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On long memory behaviour and predictability of financial markets

  • Vo, Long H.
  • Roberts, Leigh

An immediate consequence of the Efficient Market Hypothesis (EMH) is the absence of auto-correlation of the return series of the financial prices and the exclusion of excess profitability made by any (active) trading strategy. However, the precondition for the validity of EMH, which assumes that all market participants can promptly receive and rationally react to the relevant information affecting the prices, might be (approximately) true for a long time horizon, but not for a short time horizon. By examining local long-range dependence (measured by the rolling Rescaled Range estimates of the Hurst index) of an empirical example, the local market inefficiency is inferred, and excess profitability of a simple trend-following trading strategies implies the potential for constructing a more profitable trading system by incorporating the former into the latter.

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Paper provided by Victoria University of Wellington, School of Economics and Finance in its series Working Paper Series with number 3361.

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Date of creation: 2014
Date of revision:
Handle: RePEc:vuw:vuwecf:3361
Contact details of provider: Postal: Alice Fong, Administrator, School of Economics and Finance, Victoria Business School, Victoria University of Wellington, PO Box 600 Wellington, New Zealand
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  1. Malliaropulos, Dimitrios & Priestley, Richard, 1999. "Mean reversion in Southeast Asian stock markets," Journal of Empirical Finance, Elsevier, vol. 6(4), pages 355-384, October.
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  7. James G. MacKinnon, 1992. "Approximate Asymptotic Distribution Functions for Unit Roots and Cointegration Tests," Working Papers 861, Queen's University, Department of Economics.
  8. Sanford J Grossman & Joseph E Stiglitz, 1997. "On the Impossibility of Informationally Efficient Markets," Levine's Working Paper Archive 1908, David K. Levine.
  9. Torben G. Andersen & Tim Bollerslev, 1996. "Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency Returns," NBER Working Papers 5752, National Bureau of Economic Research, Inc.
  10. Bollerslev, Tim & Wright, Jonathan H., 2000. "Semiparametric estimation of long-memory volatility dependencies: The role of high-frequency data," Journal of Econometrics, Elsevier, vol. 98(1), pages 81-106, September.
  11. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
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