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Learning and Stock Market Volatility

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Listed:
  • Klaus Adam

    () (Research Department CEPR and European Central Bank)

  • Albert Marcet
  • Juan Pablo Nicolini

Abstract

Introducing learning into a standard asset pricing model improves considerably its empirical performance. In a model of learning where today's stock price is determined by the expectation of tomorrow's stock price, the dynamics of expectations and actual price are such that the market has inertia. If the market has been increasing it will have a tendency to increase further, thereby generating large and persistent deviations of asset prices from fundamental values. For overvalued asset prices the model predicts the possibility of sudden and strong price decreases, i.e., 'stock market crashes', but no symmetric stock market increases in the presence of undervalued asset prices. These features emerge even though the deviations of agents' price expectations from perfectly rational return forecasts would be hard to detect given available sample sizes. Using a calibrated asset pricing model with habit persistence and learning, we can match the following quarterly U.S. asset pricing facts: the mean and volatility of stock returns; the mean, volatility, and autocorrelation of the price dividend ratio; and the average bond returns (equity premium). Consistent with empirical studies, the learning model also predicts that the price dividend ratio has predictive power for stock returns over the medium term (but not the short-term) and is unrelated to future fundamentals. The same model under rational expectations generates insufficient volatility and auto-correlation of the price dividend ratio and implies that the price dividend ratio is unrelated to future stock returns. The learning and rational expectations models both predict too much volatility of the short-term real interest rate, although the learning model performs somewhat better on this account.

Suggested Citation

  • Klaus Adam & Albert Marcet & Juan Pablo Nicolini, 2006. "Learning and Stock Market Volatility," Computing in Economics and Finance 2006 15, Society for Computational Economics.
  • Handle: RePEc:sce:scecfa:15
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    References listed on IDEAS

    as
    1. Balke, Nathan S & Fomby, Thomas B, 1997. "Threshold Cointegration," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 38(3), pages 627-645, August.
    2. Kapetanios, George & Shin, Yongcheol & Snell, Andy, 2003. "Testing for a unit root in the nonlinear STAR framework," Journal of Econometrics, Elsevier, vol. 112(2), pages 359-379, February.
    3. Robert J. Shiller, 1984. "Stock Prices and Social Dynamics," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 15(2), pages 457-510.
    4. Taylor, Mark P & Peel, David A & Sarno, Lucio, 2001. "Nonlinear Mean-Reversion in Real Exchange Rates: Toward a Solution to the Purchasing Power Parity Puzzles," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(4), pages 1015-1042, November.
    5. Kilian, Lutz & Taylor, Mark P., 2003. "Why is it so difficult to beat the random walk forecast of exchange rates?," Journal of International Economics, Elsevier, pages 85-107.
    6. Jeremy Berkowitz & Lorenzo Giorgianni, 2001. "Long-Horizon Exchange Rate Predictability?," The Review of Economics and Statistics, MIT Press, vol. 83(1), pages 81-91, February.
    7. Lucas, Robert Jr., 1982. "Interest rates and currency prices in a two-country world," Journal of Monetary Economics, Elsevier, vol. 10(3), pages 335-359.
    8. Georgios Chortareas & George Kapetanios, 2004. "The Yen Real Exchange Rate may be Stationary after all: Evidence from Non-linear Unit-root Tests," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(1), pages 113-131, February.
    9. Faust, Jon & Rogers, John H & Wright, Jonathan H, 2005. "News and Noise in G-7 GDP Announcements," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 403-419, June.
    10. Yin-Wong Cheung & Menzie D. Chinn & Ian W. Marsh, 2004. "How do UK-based foreign exchange dealers think their market operates?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 9(4), pages 289-306.
    11. Athanasios Orphanides, 2001. "Monetary Policy Rules Based on Real-Time Data," American Economic Review, American Economic Association, vol. 91(4), pages 964-985, September.
    12. Michael, Panos & Nobay, A Robert & Peel, David A, 1997. "Transactions Costs and Nonlinear Adjustment in Real Exchange Rates: An Empirical Investigation," Journal of Political Economy, University of Chicago Press, vol. 105(4), pages 862-879, August.
    13. Dean Croushore & Tom Stark, 2003. "A Real-Time Data Set for Macroeconomists: Does the Data Vintage Matter?," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 605-617, August.
    14. Christopher J. Neely & Lucio Sarno, 2002. "How well do monetary fundamentals forecast exchange rates?," Review, Federal Reserve Bank of St. Louis, issue Sep, pages 51-74.
    15. Cheung, Y. -W. & Chinn, M. D., 1998. "Integration, cointegration and the forecast consistency of structural exchange rate models," Journal of International Money and Finance, Elsevier, vol. 17(5), pages 813-830, October.
    16. S. Boragan Aruoba, 2008. "Data Revisions Are Not Well Behaved," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2-3), pages 319-340, March.
    17. Enders, Walter & Granger, Clive W J, 1998. "Unit-Root Tests and Asymmetric Adjustment with an Example Using the Term Structure of Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 304-311, July.
    18. Faust, Jon & Rogers, John H. & H. Wright, Jonathan, 2003. "Exchange rate forecasting: the errors we've really made," Journal of International Economics, Elsevier, vol. 60(1), pages 35-59, May.
    19. Mehmet Caner & Bruce E. Hansen, 2001. "Threshold Autoregression with a Unit Root," Econometrica, Econometric Society, vol. 69(6), pages 1555-1596, November.
    20. Mark, Nelson C, 1995. "Exchange Rates and Fundamentals: Evidence on Long-Horizon Predictability," American Economic Review, American Economic Association, vol. 85(1), pages 201-218, March.
    21. Kilian, Lutz, 1999. "Exchange Rates and Monetary Fundamentals: What Do We Learn from Long-Horizon Regressions?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 491-510, Sept.-Oct.
    22. Coakley, Jerry & Fuertes, Ana-Maria, 2001. "Border costs and real exchange rate dynamics in Europe," Journal of Policy Modeling, Elsevier, vol. 23(6), pages 669-676, August.
    23. 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.
    24. Mark P. Taylor, 1995. "The Economics of Exchange Rates," Journal of Economic Literature, American Economic Association, vol. 33(1), pages 13-47, March.
    25. Chen, Jian & Mark, Nelson C, 1996. "Alternative Long-Horizon Exchange-Rate Predictors," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 1(4), pages 229-250, October.
    26. Sercu, Piet & Uppal, Raman & Van Hulle, Cynthia, 1995. " The Exchange Rate in the Presence of Transaction Costs: Implications for Tests of Purchasing Power Parity," Journal of Finance, American Finance Association, vol. 50(4), pages 1309-1319, September.
    27. Taylor, Mark P. & Peel, David A., 2000. "Nonlinear adjustment, long-run equilibrium and exchange rate fundamentals," Journal of International Money and Finance, Elsevier, vol. 19(1), pages 33-53, February.
    28. N. Gregory Mankiw & Matthew D. Shapiro, 1986. "News or Noise? An Analysis of GNP Revisions," NBER Working Papers 1939, National Bureau of Economic Research, Inc.
    29. Dirk Te Velde, 2001. "Balance of payments prospects in EMU," National Institute of Economic and Social Research (NIESR) Discussion Papers 178, National Institute of Economic and Social Research.
    30. Cheung, Yin-Wong & Chinn, Menzie David, 2001. "Currency traders and exchange rate dynamics: a survey of the US market," Journal of International Money and Finance, Elsevier, vol. 20(4), pages 439-471, August.
    31. Neftci, Salih N, 1984. "Are Economic Time Series Asymmetric over the Business Cycle?," Journal of Political Economy, University of Chicago Press, vol. 92(2), pages 307-328, April.
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    Citations

