The Use of Financial Ratio Models to Help Investors Predict and Interpret Significant Corporate Events* B. Korcan Ak The Haas School of Business, University of California, Berkeley Berkeley, CA 94705
[email protected], Patricia M. Dechow The Haas School of Business, University of California, Berkeley Berkeley, CA 94705
[email protected] Yuan Sun Boston University School of Management Boston, MA 02215
[email protected] Annika Yu Wang The Haas School of Business, University of California, Berkeley Berkeley, CA 94705
[email protected] 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. * We are grateful for the comments of Greg Clinch, Neil Fargher, Matt Pinnuck, Richard Sloan, and to participants at the Australian Journal of Management Conference held at University of Melbourne.