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...

The COVID-19 pandemic has exerted a remarkable impact on stock market volatility around the globe. Can vaccination programs revert these adverse effects? To answer this question, we scrutinize daily data from 66 countries from January 1st, 2020, to February 18th, 2021. We provide convincing...

We explore the impact of the COVID-19 pandemic on the term structure of interest rates. Using data from developed and emerging countries, we demonstrate that the expansion of the disease significantly affects sovereign bond markets. The growth of confirmed cases significantly widens the term...

We explore the relationship between two novel Twitter-based measures of economic and market uncertainty and the performance of four major cryptocurrencies. Using a battery of methods - quantile regressions, Granger-causality in distributions using copula functions, and directional predictability...

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 relationship between political motivations and underpricing of public offerings of privatized companies is to a great extend unexplored field in the global academic literature. In this paper we offer a new explanation for the IPO underpricing anomaly. We formulate the election gimmick...

IPO anomalies in the corporate debt markets are to great extent unexplored field in the academic literature. The aim of this paper is to investigate the undepricing phenomenon of newly issued corporate bonds on the Catalyst market and its determinants. I use event study methodology to test for...