IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/16222.html
   My bibliography  Save this paper

Hard Times

Author

Listed:
  • John Y. Campbell
  • Stefano Giglio
  • Christopher Polk

Abstract

This paper shows that the stock market downturns of 2000-2002 and 2007-09 have very different proximate causes. The early 2000's saw a large increase in the discount rates applied to corporate profits by rational investors, while the late 2000's saw a decrease in rational expectations of future profits. In each case the downturn reversed the trends of the previous boom. We reach these conclusions using a vector autoregressive model of aggregate stock returns and valuations, estimated imposing the cross-sectional restrictions of the intertemporal capital asset pricing model (ICAPM). As stock returns are very noisy, exploiting an economic model such as the ICAPM to extract information about future corporate profits from realized returns can potentially be very useful. We confirm that the ICAPM restrictions improve the out-of-sample forecasting performance of VAR models for stock returns, and that our conclusions are consistent with a simple graphical data analysis. Our findings imply that the 2007-09 downturn was particularly serious for rational long-term investors, who did not expect a strong recovery of stock prices as they did earlier in the decade.

Suggested Citation

  • John Y. Campbell & Stefano Giglio & Christopher Polk, 2010. "Hard Times," NBER Working Papers 16222, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:16222
    Note: AP
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w16222.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    • Campbell, John Y. & Giglio, Stefano & Polk, Christopher, 2013. "Hard Times," Scholarly Articles 12172786, Harvard University Department of Economics.

