In this paper, we estimate coefficients of bankruptcy forecasting models, such as logistic and neural network models, by maximizing their discriminatory power as measured by the Area Under Receiver Operating Characteristics (AUROC) curve. A method is introduced and compared with traditional...

Motivated by the seasonality found in equity returns, we create a Turn-of-the-Month (ToM) allocation strategy in the U.S. equity market and investigate its value in asset allocation. By using a wide variety of portfolio construction techniques in an attempt to address the impact of estimation...

A multi-factor commodity portfolio combining the momentum, basis, basis-momentum, hedging pressure and value commodity factor portfolios outperforms significantly, economically and statistically, widely used commodity benchmarks. We find evidence that a variance timing strategy applied to...

We develop an analytical solution to the dynamic multi-period portfolio choice problem of an investor with risky liabilities and time varying investment opportunities. We use the model to compare the asset allocation of investors who take liabilities into account, assuming time varying returns...

Estimation errors in the inputs are the main problem when applying portfolio analysis, and Markov regime switching models have been shown to reduce these errors. We investigate whether the use of two regime models remains superior across a range of values of risk aversion and transaction costs,...

We shed new light on the role of commodities in asset allocation for investors with and without liabilities who (a) believe that asset returns are time varying and predictable (b) have short and long term horizons and (c) have access, in addition to a standard passive commodity portfolio, to...