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Do Moving Average Trading Rule Results Imply Nonlinearities in Foreign Exchange?

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  • Blake LeBaron

    ()
    (University of Wisconsin - Madison)

Abstract

This paper tests whether fitted linear models can replicate results from moment tests inspired by moving average technical trading rules for weekly foreign exchange series. Estimation is performed using standard OLS and maximum likelihood methods, along with a simulated method of moments technique which incorporates the trading rule moments into the estimation procedure. Results show that linear models are capable of replicating the trading rule moments along with the small autocorrelations observed in these series. This result holds for parameter values estimated using SMM and GARCH disturbances, but not for parameters estimated using maximum likelihood. The estimated models are simulated to examine the amount of predictability over long horizons.

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Bibliographic Info

Paper provided by University of Wisconsin - Madison in its series Working papers with number _005.

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Handle: RePEc:wop:wimahp:_005

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Cited by:
  1. Hans Dewachter & Marco Lyrio, 2005. "The economic value of technical trading rules: a nonparametric utility-based approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 10(1), pages 41-62.
  2. Ronald J. Balvers & Yangru Wu, 2005. "Optimal Transaction Filters Under Transitory Trading Opportunities: Theory and Empirical Illustration," Working Papers 022005, Hong Kong Institute for Monetary Research.
  3. Mark, Nelson C & Wu, Yangru, 1998. "Rethinking Deviations from Uncovered Interest Parity: The Role of Covariance Risk and Noise," Economic Journal, Royal Economic Society, vol. 108(451), pages 1686-1706, November.
  4. Bertrand Maillet & Thierry Michel, 2000. "Further insights on the puzzle of technical analysis profitability," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 196-224.
  5. Nelson C. Mark & Yangru Wu, 1997. "Risk, Policy Rules, and Noise: Rethinking Deviations from Uncovered Interest Parity," Tinbergen Institute Discussion Papers 97-041/2, Tinbergen Institute.
  6. Spyros Skouras, 1998. "Financial Returns and Efficiency as seen by an Artificial Technical Analyst," Finance 9808001, EconWPA, revised 24 Aug 1998.
  7. Emmanuel Acar & Stephen Satchell, 1997. "A theoretical analysis of trading rules: an application to the moving average case with Markovian returns," Applied Mathematical Finance, Taylor & Francis Journals, vol. 4(3), pages 165-180.
  8. Alessandro Beber, 1999. "Il dibattito su dignità ed efficacia dell'analisi tecnica nell'economia finanziaria," Alea Tech Reports 003, Department of Computer and Management Sciences, University of Trento, Italy, revised 14 Jun 2008.
  9. Michael Dueker & Christopher J. Neely, 2006. "Can Markov switching models predict excess foreign exchange returns?," Working Papers 2001-021, Federal Reserve Bank of St. Louis.
  10. P. Lequeux & E. Acar, 1998. "A dynamic index for managed currencies funds using CME currency contracts," The European Journal of Finance, Taylor & Francis Journals, vol. 4(4), pages 311-330.

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