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Aggregate Earnings, Firm-Level Earnings, and Expected Stock Returns

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  • Bali, Turan G.
  • Demirtas, K. Ozgur
  • Tehranian, Hassan

Abstract

This paper provides an analysis of the predictability of stock returns using market-, industry-, and firm-level earnings. Contrary to Lamont (1998), we find that neither dividend payout ratio nor the level of aggregate earnings can forecast the excess market return. We show that these variables do not have robust predictive power across different stock portfolios and sample periods. In contrast to the aggregate-level findings, earnings yield has significant explanatory power for the time-series and cross-sectional variation in firmlevel stock returns and the 48 industry portfolio returns. The mean reversion of stock prices as well as the earnings' correlation with expected stock returns are responsible for the forecasting power of earnings yield. These results are robust after controlling for bookto-market, size, price momentum, and post-earnings announcement drift. At the aggregate level, the information content of firm-level earnings about future cash flows is diversified away and higher aggregate earnings do not forecast higher returns.

Suggested Citation

  • Bali, Turan G. & Demirtas, K. Ozgur & Tehranian, Hassan, 2008. "Aggregate Earnings, Firm-Level Earnings, and Expected Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(3), pages 657-684, September.
  • Handle: RePEc:cup:jfinqa:v:43:y:2008:i:03:p:657-684_00
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    Citations

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    Cited by:

    1. Yunhao Chen & Xiaoquan Jiang & Bong-Soo Lee, 2015. "Long-Term Evidence on the Effect of Aggregate Earnings on Prices," Financial Management, Financial Management Association International, vol. 44(2), pages 323-351, June.
    2. Naresh Bansal & Jack Strauss & Alireza Nasseh, 2015. "Can we consistently forecast a firm’s earnings? Using combination forecast methods to predict the EPS of Dow firms," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 39(1), pages 1-22, January.
    3. Choi, Jung Ho & Kalay, Alon & Sadka, Gil, 2016. "Earnings news, expected earnings, and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 29(C), pages 110-143.
    4. Walkshäusl, Christian, 2014. "The MAX effect: European evidence," Journal of Banking & Finance, Elsevier, vol. 42(C), pages 1-10.
    5. Sanna, Dario, 2020. "A Fast and Parsimonious Way to Estimate the Implied Rate of Return on Equity," MPRA Paper 102072, University Library of Munich, Germany.
    6. SHUBITA, Moade Fawzi & AL-SHARKAS, Adel A., 2010. "A Study Of Size Effect And Macroeconomics Factors In New York Stock Exchange Stock Returns," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 10(2).
    7. Xanthi Gkougkousi, 2014. "Aggregate Earnings and Corporate Bond Markets," Journal of Accounting Research, Wiley Blackwell, vol. 52(1), pages 75-106, March.
    8. Maio, Paulo & Xu, Danielle, 2020. "Cash-flow or return predictability at long horizons? The case of earnings yield," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 172-192.
    9. Christian Walkshäusl, 2013. "The high returns to low volatility stocks are actually a premium on high quality firms," Review of Financial Economics, John Wiley & Sons, vol. 22(4), pages 180-186, November.
    10. Walkshäusl, Christian, 2013. "The high returns to low volatility stocks are actually a premium on high quality firms," Review of Financial Economics, Elsevier, vol. 22(4), pages 180-186.
    11. Gunduz Caginalp & Mark DeSantis, 2019. "Nonlinear price dynamics of S&P 100 stocks," Papers 1907.04422, arXiv.org.
    12. Bali, Turan G. & Cakici, Nusret, 2010. "World market risk, country-specific risk and expected returns in international stock markets," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1152-1165, June.
    13. Yuto Yoshinaga, 2016. "Market-Wide Cost of Capital Impacts on the Aggregate Earnings-Returns Relation: Evidence from Japan," The Japanese Accounting Review, Research Institute for Economics & Business Administration, Kobe University, vol. 6, pages 95-122, December.
    14. Erkan, Asligul & Fainshmidt, Stav & Judge, William Q., 2016. "Variance decomposition of the country, industry, firm, and firm-year effects on dividend policy," International Business Review, Elsevier, vol. 25(6), pages 1309-1320.
    15. David R Gallagher & Peter A Gardner & Camille H Schmidt, 2015. "Style factor timing: An application to the portfolio holdings of US fund managers," Australian Journal of Management, Australian School of Business, vol. 40(2), pages 318-350, May.
    16. Caginalp, Gunduz & DeSantis, Mark, 2020. "Nonlinear price dynamics of S&P 100 stocks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).

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