricted vector autoregressive process to model predictability in the asset returns and the state variables, where - additional...

Purpose: Hailstorms are a major risk in agriculture. In order to mitigate the negative consequences on farm revenues, in the present paper the authors analyse the choice between insurance contracts and anti-hail nets. Furthermore, the authors discuss the consequences of anti-hail nets adoption...

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...

We optimize the asset allocation, consumption and bequest decisions of an investor with uncertain lifetime and under time-varying investment opportunities. The asset menu is given by stocks, zero coupon bonds and pure endowments with different maturities. The latter are contingent on either a...

Most portfolio selection rules based on the sample mean and covariance matrix perform poorly out-of-sample. Moreover, there is a growing body of evidence that such optimization rules are not able to beat simple rules of thumb, such as 1/N. Parameter uncertainty has been identified as one major...

This paper analyzes empirically the relation between financial analysts' recommendation profitability and their forecast accuracy and shows that contrary to intuition the group of most successful recommendations is not associated with the highest accuracy on average. The finding that best...