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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. Nelson Mark & Yangru Wu, 1998. "Rethinking Deviations from Uncovered Interest Parity: The Role of Covariance Risk and Noise," Working Papers 98-05, Ohio State University, Department of Economics.
  2. Balvers, Ronald & Wu, Yangru, 2010. "Optimal transaction filters under transitory trading opportunities: Theory and empirical illustration," Journal of Financial Markets, Elsevier, vol. 13(1), pages 129-156, February.
  3. 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.
  4. 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.
  5. Dueker, Michael & Neely, Christopher J., 2007. "Can Markov switching models predict excess foreign exchange returns?," Journal of Banking & Finance, Elsevier, vol. 31(2), pages 279-296, February.
  6. 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.
  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. 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.
  9. Spyros Skouras, 1998. "Financial Returns and Efficiency as seen by an Artificial Technical Analyst," Finance 9808001, EconWPA, revised 24 Aug 1998.
  10. 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.

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