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Financial Market Efficiency Tests

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  • Tim Bollerslev
  • Robert J. Hodrick

Abstract

This paper provides a selective survey of the voluminous literature on tests for market efficiency. The ideas discussed include standard autocorrelation tests, multi-period regression tests and volatility tests. The formulation and estimation of models for time-varying volatility are also considered. Dependence in second-order moments plays an important role in implementing and understanding tests for market efficiency. All of the reported test statistics and model estimates are calculated with monthly data on value-weighted NYSE stock prices and dividends. The distributions of the test statistics under various alternatives, including fads and bubbles, are illustrated through the use of Monte Carlo methods. In addition to the standard constant discount rate present value model, we postulate and simulate a new fundamental price relationship that accounts for the time-varying uncertainty in the monthly dividend growth rates. Allowing the discount rate to be a function of the time-varying uncertainty in the dividend process results in a simulated fundamental price series that is broadly consistent with most of the sample statistics of the actual data.

Suggested Citation

  • Tim Bollerslev & Robert J. Hodrick, 1992. "Financial Market Efficiency Tests," NBER Working Papers 4108, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:4108
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    1. Camilleri, Silvio John, 2005. "Can a Stock Index Be Less Efficient Than Underlying Shares? An Analysis Using Malta Stock Exchange Data," MPRA Paper 84574, University Library of Munich, Germany.
    2. Angelos Kanas, 2003. "Non-linear forecasts of stock returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(4), pages 299-315.
    3. Rizwana Bashir & Rabia Shakir & Badar Ashfaq & Atif Hassan, 2014. "The Efficiency of Foreign Exchange Markets in Pakistan: An Empirical Analysis," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 19(1), pages 133-149, Jan-June.
    4. Bordignon, Silvano & Caporin, Massimiliano & Lisi, Francesco, 2007. "Generalised long-memory GARCH models for intra-daily volatility," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5900-5912, August.
    5. Andrew Ang & Geert Bekaert, 2001. "Stock Return Predictability: Is it There?," NBER Working Papers 8207, National Bureau of Economic Research, Inc.
    6. Ravi Bansal & Amir Yaron, 2004. "Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles," Journal of Finance, American Finance Association, vol. 59(4), pages 1481-1509, August.
    7. Kan, Denis & Andreosso-O'Callaghan, B., 2007. "Examination of the efficient market hypothesis--the case of post-crisis Asia Pacific countries," Journal of Asian Economics, Elsevier, vol. 18(2), pages 294-313, April.
    8. Tim Bollerslev & Eric Ghysels, 1994. "On Periodic Autogressive Conditional Heteroskedasticity," CIRANO Working Papers 94s-03, CIRANO.
    9. Jorge Selaive & Vicente Tuesta, 2006. "Can fluctuations in the consumption-wealth ratio help to predict exchange rates?," Applied Financial Economics, Taylor & Francis Journals, vol. 16(17), pages 1251-1263.
    10. Lennart Berg, 2003. "Deterministic Seasonal Volatility in a Small and Integrated Stock Market: The Case of Sweden," Finnish Economic Papers, Finnish Economic Association, vol. 16(2), pages 61-71, Autumn.
    11. Moore, Bartholomew & Schaller, Huntley, 1996. "Learning, regime switches, and equilibrium asset pricing dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 20(6-7), pages 979-1006.
    12. Bachar Fakhry & Christian Richter, 2015. "Is the sovereign debt market efficient? Evidence from the US and German sovereign debt markets," International Economics and Economic Policy, Springer, vol. 12(3), pages 339-357, September.
    13. Smith, Peter & Wickens, Michael, 2002. " Asset Pricing with Observable Stochastic Discount Factors," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 397-446, July.
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    15. repec:ksp:journ2:v:4:y:2017:i:2:p:239-249 is not listed on IDEAS
    16. Narayan, Seema & Smyth, Russell, 2015. "The financial econometrics of price discovery and predictability," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 380-393.
    17. Massimiliano Caporin & Francesco Lisi, 2010. "Misspecification tests for periodic long memory GARCH models," Statistical Methods & Applications, Springer;SocietĂ  Italiana di Statistica, vol. 19(1), pages 47-62, March.
    18. Bartolini, Leonardo & Giorgianni, Lorenzo, 2001. "Excess Volatility of Exchange Rates with Unobservable Fundamentals," Review of International Economics, Wiley Blackwell, vol. 9(3), pages 518-530, August.
    19. 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.
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    21. Leonardo Bartolini & Gordon M. Bodnar, 1996. "Are Exchange Rates Excessively Volatile? And What Does "Excessively Volatile" Mean, Anyway?," IMF Staff Papers, Palgrave Macmillan, vol. 43(1), pages 72-96, March.
    22. Simon van Norden & Huntley Schaller, 2002. "Fads or bubbles?," Empirical Economics, Springer, vol. 27(2), pages 335-362.
    23. Asada, Toichiro & Semmler, Willi, 1995. "Growth and finance: An intertemporal model," Journal of Macroeconomics, Elsevier, vol. 17(4), pages 623-649.
    24. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
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