    References listed on IDEAS

    as
    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. Whitney K. Newey & Richard J. Smith, 2004. "Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators," Econometrica, Econometric Society, vol. 72(1), pages 219-255, January.
    3. Campbell, John Y, 1991. "A Variance Decomposition for Stock Returns," Economic Journal, Royal Economic Society, vol. 101(405), pages 157-179, March.
    4. Martin Lettau & Sydney C. Ludvigson, 2014. "Shocks and Crashes," NBER Macroeconomics Annual, University of Chicago Press, vol. 28(1), pages 293-354.
    5. John Y. Campbell & Christopher Polk & Tuomo Vuolteenaho, 2010. "Growth or Glamour? Fundamentals and Systematic Risk in Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 305-344, January.
    6. 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.
    7. Larry G. Epstein & Stanley E. Zin, 2013. "Substitution, risk aversion and the temporal behavior of consumption and asset returns: A theoretical framework," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 12, pages 207-239, World Scientific Publishing Co. Pte. Ltd..
    8. Engsted, Tom & Pedersen, Thomas Q. & Tanggaard, Carsten, 2012. "Pitfalls in VAR based return decompositions: A clarification," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1255-1265.
    9. Campbell, John Y. & Giglio, Stefano & Polk, Christopher & Turley, Robert, 2018. "An intertemporal CAPM with stochastic volatility," Journal of Financial Economics, Elsevier, vol. 128(2), pages 207-233.
    10. Ravi Bansal & Dana Kiku & Ivan Shaliastovich & Amir Yaron, 2014. "Volatility, the Macroeconomy, and Asset Prices," Journal of Finance, American Finance Association, vol. 69(6), pages 2471-2511, December.
    11. 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.
    12. John Y. Campbell & Tuomo Vuolteenaho, 2004. "Bad Beta, Good Beta," American Economic Review, American Economic Association, vol. 94(5), pages 1249-1275, December.
    13. John H. Cochrane, 2008. "The Dog That Did Not Bark: A Defense of Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1533-1575, July.
    14. Epstein, Larry G & Zin, Stanley E, 1991. "Substitution, Risk Aversion, and the Temporal Behavior of Consumption and Asset Returns: An Empirical Analysis," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 263-286, April.
    15. 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.
    16. Clark, Todd E. & West, Kenneth D., 2006. "Using out-of-sample mean squared prediction errors to test the martingale difference hypothesis," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 155-186.
    17. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    18. Long Chen & Xinlei Zhao, 2009. "Return Decomposition," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5213-5249, December.
    19. Olivier J. Blanchard & Mark W. Watson, 1986. "Are Business Cycles All Alike?," NBER Chapters, in: The American Business Cycle: Continuity and Change, pages 123-180, National Bureau of Economic Research, Inc.
    20. John H. Cochrane, 2011. "Presidential Address: Discount Rates," Journal of Finance, American Finance Association, vol. 66(4), pages 1047-1108, August.
    21. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    22. Campbell, John Y, 1996. "Understanding Risk and Return," Journal of Political Economy, University of Chicago Press, vol. 104(2), pages 298-345, April.
    23. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, July.
    24. Campbell, John Y, 1993. "Intertemporal Asset Pricing without Consumption Data," American Economic Review, American Economic Association, vol. 83(3), pages 487-512, June.
    25. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    26. 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.
    27. 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.
    28. Schroder, Mark & Skiadas, Costis, 1999. "Optimal Consumption and Portfolio Selection with Stochastic Differential Utility," Journal of Economic Theory, Elsevier, vol. 89(1), pages 68-126, November.
    29. Hansen, Lars Peter & Heaton, John & Yaron, Amir, 1996. "Finite-Sample Properties of Some Alternative GMM Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 262-280, July.
    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. Tobias Adrian & Richard K. Crump & Erik Vogt, 2019. "Nonlinearity and Flight‐to‐Safety in the Risk‐Return Trade‐Off for Stocks and Bonds," Journal of Finance, American Finance Association, vol. 74(4), pages 1931-1973, August.
    2. William N. Goetzmann & Dasol Kim, 2018. "Negative bubbles: What happens after a crash," European Financial Management, European Financial Management Association, vol. 24(2), pages 171-191, March.
    3. Dr. Thomas Nitschka, 2014. "The Good? The Bad? The Ugly? Which news drive (co)variation in Swiss and US bond and stock excess returns?," Working Papers 2014-01, Swiss National Bank.
    4. Thomas Nitschka, 2014. "What News Drive Variation in Swiss and US Bond and Stock Excess Returns?," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 150(II), pages 89-118, June.
    5. Botshekan, Mahmoud & Kraeussl, Roman & Lucas, Andre, 2012. "Cash Flow and Discount Rate Risk in Up and Down Markets: What Is Actually Priced?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 47(6), pages 1279-1301, December.
    6. Dr. Thomas Nitschka, 2014. "Have investors been looking for exposure to specific countries since the global financial crisis? - Insights from the Swiss franc bond market," Working Papers 2014-13, Swiss National Bank.
    7. Stijn Claessens & M Ayhan Kose, 2017. "Asset prices and macroeconomic outcomes: a survey," BIS Working Papers 676, Bank for International Settlements.
    8. Yeh, Chung-Ying & Hsu, Junming & Wang, Kai-Li & Lin, Che-Hui, 2015. "Explaining the default risk anomaly by the two-beta model," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 16-33.
    9. Maio, Paulo, 2013. "Return decomposition and the Intertemporal CAPM," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4958-4972.
    10. Benjamin Beckers & Kerstin Bernoth, 2016. "Monetary Policy and Mispricing in Stock Markets," Discussion Papers of DIW Berlin 1605, DIW Berlin, German Institute for Economic Research.
    11. Maio, Paulo & Philip, Dennis, 2015. "Macro variables and the components of stock returns," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 287-308.
    12. Celiker, Umut & Kayacetin, Nuri Volkan & Kumar, Raman & Sonaer, Gokhan, 2016. "Cash flow news, discount rate news, and momentum," Journal of Banking & Finance, Elsevier, vol. 72(C), pages 240-254.
    13. Beckers, Benjamin & Bernoth, Kerstin, 2016. "Monetary Policy and Asset Mispricing," VfS Annual Conference 2016 (Augsburg): Demographic Change 145684, Verein für Socialpolitik / German Economic Association.
    14. Volkov, Nikanor I. & Smith, Garrett C., 2015. "Corporate diversification and firm value during economic downturns," The Quarterly Review of Economics and Finance, Elsevier, vol. 55(C), pages 160-175.

