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Algorithmic complexity of financial motions

Author

Listed:
  • O. Brandouy
  • Lin Ma

    (LEM - Lille - Economie et Management - Université de Lille, Sciences et Technologies - CNRS - Centre National de la Recherche Scientifique)

  • Hector Zenil
  • Jean-Paul Delahaye

    (SMAC - Systèmes Multi-Agents et Comportements - CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 - Centrale Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique, LIFL - Laboratoire d'Informatique Fondamentale de Lille - Université de Lille, Sciences et Technologies - Inria - Institut National de Recherche en Informatique et en Automatique - Université de Lille, Sciences Humaines et Sociales - CNRS - Centre National de la Recherche Scientifique)

Abstract

We survey the main applications of algorithmic (Kolmogorov) complexity to the problem of price dynamics in financial markets. We stress the differences between these works and put forward a general algorithmic framework in order to highlight its potential for financial data analysis. This framework is “general” in the sense that it is not constructed on the common assumption that price variations are predominantly stochastic in nature.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • O. Brandouy & Lin Ma & Hector Zenil & Jean-Paul Delahaye, 2012. "Algorithmic complexity of financial motions," Post-Print hal-00802537, HAL.
    • Handle: RePEc:hal:journl:hal-00802537
    DOI: 10.1016/j.ribaf.2012.08.001
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    References listed on IDEAS

    as
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    Cited by:

    1. Fernando Soler-Toscano & Hector Zenil & Jean-Paul Delahaye & Nicolas Gauvrit, 2014. "Calculating Kolmogorov Complexity from the Output Frequency Distributions of Small Turing Machines," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-18, May.
    2. Brandouy, Olivier & Delahaye, Jean-Paul & Ma, Lin & Zenil, Hector, 2014. "Algorithmic complexity of financial motions," Research in International Business and Finance, Elsevier, vol. 30(C), pages 336-347.
    3. Daniel Wilson-Nunn & Hector Zenil, 2014. "On the Complexity and Behaviour of Cryptocurrencies Compared to Other Markets," Papers 1411.1924, arXiv.org.
    4. Serbera, Jean-Philippe & Paumard, Pascal, 2016. "The fall of high-frequency trading: A survey of competition and profits," Research in International Business and Finance, Elsevier, vol. 36(C), pages 271-287.

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    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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