Macroeconomic Uncertainty and Quantitative versus Qualitative Inputs to Analyst Risk Forecasts

Autor: Khrystyna Bochkay, Peter R. Joos
Rok vydání: 2020
Předmět:
Zdroj: The Accounting Review. 96:59-90
ISSN: 1558-7967
0001-4826
DOI: 10.2308/tar-2017-0490
Popis: Risk forecasting is crucial for informed investment decision-making. Moreover, the salience of investment risk increases during economically uncertain times. In this paper, we study how sell-side analysts form expectations of firm risk, under different macroeconomic conditions (low versus high uncertainty) and by distinguishing between quantitative and qualitative information inputs. We find that analysts jointly consider quantitative and qualitative information, but that their reliance on qualitative information—in particular, disclosure tone—increases when macroeconomic uncertainty is high. We also find that analysts mostly rely on disclosure tone when it contradicts quantitative information. These findings highlight how narrative disclosures can provide context for quantitative information. Finally, we find that analysts' specific use of quantitative/qualitative information improves their forecasts as predictors of firm risk. Together, our results illuminate analysts' risk forecasting process—what information they use and how. JEL Classifications: G01; G11; G20; G24.
Databáze: OpenAIRE