As supply chain channels physical, financial, and information flows as well as associated risks, a firm’s supply chain information should be helpful in understanding and predicting its credit risks. Credit ratings as an approximate but important measure of corporate credit risks have been...

We use machine learning techniques to conduct out-of-sample predictions of the underpricing of U.S. initial public offerings (IPOs) from 1990 to 2019. Using predicted underpricing based on ex ante information to sort the IPOs into 10 groups, we find that the underpricing averages for the top and...

Sell-side fundamental analyst reports are highly valued in the financial industry and include three main quantitative components: earnings forecasts, target prices, and buy/sell recommendations. An important question for investment managers is then, how accurate are the forecasts of fundamental...

Over the past 12 years, financial analysts across the world have been optimistically wrong with their 12-month earnings forecasts by 25.3%. This study may be the first of its kind to assess analyst earnings forecast accuracy at all listed companies across the globe, covering 70 countries. A...

This study presents evidence suggesting that investors do not fully unravel predictable pessimism in sell-side analysts' earnings forecasts. We show that measures of prior consensus and individual analyst forecast pessimism are predictive of both the sign of firms' earnings surprises and the...

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...

This study focuses on the impact of model estimation methods on earnings forecast accuracy. Compared with an ordinary least squares (OLS) regression combined with winsorization, robust regression MM-estimation improves the earnings forecast accuracy of all the models examined, especially for...

Final working paper version. "" Published version: The Review of Financial Studies, Volume 31, Issue 7, July 2018, pp. 2499–2552. Past fund performance does a poor job of predicting future outcomes. The reason is noise. Using a random effects framework, we reduce the noise by pooling...

Using detailed information on establishments owned by U.S. public firms, we construct a novel measure of geographic linkage between firms. We show that the returns of geography-linked firms have strong predictive power for focal firm returns and fundamentals. A long-short strategy based on this...

I hypothesize that the stock market overreacts to management earnings forecasts because of the uncertainty surrounding them. I find that negative management forecast surprises lead to a –5.9% abnormal return around the forecast and a 1.9% correction in the 2-month period after earnings are...