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Beta dispersion and market timing

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  • Kuntz, Laura-Chloé

Abstract

The beta dispersion, which is the spread of betas on a stock market, can be interpreted as a measure of market vulnerability. This study examines the economic idea of the beta dispersion and its application as a market return predictor. Based on the empirical beta dispersion observed in the US equity market, the study develops measures to predict future market returns. These dispersion measures have substantial predictive power for future market movements. Moreover, I show that the informational content of beta dispersion can be successfully exploited by market timing strategies with the help of distributional regressions. This is an innovative application of this novel way of modeling the relationship between multiple variables and appears to be quite useful for timing strategies.

Suggested Citation

  • Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Discussion Papers 46/2020, Deutsche Bundesbank.
  • Handle: RePEc:zbw:bubdps:462020
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    References listed on IDEAS

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    1. Faria, Gonçalo & Verona, Fabio, 2018. "Forecasting stock market returns by summing the frequency-decomposed parts," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 228-242.
    2. Geert Bekaert & Campbell R. Harvey, 2000. "Foreign Speculators and Emerging Equity Markets," Journal of Finance, American Finance Association, vol. 55(2), pages 565-613, April.
    3. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    4. Xiaoquan Jiang, 2010. "Return dispersion and expected returns," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 24(2), pages 107-135, June.
    5. Baetje, Fabian & Menkhoff, Lukas, 2016. "Equity premium prediction: Are economic and technical indicators unstable?," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1193-1207.
    6. Jun Tu, 2010. "Is Regime Switching in Stock Returns Important in Portfolio Decisions?," Management Science, INFORMS, vol. 56(7), pages 1198-1215, July.
    7. Pettenuzzo, Davide & Timmermann, Allan & Valkanov, Rossen, 2014. "Forecasting stock returns under economic constraints," Journal of Financial Economics, Elsevier, vol. 114(3), pages 517-553.
    8. 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.
    9. Pollet, Joshua M. & Wilson, Mungo, 2010. "Average correlation and stock market returns," Journal of Financial Economics, Elsevier, vol. 96(3), pages 364-380, June.
    10. Tim Bollerslev & George Tauchen & Hao Zhou, 2009. "Expected Stock Returns and Variance Risk Premia," Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4463-4492, November.
    11. 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.
    12. Alexandros Kostakis & Nikolaos Panigirtzoglou & George Skiadopoulos, 2011. "Market Timing with Option-Implied Distributions: A Forward-Looking Approach," Management Science, INFORMS, vol. 57(7), pages 1231-1249, July.
    13. Andreas Neuhierl & Bernd Schlusche, 2011. "Data Snooping and Market-Timing Rule Performance," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 9(3), pages 550-587, Summer.
    14. Andrew Ang & Geert Bekaert, 2007. "Stock Return Predictability: Is it There?," Review of Financial Studies, Society for Financial Studies, vol. 20(3), pages 651-707.
    15. Peter Reinhard Hansen & Allan Timmermann, 2012. "Choice of Sample Split in Out-of-Sample Forecast Evaluation," CREATES Research Papers 2012-43, Department of Economics and Business Economics, Aarhus University.
    16. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2014. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Management Science, INFORMS, vol. 60(7), pages 1772-1791, July.
    17. Avramov, Doron & Chordia, Tarun, 2006. "Predicting stock returns," Journal of Financial Economics, Elsevier, vol. 82(2), pages 387-415, November.
    18. Chen, Shiu-Sheng, 2009. "Predicting the bear stock market: Macroeconomic variables as leading indicators," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 211-223, February.
    19. Amit Goyal & Ivo Welch, 2003. "Predicting the Equity Premium with Dividend Ratios," Management Science, INFORMS, vol. 49(5), pages 639-654, May.
    20. Dashan Huang & Fuwei Jiang & Jun Tu & Guofu Zhou, 2015. "Investor Sentiment Aligned: A Powerful Predictor of Stock Returns," Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 791-837.