    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. Maio, Paulo, 2013. "Return decomposition and the Intertemporal CAPM," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4958-4972.
    2. Maio, Paulo & Philip, Dennis, 2015. "Macro variables and the components of stock returns," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 287-308.
    3. Campbell, John Y. & Giglio, Stefano & Polk, Christopher & Turley, Robert, 2018. "An intertemporal CAPM with stochastic volatility," Journal of Financial Economics, Elsevier, vol. 128(2), pages 207-233.
    4. Maio, Paulo & Santa-Clara, Pedro, 2012. "Multifactor models and their consistency with the ICAPM," Journal of Financial Economics, Elsevier, vol. 106(3), pages 586-613.
    5. 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.
    6. Lin, Qi & Lin, Xi, 2021. "Cash conversion cycle and aggregate stock returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    7. Maio, Paulo & Xu, Danielle, 2020. "Cash-flow or return predictability at long horizons? The case of earnings yield," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 172-192.
    8. Roh, Tai-Yong & Lee, Changjun & Min, Byoung-Kyu, 2019. "Consumption growth predictability and asset prices," Journal of Empirical Finance, Elsevier, vol. 51(C), pages 95-118.
    9. Jessica A. Wachter, 2010. "Asset Allocation," Annual Review of Financial Economics, Annual Reviews, vol. 2(1), pages 175-206, December.
    10. John Y. Campbell & Christopher Polk & Tuomo Vuolteenaho, 2010. "Growth or Glamour? Fundamentals and Systematic Risk in Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 305-344, January.
    11. Ma, Feng & Wang, Ruoxin & Lu, Xinjie & Wahab, M.I.M., 2021. "A comprehensive look at stock return predictability by oil prices using economic constraint approaches," International Review of Financial Analysis, Elsevier, vol. 78(C).
    12. Bianchi, Francesco, 2020. "The Great Depression and the Great Recession: A view from financial markets," Journal of Monetary Economics, Elsevier, vol. 114(C), pages 240-261.
    13. John Y. Campbell & Tuomo Vuolteenaho, 2004. "Bad Beta, Good Beta," American Economic Review, American Economic Association, vol. 94(5), pages 1249-1275, December.
    14. John Y. Campbell, 2000. "Asset Pricing at the Millennium," Journal of Finance, American Finance Association, vol. 55(4), pages 1515-1567, August.
    15. Reis, Pedro Manuel Nogueira & Pinho, Carlos, 2020. "A new European investor sentiment index (EURsent) and its return and volatility predictability," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    16. Michail Koubouros & Dimitrios Malliaropulos & Ekaterini Panopoulou, 2010. "Long-run cash flow and discount-rate risks in the cross-section of US returns," The European Journal of Finance, Taylor & Francis Journals, vol. 16(3), pages 227-244.
    17. Bollerslev, Tim & Xu, Lai & Zhou, Hao, 2015. "Stock return and cash flow predictability: The role of volatility risk," Journal of Econometrics, Elsevier, vol. 187(2), pages 458-471.
    18. Gonçalves, Andrei S., 2021. "The short duration premium," Journal of Financial Economics, Elsevier, vol. 141(3), pages 919-945.
    19. Dunbar, Kwamie, 2021. "Pricing the hedging factor in the cross-section of stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    20. Ruan, Qingsong & Wang, Zilin & Zhou, Yaping & Lv, Dayong, 2020. "A new investor sentiment indicator (ISI) based on artificial intelligence: A powerful return predictor in China," Economic Modelling, Elsevier, vol. 88(C), pages 47-58.

    More about this item

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:nbr:nberwo:16222. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.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.