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    Cited by:

    1. Klaus Adam & Pei Kuang & Albert Marcet, 2012. "House Price Booms and the Current Account," NBER Macroeconomics Annual, University of Chicago Press, vol. 26(1), pages 77-122.
    2. Eva Carceles-Poveda & Chryssi Giannitsarou, 2008. "Asset Pricing with Adaptive Learning," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 11(3), pages 629-651, July.
    3. Francesco Caprioli & Pietro Rizza & Pietro Tommasino, 2011. "Optimal Fiscal Policy when Agents Fear Government Default," Revue économique, Presses de Sciences-Po, vol. 62(6), pages 1031-1043.
    4. George W. Evans, 2011. "Comment on "Natural Expectations, Macroeconomic Dynamics, and Asset Pricing"," NBER Chapters,in: NBER Macroeconomics Annual 2011, Volume 26, pages 61-71 National Bureau of Economic Research, Inc.
    5. William A. Branch & George W. Evans, 2011. "Learning about Risk and Return: A Simple Model of Bubbles and Crashes," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(3), pages 159-191, July.
    6. Adam, Klaus & Marcet, Albert, 2011. "Internal rationality, imperfect market knowledge and asset prices," Journal of Economic Theory, Elsevier, vol. 146(3), pages 1224-1252, May.
    7. Eva Carceles-Poveda & Chryssi Giannitsarou, 2008. "Asset Pricing with Adaptive Learning," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 11(3), pages 629-651, July.
    8. Klaus Adam & Albert Marcet, 2010. "Booms and Busts in Asset Prices," IMES Discussion Paper Series 10-E-02, Institute for Monetary and Economic Studies, Bank of Japan.
    9. Adam, Klaus & Marcet, Albert, 2009. "Internal Rationality and Asset Prices," CEPR Discussion Papers 7498, C.E.P.R. Discussion Papers.

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