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Real-Time Trading Models and the Statistical Properties of Foreign Exchange Rates

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  • Ramazan GenÁay

    (University of Windsor, Canada)

  • Giuseppe Ballocchi

    (Olsen & Associates, Switzerland)

  • Michel Dacorogna

    (Converium, Switzerland)

  • Richard Olsen

    (Dynamic Asset Management, Switzerland)

  • Olivier Pictet

    (Dynamic Asset Management, Switzerland)

Abstract

The contributions of this article are twofold. First, the performance of a widely used commercial real-time trading model is compared with the performance of systematic currency traders. Second, the real-time trading model is used to evaluate the statistical properties of foreign exchange rates. The out-of-sample test period is seven years of high-frequency data for four major rates. The trading model yields positive annualized returns (net of transaction costs) in all cases. The null hypothesis of whether the real-time performances of the foreign exchange series are consistent with traditional statistical processes is tested under the probability distributions of the performance measures. Copyright Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association

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Bibliographic Info

Article provided by Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association in its journal International Economic Review.

Volume (Year): 43 (2002)
Issue (Month): 2 (May)
Pages: 463-492

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Handle: RePEc:ier:iecrev:v:43:y:2002:i:2:p:463-492

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Cited by:
  1. Stephan Schulmeister, 2005. "The Interaction between Technical Currency Trading and Exchange Rate Fluctuations," Finance, EconWPA 0512033, EconWPA.
  2. Ait-Sahalia, Yacine & Mykland, Per A. & Zhang, Lan, 2005. "Ultra high frequency volatility estimation with dependent microstructure noise," Discussion Paper Series 1: Economic Studies 2005,30, Deutsche Bundesbank, Research Centre.
  3. Nour Meddahi, 2000. "Temporal Aggregation of Volatility Models," Econometric Society World Congress 2000 Contributed Papers 1903, Econometric Society.
  4. Neely, C. J. & Weller, P. A., 2003. "Intraday technical trading in the foreign exchange market," Journal of International Money and Finance, Elsevier, Elsevier, vol. 22(2), pages 223-237, April.
  5. Walid Omrane & Hervé Oppens, 2006. "The performance analysis of chart patterns: Monte Carlo simulation and evidence from the euro/dollar foreign exchange market," Empirical Economics, Springer, Springer, vol. 30(4), pages 947-971, January.
  6. Fang, Jiali & Jacobsen, Ben & Qin, Yafeng, 2014. "Predictability of the simple technical trading rules: An out-of-sample test," Review of Financial Economics, Elsevier, Elsevier, vol. 23(1), pages 30-45.
  7. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers, Federal Reserve Bank of St. Louis 2011-001, Federal Reserve Bank of St. Louis.
  8. Yacine Ait-Sahalia & Jialin Yu, 2008. "High Frequency Market Microstructure Noise Estimates and Liquidity Measures," NBER Working Papers 13825, National Bureau of Economic Research, Inc.
  9. Manahov, Viktor & Hudson, Robert & Gebka, Bartosz, 2014. "Does high frequency trading affect technical analysis and market efficiency? And if so, how?," Journal of International Financial Markets, Institutions and Money, Elsevier, Elsevier, vol. 28(C), pages 131-157.

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