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Does the bond-stock earning yield differential model predict equity market corrections better than high P/E models?

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  • Lleo, Sebastien
  • Ziemba, William T.

Abstract

In this paper, we extend the literature on crash prediction models in three main respects. First, we relate explicitly crash prediction measures and asset pricing models. Second, we present a simple, effective statistical significance test for crash prediction models. Finally, we propose a definition and a measure of robustness for crash prediction models. We apply the statistical test and measure the robustness of selected model specifications of the Price-Earnings (P/E) ratio and Bond Stock Earning Yield Differential (BSEYD) measures. This analysis suggests that the BSEYD, the logarithmic BSEYD model, and to a lesser extent the P/E ratio, are statistically significant robust predictors of equity market crashes.

Suggested Citation

  • Lleo, Sebastien & Ziemba, William T., 2014. "Does the bond-stock earning yield differential model predict equity market corrections better than high P/E models?," LSE Research Online Documents on Economics 59290, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:59290
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    References listed on IDEAS

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    1. Andrew Ang & Geert Bekaert, 2002. "International Asset Allocation With Regime Shifts," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1137-1187.
    2. Fama, Eugene F & French, Kenneth R, 1988. "Permanent and Temporary Components of Stock Prices," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 246-273, April.
    3. John Y. Campbell & Tuomo Vuolteenaho, 2004. "Inflation Illusion and Stock Prices," American Economic Review, American Economic Association, vol. 94(2), pages 19-23, May.
    4. Thaler, Richard H, 1997. "Irving Fisher: Modern Behavioral Economist," American Economic Review, American Economic Association, vol. 87(2), pages 439-441, May.
    5. 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.
    6. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    7. Koivu, Matti & Pennanen, Teemu & Ziemba, William T., 2005. "Cointegration analysis of the Fed model," Finance Research Letters, Elsevier, vol. 2(4), pages 248-259, December.
    8. McGuckin, Robert H. & Ozyildirim, Ataman & Zarnowitz, Victor, 2007. "A More Timely and Useful Index of Leading Indicators," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 110-120, January.
    9. Estrada, Javier, 2006. "The Fed model: A note," Finance Research Letters, Elsevier, vol. 3(1), pages 14-22, March.
    10. Keim,Donald B. & Ziemba,William T. (ed.), 2000. "Security Market Imperfections in Worldwide Equity Markets," Cambridge Books, Cambridge University Press, number 9780521571388, November.
    11. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    12. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    13. Paulo Maio, 2013. "The "Fed Model" and the Predictability of Stock Returns," Review of Finance, European Finance Association, vol. 17(4), pages 1489-1533.
    14. Lleo, Sébastien & Ziemba, William T., 2015. "Some historical perspectives on the Bond-Stock Earnings Yield Model for crash prediction around the world," International Journal of Forecasting, Elsevier, vol. 31(2), pages 399-425.
    15. Robert Jarrow & Younes Kchia & Philip Protter, 2011. "Is there a bubble in LinkedIn's stock price?," Papers 1105.5717, arXiv.org.
    16. Campbell, John Y. & Shiller, Robert J., 1989. "The dividend ratio model and small sample bias : A Monte Carlo study," Economics Letters, Elsevier, vol. 29(4), pages 325-331.
    17. Ronald Balvers & Yangru Wu & Erik Gilliland, 2000. "Mean Reversion across National Stock Markets and Parametric Contrarian Investment Strategies," Journal of Finance, American Finance Association, vol. 55(2), pages 745-772, April.
    18. Philip A. Klein & Geoffrey H. Moore, 1982. "The Leading Indicator Approach to Economic Forecasting--Retrospect and Prospect," NBER Working Papers 0941, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Sanna, Dario, 2020. "A Fast and Parsimonious Way to Estimate the Implied Rate of Return of Equity," MPRA Paper 102003, University Library of Munich, Germany.
    2. Lleo, Sebastien & Ziemba, William, 2017. "A tale of two indexes: predicting equity market downturns in China," LSE Research Online Documents on Economics 85131, London School of Economics and Political Science, LSE Library.
    3. Nebojsa Dimic & Vitaly Orlov & Janne Äijö, 2019. "Bond–Equity Yield Ratio Market Timing in Emerging Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(1), pages 52-79, April.
    4. Lleo, Sébastien & Ziemba, William T., 2015. "Some historical perspectives on the Bond-Stock Earnings Yield Model for crash prediction around the world," International Journal of Forecasting, Elsevier, vol. 31(2), pages 399-425.
    5. Shiryaev, Albert N. & Zhitlukhin, Mikhail N. & Ziemba, William T., 2014. "Land and stock bubbles, crashes and exit strategies in Japan circa 1990 and in 2013," LSE Research Online Documents on Economics 59288, London School of Economics and Political Science, LSE Library.

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    More about this item

    Keywords

    stock market crashes; bond-stock earnings yield mode; Fed model; price-earnings-ratio;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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