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Determinism in Financial Time Series


  • Small Michael

    () (Hong Kong Polytechnic University)

  • Tse Chi K.

    (Hong Kong Polytechnic University)


The attractive possibility that financial indices may be chaotic has been the subject of much study. In this paper we address two specific questions: "Masked by stochasticity, do financial data exhibit deterministic nonlinearity?", and "If so, so what?". We examine daily returns from three financial indicators: the Dow Jones Industrial Average, the London gold fixings, and the USD-JPY exchange rate. For each data set we apply surrogate data methods and nonlinearity tests to quantify determinism over a wide range of time scales (from 100 to 20,000 days). We find that all three time series are distinct from linear noise or conditional heteroskedastic models and that there therefore exists detectable deterministic nonlinearity that can potentially be exploited for prediction.

Suggested Citation

  • Small Michael & Tse Chi K., 2003. "Determinism in Financial Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(3), pages 1-31, October.
  • Handle: RePEc:bpj:sndecm:v:7:y:2003:i:3:n:5

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    References listed on IDEAS

    1. Joseph L. McCauley, 1999. "The Futility of Utility: how market dynamics marginalize Adam Smith," Papers cond-mat/9911291,, revised Feb 2000.
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    5. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
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    7. Darbellay, Georges A & Wuertz, Diethelm, 2000. "The entropy as a tool for analysing statistical dependences in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 429-439.
    8. McCauley, Joseph L., 2000. "The futility of utility: how market dynamics marginalize Adam Smith," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 285(3), pages 506-538.
    9. Crack, Timothy Falcon & Ledoit, Olivier, 1996. " Robust Structure without Predictability: The "Compass Rose" Pattern of the Stock Market," Journal of Finance, American Finance Association, vol. 51(2), pages 751-762, June.
    10. Agnon, Yehuda & Golan, Amos & Shearer, Matthew, 1999. "Nonparametric, nonlinear, short-term forecasting: theory and evidence for nonlinearities in the commodity markets," Economics Letters, Elsevier, vol. 65(3), pages 293-299, December.
    11. James Theiler & Stephen Eubank, 1993. "Don't Bleach Chaotic Data," Working Papers 93-05-026, Santa Fe Institute.
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    Cited by:

    1. Webel, Karsten, 2012. "Chaos in German stock returns — New evidence from the 0–1 test," Economics Letters, Elsevier, vol. 115(3), pages 487-489.
    2. Leontitsis, Alexandros & Vorlow, Constantinos E., 2006. "Accounting for outliers and calendar effects in surrogate simulations of stock return sequences," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 368(2), pages 522-530.

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