IDEAS home Printed from https://ideas.repec.org/p/vnm/wpaper/145.html
   My bibliography  Save this paper

Simulation techniques for generalized Gaussian densities

Author

Listed:
  • Martina Nardon

    (Department of Applied Mathematics, University of Venice)

  • Paolo Pianca

    (Department of Applied Mathematics, University of Venice)

Abstract

This contribution deals with Monte Carlo simulation of generalized Gaussian random variables. Such a parametric family of distributions has been proposed in many applications in science to describe physical phenomena and in engineering, and it seems also useful in modeling economic and financial data. For values of the shape parameter a within a certain range, the distribution presents heavy tails. In particular, the cases a=1/3 and a=1/2 are considered. For such values of the shape parameter, different simulation methods are assessed.

Suggested Citation

  • Martina Nardon & Paolo Pianca, 2006. "Simulation techniques for generalized Gaussian densities," Working Papers 145, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    • Handle: RePEc:vnm:wpaper:145
    as

    Download full text from publisher

    File URL: http://virgo.unive.it/wpideas/storage/2006wp145.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Olivier V. Pictet & Michel M. Dacorogna & Ulrich A. Muller, 1996. "Heavy tails in high-frequency financial data," Working Papers 1996-12-11, Olsen and Associates.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sebastiano Michele Zema, 2020. "Directed Acyclic Graph based Information Shares for Price Discovery," LEM Papers Series 2020/28, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nuyts, Jean & Platten, Isabelle, 2001. "Phenomenology of the term structure of interest rates with Padé Approximants," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(3), pages 528-546.
    2. J. Doyne Farmer, 2000. "Physicists Attempt To Scale The Ivory Towers Of Finance," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(03), pages 311-333.
    3. Ibrahim Onour, "undated". "Extreme Risk and Fat-tails Distribution Model:Empirical Analysis," API-Working Paper Series 0911, Arab Planning Institute - Kuwait, Information Center.
    4. Weshah Razzak, "undated". "On the GCC Currency Union," API-Working Paper Series 0910, Arab Planning Institute - Kuwait, Information Center.
    5. Dr. Ibrahim Onour, "undated". "The Global Financial Crisis and Equity Markets in Middle East Oil Exporting Countries," API-Working Paper Series 1009, Arab Planning Institute - Kuwait, Information Center.
    6. Pierre Giot, 2005. "Market risk models for intraday data," The European Journal of Finance, Taylor & Francis Journals, vol. 11(4), pages 309-324.
    7. Sayantan Ghosh & P. Manimaran & Prasanta K. Panigrahi, 2010. "Characterizing Multi-Scale Self-Similar Behavior and Non-Statistical Properties of Financial Time Series," Papers 1003.2539, arXiv.org, revised Dec 2010.
    8. Mora Galán, Alberto & Pérez, Ana & Ruiz Ortega, Esther, 2004. "Stochastic volatility models and the Taylor effect," DES - Working Papers. Statistics and Econometrics. WS ws046315, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Alan Collins & Chris Hand & Martin C. Snell, 2002. "What makes a blockbuster? Economic analysis of film success in the United Kingdom," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 23(6), pages 343-354.

    More about this item

    Keywords

    Generalized Gaussian density; heavy tails; transformations of rendom variables; Monte Carlo simulation; Lambert W function;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vnm:wpaper:145. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Marco LiCalzi (email available below). General contact details of provider: https://edirc.repec.org/data/dmvenit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.