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Are US stock index returns predictable? Evidence from automatic autocorrelation-based tests

Author Info

Listed author(s):
  • Kian-Ping Lim
  • Weiwei Luo
  • Jae H. Kim

Abstract

This article re-examines the evidence of return predictability for three major US stock indices using two recently developed data-driven tests, namely the automatic portmanteau Box--Pierce test and the wild bootstrapped automatic variance ratio test. In tracking the time variation of return predictability via rolling estimation window, we find that those periods with significant return autocorrelations can largely be associated with major exogenous events. Theoretically, the documented time varying nature of predictable patterns is consistent with the adaptive markets hypothesis.

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File URL: http://hdl.handle.net/10.1080/00036846.2011.613782
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Article provided by Taylor & Francis Journals in its journal Applied Economics.

Volume (Year): 45 (2013)
Issue (Month): 8 (March)
Pages: 953-962

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Handle: RePEc:taf:applec:45:y:2013:i:8:p:953-962
DOI: 10.1080/00036846.2011.613782
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Cited by:

  1. Urquhart, Andrew & Gebka, Bartosz & Hudson, Robert, 2015. "How exactly do markets adapt? Evidence from the moving average rule in three developed markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 127-147.
  2. Rahman, Md. Lutfur & Lee, Doowon & Shamsuddin, Abul, 2017. "Time-varying return predictability in South Asian equity markets," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 179-200.
  3. Khurshid M. Kiani, 2016. "On Modelling and Forecasting Predictable Components in European Stock Markets," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 487-502, October.
  4. Noda, Akihiko, 2016. "A test of the adaptive market hypothesis using a time-varying AR model in Japan," Finance Research Letters, Elsevier, vol. 17(C), pages 66-71.
  5. repec:ove:journl:aid:11556 is not listed on IDEAS
  6. Verheyden, Tim & De Moor, Lieven & Van den Bossche, Filip, 2015. "Towards a new framework on efficient markets," Research in International Business and Finance, Elsevier, vol. 34(C), pages 294-308.
  7. Maderitsch, R., 2015. "Information transmission between stock markets in Hong Kong, Europe and the US: New evidence on time- and state-dependence," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 13-36.
  8. Urquhart, Andrew & McGroarty, Frank, 2014. "Calendar effects, market conditions and the Adaptive Market Hypothesis: Evidence from long-run U.S. data," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 154-166.
  9. Graham Smith & Aneta Dyakova, 2016. "The Relative Predictability of Stock Markets in the Americas," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 21(2), pages 131-142, 04.
  10. Mirzaee Ghazani, Majid & Khalili Araghi, Mansour, 2014. "Evaluation of the adaptive market hypothesis as an evolutionary perspective on market efficiency: Evidence from the Tehran stock exchange," Research in International Business and Finance, Elsevier, vol. 32(C), pages 50-59.
  11. Urquhart, Andrew & Hudson, Robert, 2013. "Efficient or adaptive markets? Evidence from major stock markets using very long run historic data," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 130-142.
  12. Urquhart, Andrew & McGroarty, Frank, 2016. "Are stock markets really efficient? Evidence of the adaptive market hypothesis," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 39-49.

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