Title
The Out-of-Sample Prediction of Annual Operating Cash Flow: A Comparison of Regression and Naïve Forecast Models
Publication Date
12-16-2011
Document Type
Article
Abstract
This study proposes that a no-change naïve forecast of (operating) cash flow is as accurate as time-series and cross-sectional regression forecasts of cash flow. The study first demonstrates that cross-sectional regression forecasts of cash flow with firm-size controls are as accurate time-series (firm-specific) regression forecasts. Next the study confirms the expectation that a naïve forecast is as accurate as the regression model forecasts. Finally, the study confirms that some studies in the literature misapply Theil’s U-statistic, and overstate the ability of regression forecast models to outperform a naïve forecast model. (RQFA review process requires 3-6 mos per Cabells).
Comments
Francis, Rick N. and Olsen, Lori, The Out-of-Sample Prediction of Annual Operating Cash Flow: A Comparison of Regression and Naïve Forecast Models (December 16, 2011). Available at SSRN: https://ssrn.com/abstract=2025224 or http://dx.doi.org/10.2139/ssrn.2025224