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The string prediction models as an invariants of time series in forex market

Listed author(s):
  • Richard Pincak
  • Marian Repasan
Registered author(s):

    In this paper we apply a new approach of the string theory to the real financial market. It is direct extension and application of the work [1] into prediction of prices. The models are constructed with an idea of prediction models based on the string invariants (PMBSI). The performance of PMBSI is compared to support vector machines (SVM) and artificial neural networks (ANN) on an artificial and a financial time series. Brief overview of the results and analysis is given. The first model is based on the correlation function as invariant and the second one is an application based on the deviations from the closed string/pattern form (PMBCS). We found the difference between these two approaches. The first model cannot predict the behavior of the forex market with good efficiency in comparison with the second one which is, in addition, able to make relevant profit per year.

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    Paper provided by in its series Papers with number 1109.0435.

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    Date of creation: Sep 2011
    Date of revision: Oct 2012
    Publication status: Published in Physica A 392 (2013) 6414-6426
    Handle: RePEc:arx:papers:1109.0435
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