IDEAS home Printed from https://ideas.repec.org/a/ier/iecrev/v43y2002i2p463-492.html
   My bibliography  Save this article

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

Author

Listed:
  • 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

Suggested Citation

  • Ramazan GenÁay & Giuseppe Ballocchi & Michel Dacorogna & Richard Olsen & Olivier Pictet, 2002. "Real-Time Trading Models and the Statistical Properties of Foreign Exchange Rates," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(2), pages 463-492, May.
  • Handle: RePEc:ier:iecrev:v:43:y:2002:i:2:p:463-492
    as

    Download full text from publisher

    File URL: http://openurl.ingenta.com/content?genre=article&issn=0020-6598&volume=43&spage=463
    Download Restriction: Free access to full text is restricted to Ingenta subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Neely, C. J. & Weller, P. A., 2003. "Intraday technical trading in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 22(2), pages 223-237, April.
    2. Schulmeister, Stephan, 2006. "The interaction between technical currency trading and exchange rate fluctuations," Finance Research Letters, Elsevier, vol. 3(3), pages 212-233, September.
    3. Bekiros, Stelios D., 2015. "Heuristic learning in intraday trading under uncertainty," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 34-49.
    4. Aït-Sahalia, Yacine & Mykland, Per A. & Zhang, Lan, 2011. "Ultra high frequency volatility estimation with dependent microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 160-175, January.
    5. Meddahi, Nour & Renault, Eric, 2004. "Temporal aggregation of volatility models," Journal of Econometrics, Elsevier, vol. 119(2), pages 355-379, April.
    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, vol. 23(1), pages 30-45.
    7. 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, vol. 30(4), pages 947-971, January.
    8. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers 2011-001, Federal Reserve Bank of St. Louis.
    9. Narayan, Paresh Kumar & Mishra, Sagarika & Narayan, Seema & Thuraisamy, Kannan, 2015. "Is Exchange Rate Trading Profitable?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 217-229.
    10. Ni, Yensen & Liao, Yi-Ching & Huang, Paoyu, 2015. "MA trading rules, herding behaviors, and stock market overreaction," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 253-265.
    11. Selçuk, Faruk & Gençay, Ramazan, 2006. "Intraday dynamics of stock market returns and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 375-387.
    12. 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.
    13. 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, vol. 28(C), pages 131-157.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ier:iecrev:v:43:y:2002:i:2:p:463-492. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (). General contact details of provider: http://edirc.repec.org/data/deupaus.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.