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Technical Trading Revisited: False Discoveries, Persistence Tests, and Transaction Costs

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Author Info

  • Pierre Bajgrowicz

    (University of Geneva)

  • Olivier Scaillet

    (University of Geneva and Swiss Finance Institute)

Abstract

We revisit the apparent historical success of technical trading rules on daily prices of the DJIA from 1897 to 2008. We use the False Discovery Rate as a new approach to data snooping. The advantage of the FDR over existing methods is that it selects more outperforming rules and di- versi es against model uncertainty. Persistence tests show that an investor would never have been able to select ex ante the future best-performing rules. Moreover, even the in-sample performance is completely o set by the introduction of transaction costs. Overall, our results seriously call into question the economic value of technical trading rules.

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Bibliographic Info

Paper provided by Swiss Finance Institute in its series Swiss Finance Institute Research Paper Series with number 08-05.

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Length: 57 pages
Date of creation: May 2007
Date of revision: Jul 2009
Handle: RePEc:chf:rpseri:rp0805

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Web page: http://www.SwissFinanceInstitute.ch
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Keywords: Technical Trading; False Discovery Rate; Persistence; Transaction Costs.;

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Cited by:
  1. David Ardia & Kris Boudt, 2013. "The Peer Performance of Hedge Funds," Cahiers de recherche 1329, CIRPEE.
  2. 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.
  3. Dan Anghel, 2013. "How Reliable is the Moving Average Crossover Rule for an Investor on the Romanian Stock Market?," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 5(2), pages 089-115, December.
  4. Aitken, Michael & Cumming, Douglas & Zhan, Feng, 2013. "High frequency trading and end-of-day price dislocation," CFS Working Paper Series 2013/16, Center for Financial Studies (CFS).

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