The Use of Financial Ratio Models to Help Investors Predict and Interpret Significant Corporate Events

75 Pages Posted: 4 Oct 2013

See all articles by B. Korcan Ak

B. Korcan Ak

University of California, Berkeley - Haas School of Business

Patricia Dechow

USC Marshall School of Business

Estelle Sun

Boston University - Questrom School of Business

Annika Yu Wang

University of Houston - Bauer College of Business

Multiple version iconThere are 2 versions of this paper

Date Written: October 2, 2013

Abstract

A firm in steady state generates predictable income and investors can generally agree on valuation. However, when a significant corporate event occurs this creates greater uncertainty and disagreement about firm valuation and investors could prefer to avoid holding such a stock. We examine research that has developed financial ratio models to (i) predict significant corporate events; and (ii) predict future performance after significant corporate events. The events we analyze include financial distress and bankruptcy, downsizing, raising equity capital, and material earnings misstatements. We find that financial ratio models generally help investors avoid stocks that are likely to have significant corporate events. We also find that conditional on a significant event occurring, financial ratio models help investors distinguish good firms from bad. However, we find that research design choices often make it difficult to determine model predictive accuracy. We discuss the role of accounting rule changes and their impact overtime on the predictive power of models and provide suggestions for improving models based on our cross-event analysis.

Suggested Citation

Ak, B. Korcan and Dechow, Patricia and Sun, Estelle Yuan and Wang, Annika Yu, The Use of Financial Ratio Models to Help Investors Predict and Interpret Significant Corporate Events (October 2, 2013). Available at SSRN: https://ssrn.com/abstract=2335185 or http://dx.doi.org/10.2139/ssrn.2335185

B. Korcan Ak

University of California, Berkeley - Haas School of Business ( email )

545 Student Services Building, #1900
2220 Piedmont Avenue
Berkeley, CA 94720
United States

Patricia Dechow (Contact Author)

USC Marshall School of Business ( email )

Los Angeles, CA 90089-0441
United States

Estelle Yuan Sun

Boston University - Questrom School of Business ( email )

595 Commonwealth Avenue
Boston, MA MA 02215
United States
1-617-353-2353 (Phone)

Annika Yu Wang

University of Houston - Bauer College of Business

Bauer College of Business
4250 Martin Luther King Blvd
Houston, TX 77204
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
860
Abstract Views
4,410
Rank
51,865
PlumX Metrics