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More Evidence on the Nature of the Distribution of Security Returns

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  • Perry, Philip R.

Abstract

The question of whether security return distributions have a finite or an infinite variance has been debated for many years. The possibility that the security return-generating process actually has an infinite variance is particularly vexing since it implies that all statistical techniques and theoretical frameworks utilizing the second (or higher) moment are invalid. While this is clearly not a disaster—alternatives do exist—much of the work which has been done in the field of finance has assumed the existence of the second moment. It is, therefore, important to determine whether or not the security return distribution actually has a finite variance.

Suggested Citation

  • Perry, Philip R., 1983. "More Evidence on the Nature of the Distribution of Security Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 18(2), pages 211-221, June.
    • Handle: RePEc:cup:jfinqa:v:18:y:1983:i:02:p:211-221_01
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    Cited by:

    1. Hall, Joyce A. & Brorsen, B. Wade & Irwin, Scott H., 1989. "The Distribution of Futures Prices: A Test of the Stable Paretian and Mixture of Normals Hypotheses," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(1), pages 105-116, March.
    2. David Edelman & Thomas Gillespie, 2000. "The Stochastically Subordinated Poisson Normal Process for Modelling Financial Assets," Annals of Operations Research, Springer, vol. 100(1), pages 133-164, December.
    3. Christophe Ley & Anouk Neven, 2013. "Simple Le Cam Optimal Inference for the Tail Weight of Multivariate Student t Distributions: Testing Procedures and Estimation," Working Papers ECARES ECARES 2013-26, ULB -- Universite Libre de Bruxelles.
    4. Ata Türkoğlu, 2016. "Normally distributed high-frequency returns: a subordination approach," Quantitative Finance, Taylor & Francis Journals, vol. 16(3), pages 389-409, March.
    5. Gillemot, L. & Töyli, J. & Kertesz, J. & Kaski, K., 2000. "Time-independent models of asset returns revisited," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 282(1), pages 304-324.
    6. McCulloch, J. Huston & Percy, E. Richard, 2013. "Extended Neyman smooth goodness-of-fit tests, applied to competing heavy-tailed distributions," Journal of Econometrics, Elsevier, vol. 172(2), pages 275-282.
    7. Kullmann, L & Töyli, J & Kertesz, J & Kanto, A & Kaski, K, 1999. "Characteristic times in stock market indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 269(1), pages 98-110.
    8. López Martín, María del Mar & García, Catalina García & García Pérez, José, 2012. "Treatment of kurtosis in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(5), pages 2032-2045.

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