Macroeconomic Uncertainty and Quantitative versus Qualitative Inputs to Analyst Risk Forecasts

• 成果类型: Article
• 署名作者: Bochkay, Khrystyna; Joos, Peter R.
• 署名单位: University of Miami; INSEAD Business School
• 刊物名称: ACCOUNTING REVIEW
• ISSN/ISSBN: 0001-4826
• DOI: 10.2308/TAR-2017-0490
• 发表日期: 2021
• 页码: 59-90
• 关键词: information-content; cross-section; empirical-analysis; CONFERENCE CALLS; earnings; management; association; DISCLOSURES; incentives; volatility

摘要

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.