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...

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...

What predicts returns on assets with "hard-to-value" fundamentals, such as Bitcoin and stocks in new industries? We propose an equilibrium model that shows how rational learning enables return predictability through technical analysis. We document that ratios of prices to their moving averages...

This study presents direct evidence on the question whether investors recognize the widely documented biases in securities analysts' earnings forecasts. The internal rate of return implied by current stock price and consensus earnings forecasts is found to be correlated with indicators of bias...

The efficient market hypothesis describes an efficient market as one in which investors cannot consistently predict stock returns because prices instantly reflect all the information flowing into the market. However, return predictability has been documented in many markets. This study tests the...

Using 719,830 analyst recommendations from 1994 to 2017, we construct various portfolios based on levels and changes in analyst recommendations and examine how the value of those recommendations in predicting the abnormal stock returns has changed over time. We find that the predictive value of...

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 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...