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Equity premium predictions with many predictors: A risk-based explanation of the size and value factors

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  • Stivers, Adam

Abstract

This paper investigates whether a direct mechanism can be found that demonstrates that the size and value factors of Fama and French (1993) are indeed ICAPM factors, as some have suggested. The results endorse this hypothesis: small size and value portfolios reflect changes in future investment opportunities. To test the hypothesis, the paper forecasts the equity premium using disaggregated portfolio returns with a partial least squares (PLS) regression approach. PLS is chosen as it is particularly suited to condense a large set of portfolios into a single index. The “index” portfolio obtained from the forecast performs well out of sample and hedges against future market risk, in addition to explaining future market returns in sample. Thus, the index portfolio may be viewed as an additional risk factor in the form of a Merton (1973) state variable. The index places larger weights on small size and value portfolios. This also provides a possible explanation for why equal-weighted portfolios typically perform better out of sample compared to factors implied by traditional mean-variance approaches and asset pricing models.

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  • Stivers, Adam, 2018. "Equity premium predictions with many predictors: A risk-based explanation of the size and value factors," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 126-140.
    • Handle: RePEc:eee:empfin:v:45:y:2018:i:c:p:126-140
    DOI: 10.1016/j.jempfin.2017.10.004
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    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. Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1683, August.
    3. Hui Guo, 2006. "On the Out-of-Sample Predictability of Stock Market Returns," The Journal of Business, University of Chicago Press, vol. 79(2), pages 645-670, March.
    4. Polk, Christopher & Thompson, Samuel & Vuolteenaho, Tuomo, 2006. "Cross-sectional forecasts of the equity premium," Journal of Financial Economics, Elsevier, vol. 81(1), pages 101-141, July.
    5. 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.
    6. Israel, Ronen & Moskowitz, Tobias J., 2013. "The role of shorting, firm size, and time on market anomalies," Journal of Financial Economics, Elsevier, vol. 108(2), pages 275-301.
    7. Ferreira, Miguel A. & Santa-Clara, Pedro, 2011. "Forecasting stock market returns: The sum of the parts is more than the whole," Journal of Financial Economics, Elsevier, vol. 100(3), pages 514-537, June.
    8. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    9. Amit Goyal & Ivo Welch, 2003. "Predicting the Equity Premium with Dividend Ratios," Management Science, INFORMS, vol. 49(5), pages 639-654, May.
    10. Novy-Marx, Robert, 2014. "Predicting anomaly performance with politics, the weather, global warming, sunspots, and the stars," Journal of Financial Economics, Elsevier, vol. 112(2), pages 137-146.
    11. 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.
    12. Pettenuzzo, Davide & Timmermann, Allan & Valkanov, Rossen, 2014. "Forecasting stock returns under economic constraints," Journal of Financial Economics, Elsevier, vol. 114(3), pages 517-553.
    13. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    14. Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1684, August.
    15. Tu, Jun & Zhou, Guofu, 2011. "Markowitz meets Talmud: A combination of sophisticated and naive diversification strategies," Journal of Financial Economics, Elsevier, vol. 99(1), pages 204-215, January.
    16. Campbell, John Y, 1996. "Understanding Risk and Return," Journal of Political Economy, University of Chicago Press, vol. 104(2), pages 298-345, April.
    17. Li, Yan & Ng, David T. & Swaminathan, Bhaskaran, 2013. "Predicting market returns using aggregate implied cost of capital," Journal of Financial Economics, Elsevier, vol. 110(2), pages 419-436.
    18. 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.
    19. Bossaerts, Peter & Hillion, Pierre, 1999. "Implementing Statistical Criteria to Select Return Forecasting Models: What Do We Learn?," The Review of Financial Studies, Society for Financial Studies, vol. 12(2), pages 405-428.
    20. Maio, Paulo & Santa-Clara, Pedro, 2015. "Dividend Yields, Dividend Growth, and Return Predictability in the Cross Section of Stocks," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 50(1-2), pages 33-60, April.
    21. Eugene F. Fama & Kenneth R. French, 2006. "The Value Premium and the CAPM," Journal of Finance, American Finance Association, vol. 61(5), pages 2163-2185, October.
    22. Kelly, Bryan & Pruitt, Seth, 2015. "The three-pass regression filter: A new approach to forecasting using many predictors," Journal of Econometrics, Elsevier, vol. 186(2), pages 294-316.
    23. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    24. Lu Zhang, 2005. "The Value Premium," Journal of Finance, American Finance Association, vol. 60(1), pages 67-103, February.
    25. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    26. Petkova, Ralitsa & Zhang, Lu, 2005. "Is value riskier than growth?," Journal of Financial Economics, Elsevier, vol. 78(1), pages 187-202, October.
    27. Matthew Spiegel, 2008. "Forecasting the Equity Premium: Where We Stand Today," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1453-1454, July.
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    10. Zhang, Yaojie & He, Mengxi & Wang, Yudong & Liang, Chao, 2023. "Global economic policy uncertainty aligned: An informative predictor for crude oil market volatility," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1318-1332.
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    More about this item

    Keywords

    Asset pricing; Factor models; Equity premium; Forecasting; Risk hedging;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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