Regulators are not always able to anticipate how mandates will translate to financial reporting practice, particularly when managers are able to exercise reporting discretion. When XBRL, the eXtensible Business Reporting Language, was mandated by the SEC, financial analysts were among the...

We introduce a new measure of stock misevaluation, 𝑄, which is consistent with the Gordon growth model for firm valuation. In our empirical application, we use 𝑄 to relate analyst forecasts to stock returns and measure the profitability of investment strategies that rely on information in...

In this paper, we forecast industry returns out-of-sample using the cross-section of book-to-market ratios and investigate whether investors can exploit this predictability in portfolio allocation. Cash-flow and return forecasting regressions show that cross-industry book-to-market ratios...

This paper reviews research that uses big data and/or machine learning methods to provide insight relevant for equity valuation. Given the huge volume of research in this area, the review focuses on studies that either use or inform on accounting variables. The article concludes by providing...

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 promising directions for future research. This survey is designed for both financial economists interested in grasping...

While economic variables have been used extensively to forecast bond risk premia, little attention has been paid to technical indicators which are widely used by practitioners. In this paper, we study the predictive ability of a variety of technical indicators vis-a-vis the economic variables....

Purpose: In this paper we try to explain US stock market variations and cash flow fundamentals by employing three different book-valued based ratios, First, we explore the explanatory capacity of the simple book-market ratio on time-varying expected returns, and procced on altering its...

This article shows that aggregate analyst recommendations predict future aggregate excess returns at MSA and state level (i.e. local level). The results hold even after controlling for macroeconomic variables, industry and market returns, as well as investor sentiment. We also show that the...

We constructed forecasts of earnings forecasts using data on 406 firms and forecasts made by 5419 individuals with on average 25 forecasts per individual. We verified previously found predictors, which are the average of the most recent available forecast for each forecaster and the difference...

An analysis of about 300000 earnings forecasts, created by 18000 individual forecasters for earnings of over 300 S&P listed firms, shows that these forecasts are predictable to a large extent using a statistical model that includes publicly available information. When we focus on the...