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Using equity premium survey data to estimate future wealth


  • Mark Freeman


  • Ben Groom



We present the first systematic methods for combining different experts’ responses to equity premium surveys. These techniques are based on the observation that the survey data are approximately gamma distributed. This distribution has convenient analytical properties that enable us to address three important problems that investment managers must face. First, we construct probability density functions for the future values of equity index tracker funds. Second, we calculate unbiased and minimum least square error estimators of the future value of these funds. Third, we derive optimal asset allocation weights between equities and the risk-free asset for risk-averse investors. Our analysis allows for both herding and biasedness in expert responses. We show that, unless investors are highly uncertain about expert biases or forecasts are very highly correlated, many investment decisions can be based solely on the mean of the survey data minus any expected bias. We also make recommendations for the design of future equity premium surveys. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Mark Freeman & Ben Groom, 2015. "Using equity premium survey data to estimate future wealth," Review of Quantitative Finance and Accounting, Springer, vol. 45(4), pages 665-693, November.
  • Handle: RePEc:kap:rqfnac:v:45:y:2015:i:4:p:665-693
    DOI: 10.1007/s11156-014-0451-7

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    References listed on IDEAS

    1. Narasimhan Jegadeesh & Woojin Kim, 2010. "Do Analysts Herd? An Analysis of Recommendations and Market Reactions," Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 901-937, February.
    2. Mehra, Rajnish & Prescott, Edward C., 1985. "The equity premium: A puzzle," Journal of Monetary Economics, Elsevier, vol. 15(2), pages 145-161, March.
    3. Ian Cooper, 1996. "Arithmetic versus geometric mean estimators: Setting discount rates for capital budgeting," European Financial Management, European Financial Management Association, vol. 2(2), pages 157-167.
    4. Robert L. Winkler, 1981. "Combining Probability Distributions from Dependent Information Sources," Management Science, INFORMS, vol. 27(4), pages 479-488, April.
    5. Eric Jacquier & Alex Kane & Alan J. Marcus, 2005. "Optimal Estimation of the Risk Premium for the Long Run and Asset Allocation: A Case of Compounded Estimation Risk," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 3(1), pages 37-55.
    6. Eugene F. Fama & Kenneth R. French, 2002. "The Equity Premium," Journal of Finance, American Finance Association, vol. 57(2), pages 637-659, April.
    7. Martin L. Weitzman, 2001. "Gamma Discounting," American Economic Review, American Economic Association, vol. 91(1), pages 260-271, March.
    8. Ferstl, Robert & Weissensteiner, Alex, 2011. "Asset-liability management under time-varying investment opportunities," Journal of Banking & Finance, Elsevier, vol. 35(1), pages 182-192, January.
    9. Weitzman, Martin L., 2010. "Risk-adjusted gamma discounting," Journal of Environmental Economics and Management, Elsevier, vol. 60(1), pages 1-13, July.
    10. Merton, Robert C, 1969. "Lifetime Portfolio Selection under Uncertainty: The Continuous-Time Case," The Review of Economics and Statistics, MIT Press, vol. 51(3), pages 247-257, August.
    11. Welch, Ivo, 2000. "Views of Financial Economists on the Equity Premium and on Professional Controversies," The Journal of Business, University of Chicago Press, vol. 73(4), pages 501-537, October.
    12. repec:dau:papers:123456789/2326 is not listed on IDEAS
    13. Jouini, Elyès & Marin, Jean-Michel & Napp, Clotilde, 2010. "Discounting and divergence of opinion," Journal of Economic Theory, Elsevier, vol. 145(2), pages 830-859, March.
    14. Vivek Singh, 2013. "Did institutions herd during the internet bubble?," Review of Quantitative Finance and Accounting, Springer, vol. 41(3), pages 513-534, October.
    15. Gollier, Christian, 2004. "Maximizing the expected net future value as an alternative strategy to gamma discounting," Finance Research Letters, Elsevier, vol. 1(2), pages 85-89, June.
    16. repec:hrv:faseco:33373344 is not listed on IDEAS
    17. Daniel C. Indro & Wayne Y. Lee, 1997. "Biases in Arithmetic and Geometric Averages as Estimates of Long-Run Expected Returns and Risk Premia," Financial Management, Financial Management Association, vol. 26(4), Winter.
    18. Ramnath, Sundaresh & Rock, Steve & Shane, Philip, 2008. "The financial analyst forecasting literature: A taxonomy with suggestions for further research," International Journal of Forecasting, Elsevier, vol. 24(1), pages 34-75.
    19. Nicholas Barberis, 2000. "Investing for the Long Run when Returns Are Predictable," Journal of Finance, American Finance Association, vol. 55(1), pages 225-264, February.
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    More about this item


    Financial surveys; Equity premium; Asset allocation; Gamma distribution; G11; G17;

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions


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