Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

We survey the nascent literature on machine learning in the study of financial markets. We
highlight the best examples of what this line of research has to offer and recommend …

Several papers argue that financial economics faces a replication crisis because the
majority of studies cannot be replicated or are the result of multiple testing of too many …

We examine the effect of environment, social, and governance (ESG) score on stock returns
in the United Kingdom (UK). Consistent with Hong and Kacperczyk (2009), Bolton and …

In the investment theory, firms with high expected investment growth earn higher expected
returns than firms with low expected investment growth, holding investment and expected …

We find that three factors—cryptocurrency market, size, and momentum—capture the cross‐
sectional expected cryptocurrency returns. We consider a comprehensive list of price‐and …

We construct a comprehensive dataset on a near universe of non-fungible token (NFT)
transactions, create indices for the NFT market and its components, and analyze their …

An AI analyst trained to digest corporate disclosures, industry trends, and macroeconomic
indicators surpasses most analysts in stock return predictions. Nevertheless, humans win …

Patents and citations are powerful tools increasingly used in financial economics (and
management research more broadly) to understand innovation. Biases may result, however …

We provide first-time evidence on whether market-wide physical or transition climate risks
are priced in US stocks. Textual and narrative analysis of Reuters climate-change news over …