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Functional Statistics and Related Fields pp 59–65Cite as

On the Geometric Brownian Motion assumption for financial time series

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Part of the book series: Contributions to Statistics ((CONTRIB.STAT.))

Abstract

The Geometric Brownian Motion type process is commonly used to describe stock price movements and is basic for many option pricing models. In this paper a new methodology for recognizing Brownian functionals is applied to financial datasets in order to evaluate the compatibility between real financial data and the above modeling assumption. The method rests on using the volumetric term which appears in the factorization of the small–ball probability of a random curve.

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References

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Author information

Authors and Affiliations

  1. Dipartimento di Studi per l’Economia e l’Impresa, Università del Piemonte Orientale, Vercelli, Italy

    Enea G. Bongiorno & Aldo Goia

  2. Institut de Mathématiques de Toulouse, Université Paul Sabatier, Toulouse, France

    Philippe Vieu

Authors
  1. Enea G. Bongiorno
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  2. Aldo Goia
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  3. Philippe Vieu
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Corresponding author

Correspondence to Aldo Goia .

Editor information

Editors and Affiliations

  1. Dept. of Mathematics, University of A Coruña, A Coruña, Spain

    Germán Aneiros

  2. Dept. of Studies in Econ.and Business, University of Eastern Piedmont "Amedeo Avogadro", Novara, Italy

    Enea G. Bongiorno

  3. Dept. of Mathematics, University of A Coruña, A Coruña, Spain

    Ricardo Cao

  4. Toulouse Mathematics Institute (IMT), Paul Sabatier University, Toulouse, France

    Philippe Vieu

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Bongiorno, E.G., Goia, A., Vieu, P. (2017). On the Geometric Brownian Motion assumption for financial time series. In: Aneiros, G., G. Bongiorno, E., Cao, R., Vieu, P. (eds) Functional Statistics and Related Fields. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-55846-2_9

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