Behavioral finance studies the application of psychology to finance, with a focus on
individual-level cognitive biases. I describe here the sources of judgment and decision …

Diversification is one of the major components of investment decision-making under risk or
uncertainty. However, paradoxically, as the 2007–2009 financial crisis revealed, the concept …

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 …

Using environmental, social, and governance (ESG) ratings from seven different data
providers for a sample of firms in the S&P 500 Index between 2010 and 2017, we studied …

We provide data and code that successfully reproduces nearly all crosssectional stock return
predictors. Our 319 characteristics draw from previous meta-studies, but we differ by …

We use deep neural networks to estimate an asset pricing model for individual stock returns
that takes advantage of the vast amount of conditioning information, keeps a fully flexible …

Long short-term memory (LSTM) networks are a state-of-the-art technique for sequence
learning. They are less commonly applied to financial time series predictions, yet inherently …

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 …

Most anomalies fail to hold up to currently acceptable standards for empirical finance. With
microcaps mitigated via NYSE breakpoints and value-weighted returns, 65% of the 452 …