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Algorithmic complexity of financial motions

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  • Brandouy, Olivier
  • Delahaye, Jean-Paul
  • Ma, Lin
  • Zenil, Hector
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    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.

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    Bibliographic Info

    Article provided by Elsevier in its journal Research in International Business and Finance.

    Volume (Year): 30 (2014)
    Issue (Month): C ()
    Pages: 336-347

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    Handle: RePEc:eee:riibaf:v:30:y:2014:i:c:p:336-347

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    Web page: http://www.elsevier.com/locate/ribaf

    Related research

    Keywords: Algorithmic information theory; Kolmogorov complexity; Financial returns; Market efficiency; Compression algorithms; Information theory; randomness; Price movements; Algorithmic probability;

    References

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    1. A. Dionisio & R. Menezes & D. A. Mendes, 2006. "An econophysics approach to analyse uncertainty in financial markets: an application to the Portuguese stock market," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, vol. 50(1), pages 161-164, 03.
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    6. Mansilla, R., 2001. "Algorithmic complexity of real financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 301(1), pages 483-492.
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