IDEAS home Printed from https://ideas.repec.org/p/hhs/sdueko/2019_008.html
   My bibliography  Save this paper

Predictability concentrates in bad times. And so does disagreement

Author

Listed:

Abstract

Within a standard risk-based asset pricing framework with rational expectations, realized returns have two components: Predictable risk premiums and unpredictable shocks. In bad times, the price of risk increases. Hence, the predictable fraction of returns – and predictability – increases. “Disagreement” (dispersion in analyst forecasts) also intensifies in bad times if (i) analysts report (close to) risk-neutral expectations weighted by state prices, which become more volatile, or (ii) dividend volatility changes with the price of risk – for example, because consumption volatility changes. In both cases, individual analysts produce unbiased forecasts based on partial information.

Suggested Citation

  • de Oliveira Souza, Thiago, 2019. "Predictability concentrates in bad times. And so does disagreement," Discussion Papers on Economics 8/2019, University of Southern Denmark, Department of Economics.
  • Handle: RePEc:hhs:sdueko:2019_008
    as

    Download full text from publisher

    File URL: https://www.sdu.dk/-/media/files/om_sdu/institutter/ivoe/disc_papers/disc_2019/dpbe8_2019.pdf?la=en&hash=82410B9523F30EEFA2240E2AE5BA1BFD1AD2E515
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Adam, Klaus & Matveev, Dmitry & Nagel, Stefan, 2021. "Do survey expectations of stock returns reflect risk adjustments?," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 723-740.
    2. Martin Lettau & Stijn Van Nieuwerburgh, 2008. "Reconciling the Return Predictability Evidence," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1607-1652, July.
    3. 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.
    4. Evan W. Anderson & Eric Ghysels & Jennifer L. Juergens, 2005. "Do Heterogeneous Beliefs Matter for Asset Pricing?," The Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 875-924.
    5. Pettenuzzo, Davide & Timmermann, Allan & Valkanov, Rossen, 2014. "Forecasting stock returns under economic constraints," Journal of Financial Economics, Elsevier, vol. 114(3), pages 517-553.
    6. Bansal, Ravi & Kiku, Dana & Yaron, Amir, 2016. "Risks for the long run: Estimation with time aggregation," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 52-69.
    7. Lucas, Robert Jr., 1972. "Expectations and the neutrality of money," Journal of Economic Theory, Elsevier, vol. 4(2), pages 103-124, April.
    8. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    9. Marco Ottaviani & Peter Norman Sørensen, 2015. "Price Reaction to Information with Heterogeneous Beliefs and Wealth Effects: Underreaction, Momentum, and Reversal," American Economic Review, American Economic Association, vol. 105(1), pages 1-34, January.
    10. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
    11. John H. Boyd & Jian Hu & Ravi Jagannathan, 2005. "The Stock Market's Reaction to Unemployment News: Why Bad News Is Usually Good for Stocks," Journal of Finance, American Finance Association, vol. 60(2), pages 649-672, April.
    12. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    13. Stefano Cassella & Huseyin Gulen, 2018. "Extrapolation Bias and the Predictability of Stock Returns by Price-Scaled Variables," The Review of Financial Studies, Society for Financial Studies, vol. 31(11), pages 4345-4397.
    14. Oliver Boguth & Lars‐Alexander Kuehn, 2013. "Consumption Volatility Risk," Journal of Finance, American Finance Association, vol. 68(6), pages 2589-2615, December.
    15. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    16. John H. Cochrane, 2011. "Presidential Address: Discount Rates," Journal of Finance, American Finance Association, vol. 66(4), pages 1047-1108, August.
    17. Martin Chalkley & In Ho Lee, 1998. "Learning and Asymmetric Business Cycles," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 1(3), pages 623-645, July.
    18. Roger K. Loh & René M. Stulz, 2018. "Is Sell‐Side Research More Valuable in Bad Times?," Journal of Finance, American Finance Association, vol. 73(3), pages 959-1013, June.
    19. Jonathan B. Berk & Richard C. Green & Vasant Naik, 1999. "Optimal Investment, Growth Options, and Security Returns," Journal of Finance, American Finance Association, vol. 54(5), pages 1553-1607, October.
    20. Roll, Richard, 1977. "A critique of the asset pricing theory's tests Part I: On past and potential testability of the theory," Journal of Financial Economics, Elsevier, vol. 4(2), pages 129-176, March.
    21. Stijn Van Nieuwerburgh & Laura Veldkamp, 2010. "Information Acquisition and Under-Diversification," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 779-805.
    22. John Y. Campbell, Robert J. Shiller, 1988. "The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors," The Review of Financial Studies, Society for Financial Studies, vol. 1(3), pages 195-228.
    23. Michael Johannes & Arthur Korteweg & Nicholas Polson, 2014. "Sequential Learning, Predictability, and Optimal Portfolio Returns," Journal of Finance, American Finance Association, vol. 69(2), pages 611-644, April.
    24. Roméo Tédongap, 2015. "Consumption Volatility and the Cross-Section of Stock Returns," Review of Finance, European Finance Association, vol. 19(1), pages 367-405.
    25. Snehal Banerjee & Ilan Kremer, 2010. "Disagreement and Learning: Dynamic Patterns of Trade," Journal of Finance, American Finance Association, vol. 65(4), pages 1269-1302, August.
    26. Cochrane, John H, 1991. "Production-Based Asset Pricing and the Link between Stock Returns and Economic Fluctuations," Journal of Finance, American Finance Association, vol. 46(1), pages 209-237, March.
