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Dividend Momentum and Stock Return Predictability: A Bayesian Approach

Author

Listed:
  • Juan Antolin-Diaz
  • Ivan Petrella
  • Juan F. Rubio-Ramirez

Abstract

A long tradition in macro finance studies the joint dynamics of aggregate stock returns and dividends using vector autoregressions (VARs), imposing the cross-equation restrictions implied by the Campbell-Shiller (CS) identity to sharpen inference. We take a Bayesian perspective and develop methods to draw from any posterior distribution of a VAR that encodes a priori skepticism about large amounts of return predictability while imposing the CS restrictions. In doing so, we show how a common empirical practice of omitting dividend growth from the system amounts to imposing the extra restriction that dividend growth is not persistent. We highlight that persistence in dividend growth induces a previously overlooked channel for return predictability, which we label "dividend momentum." Compared to estimation based on ordinary least squares, our restricted informative prior leads to a much more moderate, but still significant, degree of return predictability, with forecasts that are helpful out of sample and realistic asset allocation prescriptions with Sharpe ratios that outperform common benchmarks.

Suggested Citation

  • Juan Antolin-Diaz & Ivan Petrella & Juan F. Rubio-Ramirez, 2021. "Dividend Momentum and Stock Return Predictability: A Bayesian Approach," FRB Atlanta Working Paper 2021-25, Federal Reserve Bank of Atlanta.
  • Handle: RePEc:fip:fedawp:93480
    DOI: 10.29338/wp2021-25
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    as
    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. Gary M. Koop, 2013. "Forecasting with Medium and Large Bayesian VARS," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(2), pages 177-203, March.
    3. Campbell, John Y & Ammer, John, 1993. "What Moves the Stock and Bond Markets? A Variance Decomposition for Long-Term Asset Returns," Journal of Finance, American Finance Association, vol. 48(1), pages 3-37, March.
    4. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
    5. Bekaert, Geert & Hodrick, Robert J. & Marshall, David A., 1997. "On biases in tests of the expectations hypothesis of the term structure of interest rates," Journal of Financial Economics, Elsevier, vol. 44(3), pages 309-348, June.
    6. John Y. Campbell & Yeung Lewis Chanb & M. Viceira, 2013. "A multivariate model of strategic asset allocation," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part II, chapter 39, pages 809-848, World Scientific Publishing Co. Pte. Ltd..
    7. Leamer, Edward E, 1973. "Multicollinearity: A Bayesian Interpretation," The Review of Economics and Statistics, MIT Press, vol. 55(3), pages 371-380, August.
    8. Doron Avramov & Scott Cederburg & Katarína Lučivjanská, 2018. "Are Stocks Riskier over the Long Run? Taking Cues from Economic Theory," The Review of Financial Studies, Society for Financial Studies, vol. 31(2), pages 556-594.
    9. Campbell, John Y, 1991. "A Variance Decomposition for Stock Returns," Economic Journal, Royal Economic Society, vol. 101(405), pages 157-179, March.
    10. John Y. Campbell & John Cochrane, 1999. "Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior," Journal of Political Economy, University of Chicago Press, vol. 107(2), pages 205-251, April.
    11. Sims, Christopher A & Uhlig, Harald, 1991. "Understanding Unit Rooters: A Helicopter Tour," Econometrica, Econometric Society, vol. 59(6), pages 1591-1599, November.
    12. John Y. Campbell & N. Gregory Mankiw, 1989. "Consumption, Income, and Interest Rates: Reinterpreting the Time Series Evidence," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 185-246, National Bureau of Economic Research, Inc.
    13. JULES H. Van BINSBERGEN & RALPH S. J. KOIJEN, 2010. "Predictive Regressions: A Present‐Value Approach," Journal of Finance, American Finance Association, vol. 65(4), pages 1439-1471, August.
    14. Martin Lettau & Sydney Ludvigson, 2001. "Consumption, Aggregate Wealth, and Expected Stock Returns," Journal of Finance, American Finance Association, vol. 56(3), pages 815-849, June.
    15. Christopher A. Sims, 1993. "A Nine-Variable Probabilistic Macroeconomic Forecasting Model," NBER Chapters, in: Business Cycles, Indicators, and Forecasting, pages 179-212, National Bureau of Economic Research, Inc.
    16. Ľuboš Pástor & Robert F. Stambaugh, 2009. "Predictive Systems: Living with Imperfect Predictors," Journal of Finance, American Finance Association, vol. 64(4), pages 1583-1628, August.
    17. Carriero, Andrea & Kapetanios, George & Marcellino, Massimiliano, 2012. "Forecasting government bond yields with large Bayesian vector autoregressions," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2026-2047.
    18. John Y. Campbell & João Cocco & Francisco Gomes & Pascal J. Maenhout & Luis M. Viceira, 2001. "Stock Market Mean Reversion and the Optimal Equity Allocation of a Long-Lived Investor," Review of Finance, European Finance Association, vol. 5(3), pages 269-292.
    19. repec:fth:harver:1435 is not listed on IDEAS
    20. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2015. "Prior Selection for Vector Autoregressions," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 436-451, May.
    21. John H. Cochrane, 2008. "The Dog That Did Not Bark: A Defense of Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1533-1575, July.
    22. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October.
    23. Marco Del Negro & Frank Schorfheide, 2004. "Priors from General Equilibrium Models for VARS," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(2), pages 643-673, May.
    24. Larrain, Borja & Yogo, Motohiro, 2008. "Does firm value move too much to be justified by subsequent changes in cash flow," Journal of Financial Economics, Elsevier, vol. 87(1), pages 200-226, January.
    25. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
    26. Sims, Christopher A & Zha, Tao, 1998. "Bayesian Methods for Dynamic Multivariate Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-968, November.
    27. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2019. "Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors," Journal of Econometrics, Elsevier, vol. 212(1), pages 137-154.
    28. Wachter, Jessica A. & Warusawitharana, Missaka, 2009. "Predictable returns and asset allocation: Should a skeptical investor time the market?," Journal of Econometrics, Elsevier, vol. 148(2), pages 162-178, February.
    29. John Y. Campbell & Luis M. Viceira, 1999. "Consumption and Portfolio Decisions when Expected Returns are Time Varying," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(2), pages 433-495.
    30. Nicholas Barberis & Ming Huang & Tano Santos, "undated". "Prospect Theory and Asset Prices," CRSP working papers 494, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
    31. Bryan Kelly & Seth Pruitt, 2013. "Market Expectations in the Cross-Section of Present Values," Journal of Finance, American Finance Association, vol. 68(5), pages 1721-1756, October.
    32. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    33. Charles Engel, 2016. "Exchange Rates, Interest Rates, and the Risk Premium," American Economic Review, American Economic Association, vol. 106(2), pages 436-474, February.
    34. repec:bla:jfinan:v:59:y:2004:i:4:p:1481-1509 is not listed on IDEAS
    35. Jonathan A. Parker & Antoinette Schoar & Yang Sun, 2020. "Retail Financial Innovation and Stock Market Dynamics: The Case of Target Date Funds," NBER Working Papers 28028, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    CS restrictions; Bayesian VARs; optimal allocation;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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