Author
Listed:
- Stephen Foerster
- John Tsagarelis
- Grant Wang
Abstract
Although various income statement–based measures predict the cross section of stock returns, direct method cash flow measures have even stronger predictive power. We transform indirect method cash flow statements into disaggregated and more direct estimates of cash flows from operations and other sources and form portfolios on the basis of these measures. Stocks in the highest-cash-flow decile outperform those in the lowest by over 10% annually (risk adjusted). Our results are robust to investment horizons and across risk factors and sector controls. We also show that, in addition to operating cash flow information, cash taxes and capital expenditures provide incremental predictive power. Disclosures:John Tsagarelis and Grant Wang are employed by Highstreet Asset Management, an investment management firm that uses empirically based research and the combination of quantitative and fundamental analysis to capture alpha drivers—growth, value, and quality. Proprietary models are based on numerous factors, only a small portion of which are related to the cash flow measure variables and findings in this article.Editor’s note:This article was externally reviewed using our double-blind peer-review process. When the article was accepted for publication, the authors thanked the reviewers in their acknowledgments. Andrew L. Berkin and Heiko Jacobs were the reviewers for this article.Submitted 2 October 2015Accepted 31 May 2016 by Stephen J. Brown
Suggested Citation
Stephen Foerster & John Tsagarelis & Grant Wang, 2017.
"Are Cash Flows Better Stock Return Predictors Than Profits?,"
Financial Analysts Journal, Taylor & Francis Journals, vol. 73(1), pages 73-99, January.
Handle:
RePEc:taf:ufajxx:v:73:y:2017:i:1:p:73-99
DOI: 10.2469/faj.v73.n1.2
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