Machine learning (ML) models for predicting stock returns are typically trained on one-month forward returns. While these models show impressive full-sample gross alphas, their performance net of transaction costs post 2004 is close to zero. By training on longer prediction horizons and using...

In this article, we advance the use of factor investing across multiple asset classes. It turns out that style factors well established in the equity domain – such as value, momentum or quality – do extend to other asset classes as well. Even more so, multi-asset multi-factors significantly...

We examine the empirical relation between risk and return in emerging equity markets and find that this relation is flat, or even negative. This is inconsistent with theoretical models such as the CAPM, which predict a positive relation, but consistent with the results of studies for developed...

Some exchange-traded funds (ETFs) are specifically designed for harvesting factor premiums, such as the size, value, momentum and low-volatility effects. Other ETFs, however, may implicitly go against these factors. This paper analyzes the factor exposures of US equity ETFs and finds that,...

We dissect the realized performance of factor-based equity portfolios using a characteristics-based multi-factor return model. We show that generic single-factor portfolios, which invest in stocks with high scores on one particular factor, are sub-optimal because they ignore the possibility that...