This paper compares various machine learning models to predict the cross-section of
emerging market stock returns. We document that allowing for non-linearities and …

Although factor premiums originate in both long and short legs of factor portfolios, we found
that (1) most added value comes from the long legs,(2) the long legs offer more …

We identify the characteristics and specifications that drive the out-of-sample performance of
machine-learning models across an international data sample of nearly 1.9 billion stock …

We examine the predictability of 299 capital market anomalies enhanced by 30 machine
learning approaches and over 250 models in a dataset with more than 500 million firm …

Motivated by recent findings from the equity market, we investigate non-standard errors in
cryptocurrency research. We examine ten prevalent decisions related to data sources …

In contrast to finding better monthly performance shown in a specific month, such as the
January effect (ie, better stock price performance in January as opposed to other months) …

Предмет. Феномен цифровых финансовых активов является сравнительно новым. В их
структуре все большую долю занимают виртуальные валюты, в частности …

This paper shows that low-risk stocks significantly outperform high-risk stocks in the local
China A-share market. The main driver of this low-risk anomaly is volatility, and not beta. A …

Purpose In the present study, we investigate whether enhanced momentum strategies
outperform price momentum strategies and if they show greater resilience and stability …

After long being one of the main puzzles in asset pricing, momentum has ironically become
a case of observational equivalence. It can now be explained both by behavioral factors …