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 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 …

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 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 …

Accruals are the non-cash component of earnings. They represent adjustments made to
cash flows to generate a profit measure largely unaffected by the timing of receipts and …

Behavioral finance tries to make sense of financial data using models that are based on
psychologically accurate assumptions about people's beliefs, preferences, and cognitive …

Do accruals-based earnings provide better information about future operating cash flows
than do operating cash flows themselves, as predicted by the Financial Accounting …

We propose a theory of the “profitability” anomaly. In our model, investors forecast future
profits using a signal and sticky belief dynamics. In this model, past profits forecast future …

The cash conversion cycle (CCC) refers to the time span between the outlay of cash for
purchases to the receipt of cash from sales. It is a widely used metric to gauge the …

This paper compares various machine learning models to predict the cross-section of
emerging market stock returns. We document that allowing for non-linearities and …