We examine the cross-section of international equity risk premia with machine learning methods. We identify, classify, and calculate 88 market characteristics and use them to forecast country returns with various machine learning techniques. While all algorithms produce substantial economic...

We examine return predictability with machine learning in 46 international stock markets. We calculate 148 stock characteristics and use them to feed a repertoire of different models. The algorithms extract predictability mainly from simple, yet popular, factor types—such as momentum,...

The paper concerns an issue of existence of a risk premium in equity and index futures markets. The paper consists of four parts. The first part describes the basic hypotheses of forward curves in the futures market. In the second section, I formulate 5 hypotheses concerning a risk premium in...

The paper concerns an issue of existence of a risk premium in equity and index futures markets. The paper consists of four parts. The first part describes the basic hypotheses of forward curves in the futures market. In the second section, I formulate 5 hypotheses concerning a risk premium in...

The paper concerns an issue of existence of a risk premium in equity and index futures markets. The paper consists of four parts. The first part describes the basic hypotheses of forward curves in the futures market. In the second section, I formulate 5 hypotheses concerning a risk premium in...

The paper addresses an issue of the performance persistence in a mutual fund market. The study focuses especially on the evidence from Poland. The past performance of mutual funds is widely regarded as a key criterion in investment decision making in Poland nowadays, whereas existing empirical...

We examine whether components of the earnings-to-price (EP) ratio can be used to extract incremental information to better estimate future returns in the cross-section of country-industry indexes. We demonstrate that the EP components such as lagged EP, changes in earnings, short-term momentum,...

We employ a repertoire of machine learning models to explore the cross-sectional return predictability in cryptocurrency markets. While all methods generate substantial economic gains, those that account for nonlinearities and interactions fare the best. The return predictability derives mainly...

Does factor momentum drive the stock price momentum? Inspired by the recent findings from the United States, we revisit this relationship across 51 markets. The factor momentum effect remains strong—both within and across countries—regardless of typical drivers of return predictability....

Does factor momentum drive the stock price momentum? Motivated by the recent findings from the United States, we revisit this relationship across 51 countries. The evidence on factor momentum's ability to capture the stock momentum profits depends fundamentally on methodological and dataset...