Ensuring that a firm has sufficient liquidity to finance valuable projects that occur in the future
is at the heart of the practice of financial management. However, although discussion of …

Market reactions to the 2019 novel coronavirus disease (COVID-19) provide new insights
into how real shocks and financial policies drive firm value. Initially, internationally oriented …

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 …

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

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 …

We propose a model selection method to systematically evaluate the contribution to asset
pricing of any new factor, above and beyond what a high‐dimensional set of existing factors …

We propose a nonparametric method to study which characteristics provide incremental
information for the cross-section of expected returns. We use the adaptive group LASSO to …

Despite the growing interest in exploring the cash holding aspects among scholars,
systematic reviews and comprehensive evaluation in this area has been limited. Also, there …

We document a significant positive relation between drought risk and the cost of equity
capital. Our estimation shows that the cost of equity capital is 92 basis points higher for firms …

Hundreds of papers and factors attempt to explain the cross-section of expected returns.
Given this extensive data mining, it does not make sense to use the usual criteria for …