Taking the perspective of international asset allocation, this paper tests if predictive regressions conditional on time-series and cross-sectional information can improve forecasts of stock index returns. We use different current price-to-fundamental ratios as predictors and condition the...

This article provides a portfolio optimization approach that takes into account extreme events. By merging a (downside only) panic copula with the empirical marginal distributions, panic-awareness is attained for the optimization process. This approach includes the likelihood of highly...

Common research suggests that investor sentiment is negatively related to future stock returns and positively related to future volatility. I incorporate this idea in the asset allocation process by blending both views on the expected return and the conditional value at risk (CVaR) based on...

This article demonstrates how to directly incorporate common value investing ideas in the portfolio optimization process. Through minimizing the relative entropy, multiple value rankings are merged with the historical return distribution. This approach yields performance improvements both from a...

We extract information on relative shopping interest from Google search volume and provide a genuine and economically meaningful approach to directly incorporate this data into a portfolio optimization technique. By generating a firm ranking based on a Google search volume metric, we can predict...