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Financial Data

In: The Laplace Distribution and Generalizations

Author

Listed:
  • Samuel Kotz

    (George Washington University, Department of Engineering Management and Systems Engineering)

  • Tomaz J. Kozubowski

    (University of Nevada, Department of Mathematics)

  • Krzysztof Podgórski

    (Indiana University—Purdue University, Department of Mathematical Sciences)

Abstract

An area where the Laplace and related distributions can find most interesting and successful applications is modeling of financial data. This is due to the fact that traditional models based on Gaussian distribution are very often not supported by real-life data because of long tails and asymmetry present in these data. Since Laplace distributions can account for leptokurtic and skewed data they are natural candidates to replace Gaussian models and processes. In fact, some activity involving the Laplace distribution can already be observed in this area. Laplace motion and models based on multivariate Laplace laws have appeared in works on modeling stock market returns, currency exchange rates, and interest rates. In this chapter, we present several such applications.

Suggested Citation

  • Samuel Kotz & Tomaz J. Kozubowski & Krzysztof Podgórski, 2001. "Financial Data," Springer Books, in: The Laplace Distribution and Generalizations, chapter 8, pages 289-302, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4612-0173-1_10
    DOI: 10.1007/978-1-4612-0173-1_10
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