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...

The emerging literature suggests that machine learning (ML) is beneficial in many asset pricing applications because of its ability to detect and exploit nonlinearities and interaction effects that tend to go unnoticed with simpler modelling approaches. In this paper, we discuss the promises and...

We explore the cross-section of factor returns using a sample of 150+ equity factors. Most factors exhibit a positive premium and a negative market beta in the long run. Factor themes with a clear positive beta, in particular low leverage and size, have no alpha after controlling for this beta...

This paper seeks to uncover the drivers of the idiosyncratic momentum anomaly. We show that: (I) idiosyncratic momentum is a distinct phenomenon that exists next to conventional momentum and is not explained by it; (ii) idiosyncratic momentum is priced in the cross-section of stock returns after...

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...

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,...

The added value of smart beta indices is known to be explained by exposures to established factor premiums, but does that make these indices suitable for implementing a factor investing strategy? This paper finds that the amount of factor exposure provided by popular smart beta strategies...

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 U.S. equity ETFs and finds that,...

In this study we evaluate the performance of actively managed equity mutual funds against a set of passively managed index funds. We find that the return spread between the best performing actively managed funds and a factor-mimicking portfolio of passive funds is positive and as large as 3 to 5...

In this paper we examine a momentum strategy based on residual stock returns. We find that residual momentum exhibits risk-adjusted profits that are about twice as large as those associated with total return momentum. Moreover, we find that the main arguments that have been put forward in the...