    27. Dangl, Thomas & Halling, Michael, 2012. "Predictive regressions with time-varying coefficients," Journal of Financial Economics, Elsevier, vol. 106(1), pages 157-181.
    28. Diego García, 2013. "Sentiment during Recessions," Journal of Finance, American Finance Association, vol. 68(3), pages 1267-1300, June.
    29. Veldkamp, Laura L., 2005. "Slow boom, sudden crash," Journal of Economic Theory, Elsevier, vol. 124(2), pages 230-257, October.
    30. de Oliveira Souza, Thiago, 2018. "Red tape asset pricing," Discussion Papers on Economics 8/2018, University of Southern Denmark, Department of Economics.
    31. Pyun, Sungjune, 2019. "Variance risk in aggregate stock returns and time-varying return predictability," Journal of Financial Economics, Elsevier, vol. 132(1), pages 150-174.
    32. Henkel, Sam James & Martin, J. Spencer & Nardari, Federico, 2011. "Time-varying short-horizon predictability," Journal of Financial Economics, Elsevier, vol. 99(3), pages 560-580, March.
    33. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
    34. 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.
    35. Moskowitz, Tobias J. & Ooi, Yao Hua & Pedersen, Lasse Heje, 2012. "Time series momentum," Journal of Financial Economics, Elsevier, vol. 104(2), pages 228-250.
    36. Ronnie Sadka & Anna Scherbina, 2007. "Analyst Disagreement, Mispricing, and Liquidity," Journal of Finance, American Finance Association, vol. 62(5), pages 2367-2403, October.
    37. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    38. McQueen, Grant & Roley, V Vance, 1993. "Stock Prices, News, and Business Conditions," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 683-707.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. de Oliveira Souza, Thiago, 2020. "Two out-of-sample forecasting models of the equity premium," Discussion Papers on Economics 11/2020, University of Southern Denmark, Department of Economics.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tsiakas, Ilias & Li, Jiahan & Zhang, Haibin, 2020. "Equity premium prediction and the state of the economy," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 75-95.
    2. Dichtl, Hubert & Drobetz, Wolfgang & Neuhierl, Andreas & Wendt, Viktoria-Sophie, 2021. "Data snooping in equity premium prediction," International Journal of Forecasting, Elsevier, vol. 37(1), pages 72-94.
    3. Sharma, Susan Sunila & Narayan, Paresh Kumar, 2022. "Technology shocks and stock returns: A long-term perspective," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 67-83.
    4. Davide Pettenuzzo & Francesco Ravazzolo, 2016. "Optimal Portfolio Choice Under Decision‐Based Model Combinations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1312-1332, November.
    5. Leland E. Farmer & Lawrence Schmidt & Allan Timmermann, 2023. "Pockets of Predictability," Journal of Finance, American Finance Association, vol. 78(3), pages 1279-1341, June.
    6. Smith, Simon C., 2021. "International stock return predictability," International Review of Financial Analysis, Elsevier, vol. 78(C).
    7. , & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," CEPR Discussion Papers 16357, C.E.P.R. Discussion Papers.
    8. Yu, Deshui & Huang, Difang, 2023. "Cross-sectional uncertainty and expected stock returns," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 321-340.
    9. Pan, Zhiyuan & Pettenuzzo, Davide & Wang, Yudong, 2020. "Forecasting stock returns: A predictor-constrained approach," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 200-217.
    10. Dangl, Thomas & Halling, Michael, 2012. "Predictive regressions with time-varying coefficients," Journal of Financial Economics, Elsevier, vol. 106(1), pages 157-181.
    11. Lansing, Kevin J. & LeRoy, Stephen F. & Ma, Jun, 2022. "Examining the sources of excess return predictability: Stochastic volatility or market inefficiency?," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 50-72.
    12. Mykola Babiak & Jozef Barunik, 2020. "Deep Learning, Predictability, and Optimal Portfolio Returns," CERGE-EI Working Papers wp677, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    13. Nonejad, Nima, 2021. "Predicting equity premium using dynamic model averaging. Does the state–space representation matter?," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    14. Lawrenz, Jochen & Zorn, Josef, 2017. "Predicting international stock returns with conditional price-to-fundamental ratios," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 159-184.
    15. Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
    16. Pyun, Sungjune, 2019. "Variance risk in aggregate stock returns and time-varying return predictability," Journal of Financial Economics, Elsevier, vol. 132(1), pages 150-174.
    17. Wang, Yudong & Pan, Zhiyuan & Liu, Li & Wu, Chongfeng, 2019. "Oil price increases and the predictability of equity premium," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 43-58.
    18. Chen, Yong & Da, Zhi & Huang, Dayong, 2022. "Short selling efficiency," Journal of Financial Economics, Elsevier, vol. 145(2), pages 387-408.
    19. de Oliveira Souza, Thiago, 2019. "A critique of momentum anomalies," Discussion Papers on Economics 5/2019, University of Southern Denmark, Department of Economics.
    20. Golab, Anna & Bannigidadmath, Deepa & Pham, Thach Ngoc & Thuraisamy, Kannan, 2022. "Economic policy uncertainty and industry return predictability – Evidence from the UK," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 433-447.

    More about this item

    Keywords

    Predictability; bad times; efficient market hypothesis; disagreement; rational expectations;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hhs:sdueko:2019_008. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Astrid Holm Nielsen (email available below). General contact details of provider: https://edirc.repec.org/data/okioudk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.