Forecasting Market Volatility: The Role of Earnings Announcements Journal Article uri icon

Overview

abstract

  • ABSTRACT; This study examines whether information revealed by firms’ earnings announcements (EAs) forecasts short-run market-wide volatility in equity index prices. Using an exponential generalized autoregressive conditional heteroskedasticity model that includes controls for the information in an array of macroeconomic announcements, we find that EA information aggregated across firms forecasts market volatility at daily and weekly intervals. EA information’s forecasting power is greatest when more firms announce earnings on a given day, when EAs convey negative news, and for EA information about core earnings. Out-of-sample tests confirm that forecasts incorporating EA information better predict short-run market volatility than forecasts omitting EA information. We conclude that firm-level EAs are a significant source of systematic, market-wide information relevant for predicting near-term market volatility.; Data Availability: All data are publicly available from sources cited in the text.; JEL Classifications: E44; G12; M41.

publication date

  • July 1, 2024

has restriction

  • bronze

Date in CU Experts

  • December 12, 2023 9:19 AM

Full Author List

  • Kim J; Schonberger B; Wasley C; Yang Y

author count

  • 4

Other Profiles

International Standard Serial Number (ISSN)

  • 0001-4826

Electronic International Standard Serial Number (EISSN)

  • 1558-7967

Additional Document Info

start page

  • 251

end page

  • 279

volume

  • 99

issue

  • 4