In the basic mean/variance framework, a stock's weight in effcient portfolios goes up if its expected rate of return goes up. In more complicated, realistic portfolio choice problems, surprising effects can occur.

In the basic Markowitz and Merton models, a stock's weight in efficient portfolios goes up if its expected rate of return goes up. Put differently, there are no financial Giffen goods. By an example from mortgage choice we illustrate that for more complicated portfolio problems Giffen effects do...

We derive no-arbitrage bounds for expected excess returns to generate scenarios used in financial applications. The bounds allow to distinguish three regions: one where arbitrage opportunities will never exist, a second where arbitrage may be present, and a third, where arbitrage opportunities...

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

Ledermann et al. (2011) propose random orthogonal matrix (ROM) simulation for generating multivariate samples matching means and covariances exactly. Its computational efficiency compared to standard Monte Carlo methods makes it an interesting alternative. In this paper we enhance this method׳s...

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...

No-arbitrage interest rate models are designed to be consistent with the current term structure of interest rates. The diffusion of the interest rates is often approximated with a tree, in which the scenario-dependent fair price of any security is calculated as the present value of the...

Many numerical optimization methods use scenario trees as a discrete approximation for the true (multi-dimensional) probability distributions of the problem's random variables. Realistic specifications in financial optimization models can lead to tree sizes that quickly become computationally...