    21. Bollerslev, Tim & Marrone, James & Xu, Lai & Zhou, Hao, 2014. "Stock Return Predictability and Variance Risk Premia: Statistical Inference and International Evidence," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(3), pages 633-661, June.
    22. Roger G. Ibbotson & Peng Chen, 2003. "Long-Run Stock Returns: Participating in the Real Economy," Yale School of Management Working Papers ysm354, Yale School of Management.
    23. Pfeifer, Phillip E., 1985. "Market Timing and Risk Reduction," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 20(4), pages 451-459, December.
    24. Stivers, Christopher T., 2003. "Firm-level return dispersion and the future volatility of aggregate stock market returns," Journal of Financial Markets, Elsevier, vol. 6(3), pages 389-411, May.
    25. Maio, Paulo, 2016. "Cross-sectional return dispersion and the equity premium," Journal of Financial Markets, Elsevier, vol. 29(C), pages 87-109.
    26. Mark Britten-Jones & Anthony Neuberger & Ingmar Nolte, 2011. "Improved Inference in Regression with Overlapping Observations," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 38(5-6), pages 657-683, June.
    27. Angelidis, Timotheos & Sakkas, Athanasios & Tessaromatis, Nikolaos, 2015. "Stock market dispersion, the business cycle and expected factor returns," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 265-279.
    28. Baltas, Nick & Karyampas, Dimitrios, 2018. "Forecasting the equity risk premium: The importance of regime-dependent evaluation," Journal of Financial Markets, Elsevier, vol. 38(C), pages 83-102.
    29. Diego García, 2013. "Sentiment during Recessions," Journal of Finance, American Finance Association, vol. 68(3), pages 1267-1300, June.
    30. 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.
    31. Matthew Spiegel, 2008. "Forecasting the Equity Premium: Where We Stand Today," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1453-1454, July.
    32. Avdis, Efstathios & Wachter, Jessica A., 2017. "Maximum likelihood estimation of the equity premium," Journal of Financial Economics, Elsevier, vol. 125(3), pages 589-609.
    33. Lewellen, Jonathan, 2004. "Predicting returns with financial ratios," Journal of Financial Economics, Elsevier, vol. 74(2), pages 209-235, November.
    34. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
    35. Donaldson, R. Glen & Kamstra, Mark J. & Kramer, Lisa A., 2010. "Estimating the Equity Premium," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(4), pages 813-846, August.
    36. Dichtl, Hubert & Drobetz, Wolfgang & Kryzanowski, Lawrence, 2016. "Timing the stock market: Does it really make no sense?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 10(C), pages 88-104.
    37. Julien Cujean & Michael Hasler, 2017. "Why Does Return Predictability Concentrate in Bad Times?," Journal of Finance, American Finance Association, vol. 72(6), pages 2717-2758, December.
    38. Connolly, Robert & Stivers, Chris, 2006. "Information content and other characteristics of the daily cross-sectional dispersion in stock returns," Journal of Empirical Finance, Elsevier, vol. 13(1), pages 79-112, January.
    39. Robert Connolly & Chris Stivers, 2003. "Momentum and Reversals in Equity‐Index Returns During Periods of Abnormal Turnover and Return Dispersion," Journal of Finance, American Finance Association, vol. 58(4), pages 1521-1556, August.
    40. George M. Constantinides, 2002. "Rational Asset Prices," NBER Working Papers 8826, National Bureau of Economic Research, Inc.
    41. Stasinopoulos, D. Mikis & Rigby, Robert A., 2007. "Generalized Additive Models for Location Scale and Shape (GAMLSS) in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 23(i07).
    42. John H. Cochrane, 2008. "The Dog That Did Not Bark: A Defense of Return Predictability," Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1533-1575, July.
    43. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
    44. Kellard, Neil M. & Nankervis, John C. & Papadimitriou, Fotios I., 2010. "Predicting the equity premium with dividend ratios: Reconciling the evidence," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 539-551, September.
    45. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
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    More about this item

    Keywords

    beta dispersion; market return predictability; systematic risk; predictice regression; distributional regression; market timing; investment stragies;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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