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Application of Simple Technical Trading Rules to Swiss Stock Prices: Is it Profitable?

Author

Listed:
  • Dušan ISAKOV

    (HEC-Université de Genève)

  • Marc HOLLISTEIN

    (Banque Cantonale de Genève)

Abstract

This paper tests if the use of simple technical trading rules on Swiss stock prices is profitable. It considers several trading rules based on the crossing of moving averages. The use of bands and oscillators such as the relative strength index or the stochastic indicator is also investigated. These rules are tested on daily returns of the Swiss Bank Corporation General Index for the period 1969-1997. It is found that the most profitable rule is a double moving average with averages computed on one and five days. With this rule, an annual average return on the SBC Index of 24.30% is obtained compared to a buy-and-hold annual return of 6.25%. These results are confirmed by bootstrap simulations which consider different return generating processes as the AR(1) model and the GARCH(1,1) model. Similar results are obtained for individual stocks. In the presence of trading costs, these rules are only profitable for a particular kind of investor.

Suggested Citation

  • Dušan ISAKOV & Marc HOLLISTEIN, 1999. "Application of Simple Technical Trading Rules to Swiss Stock Prices: Is it Profitable?," FAME Research Paper Series rp2, International Center for Financial Asset Management and Engineering.
  • Handle: RePEc:fam:rpseri:rp2
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    File URL: http://www.swissfinanceinstitute.ch/rp2.pdf
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    Cited by:

    1. Roy L. Hayes & Jingwei Wu & Ruijra Chaysiri & Jean Bae & Peter A. Beling & William T. Scherer, 2016. "Effects of time horizon and asset condition on the profitability of technical trading rules," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 40(1), pages 41-59, January.
    2. Wang, Zi-Mei & Chiao, Chaoshin & Chang, Ya-Ting, 2012. "Technical analyses and order submission behaviors: Evidence from an emerging market," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 109-128.
    3. Michael McAleer & John Suen & Wing Keung Wong, 2016. "Profiteering from the Dot-Com Bubble, Subprime Crisis and Asian Financial Crisis," The Japanese Economic Review, Japanese Economic Association, vol. 67(3), pages 257-279, September.
    4. Ratner, Mitchell & Leal, Ricardo P. C., 1999. "Tests of technical trading strategies in the emerging equity markets of Latin America and Asia," Journal of Banking & Finance, Elsevier, vol. 23(12), pages 1887-1905, December.
    5. Roy Hayes & Jingwei Wu & Ruijra Chaysiri & Jean Bae & Peter Beling & William Scherer, 2016. "Effects of time horizon and asset condition on the profitability of technical trading rules," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 40(1), pages 41-59, January.
    6. William Cheung & Keith Lam & HangFai Yeung, 2011. "Intertemporal profitability and the stability of technical analysis: evidences from the Hong Kong stock exchange," Applied Economics, Taylor & Francis Journals, vol. 43(15), pages 1945-1963.
    7. Yochanan Shachmurove & Uri BenZion & Paul Klein & Joseph Yagil, 2001. "A Moving Average Comparison of the Tel-Aviv 25 and S&P 500 Stock Indices," Penn CARESS Working Papers 4731f3394c43bebf4d3191c81, Penn Economics Department.

    More about this item

    Keywords

    Moving average; investment strategy; technical analysis; bootstrap;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G19 - Financial Economics - - General Financial Markets - - - Other

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