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The benefit of information reduction for trading strategies

Author

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  • Christian Schittenkopf
  • Peter Tino
  • Georg Dorffner

Abstract

Motivated by previous findings that discretization of financial time series can effectively filter the data and reduce the noise, this experimental study compares the trading performance of predictive models based on different modelling paradigms in a realistic setting. Different methods ranging from real-valued time series models to predictive models on a symbolic level are applied to predict the daily change in volatility of two major stock indices. The predicted volatility changes are interpreted as trading signals for buying or selling a straddle portfolio on the underlying stock index. Profits realized by this trading strategy are tested for statistical significance taking into account transactions costs. The results indicate that symbolic information processing is a promising approach to financial prediction tasks undermining the hypothesis of efficient capital markets.

Suggested Citation

  • Christian Schittenkopf & Peter Tino & Georg Dorffner, 2002. "The benefit of information reduction for trading strategies," Applied Economics, Taylor & Francis Journals, vol. 34(7), pages 917-930.
    • Handle: RePEc:taf:applec:v:34:y:2002:i:7:p:917-930
    DOI: 10.1080/00036840110061938
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    References listed on IDEAS

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    1. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 1999. "The Distribution of Exchange Rate Volatility," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-059, New York University, Leonard N. Stern School of Business-.
    2. Schmitt, Christian & Kaehler, Jürgen, 1996. "Delta-neutral volatility trading with intra-day prices: an application to options on the DAX," ZEW Discussion Papers 96-25, ZEW - Leibniz Centre for European Economic Research.
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    Cited by:

    1. Miguel Henry & George Judge, 2019. "Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time Series," Econometrics, MDPI, vol. 7(1), pages 1-16, March.
    2. Risso, Wiston Adrián, 2008. "The informational efficiency and the financial crashes," Research in International Business and Finance, Elsevier, vol. 22(3), pages 396-408, September.

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