题名

The Out-Of-Sample Prediction of Annual Operating Cash Flow: a Comparison of Regression and Naïve Forecast Models

DOI

10.6292/AFPF.2015.06.03

作者

Rick N. Francis;Lori M. Olsen

关键词

Forecast ; Operating Cash Flow ; Naïve ; Out-of-Sample

期刊名称

Advances in Financial Planning and Forecasting

卷期/出版年月

6期(2015 / 02 / 01)

页次

65 - 93

内容语文

英文

英文摘要

This study proposes that a no-change naive forecast of (operating) cash flow is as accurate as time-series (firm-specific) 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 as time-series regression forecasts. Next the study confirms the expectation that a naive forecast is as accurate as the regression model forecasts. Finally, the study identifies apparent misapplications of Theil's U-statistic, which overstate the ability of regression forecast models to outperform a naive forecast model.

主题分类 社會科學 > 經濟學
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