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Does cash flow predict returns?

Author

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  • Narayan, Paresh Kumar
  • Westerlund, Joakim

Abstract

In this paper, we propose the hypothesis that cash flow and cash flow volatility predict returns. We categorize firms listed on the New York Stock Exchange into sectors, and apply tests for both in-sample and out-of-sample predictability. While we find strong evidence that cash flow volatility predicts returns for all sectors, the evidence obtained when using cash flow as a predictor is relatively weak. Estimated profits and utility gains also suggest that it is cash flow volatility that is more relevant as a source of information than cash flow.
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Suggested Citation

  • Narayan, Paresh Kumar & Westerlund, Joakim, 2015. "Does cash flow predict returns?," Working Papers fe_2015_03, Deakin University, Department of Economics.
    • Handle: RePEc:dkn:ecomet:fe_2015_03
    DOI: 10.1016/j.irfa.2014.10.001
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    Cited by:

    1. is not listed on IDEAS
    2. Kumar, Dilip, 2015. "Sudden changes in extreme value volatility estimator: Modeling and forecasting with economic significance analysis," Economic Modelling, Elsevier, vol. 49(C), pages 354-371.
    3. Wang, Chih-Wei & Lee, Chien-Chiang & Wu, Lin-Tan, 2023. "The relationship between cash flow uncertainty and extreme risk: International evidence," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).
    4. Xin-Lan Fu & Xing-Lu Gao & Zheng Shan & Yin-Jie Ma & Zhi-Qiang Jiang & Wei-Xing Zhou, 2025. "Multifractal characteristics and return predictability in the Chinese stock markets," Annals of Operations Research, Springer, vol. 352(3), pages 415-440, September.
    5. repec:ehu:cuader:55444 is not listed on IDEAS

    More about this item

    Keywords

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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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