We estimate the impact of the COVID-19 pandemic on credit risk changes on a large sample of Polish SME firms. The Altman Z"-Score model, which has proven to be a powerful and robust bankruptcy prediction model across many industries and countries, is used to assess over 1,000 SMEs from seven...

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...

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...

Identifying firms linked economically through the comovement of the credit rating of their corporate bonds, we find that a long-short strategy for stocks based on the link generates a risk-adjusted alpha of 0.62 percent per month, which cannot be explained by industry, customer-supplier, single-...

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...