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A Reexamination of Finite- and Infinite-Variance Distributions as Models of Daily Stock Returns

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  • Tucker, Alan L

Abstract

This study investigates the general (asymmetric) stable Paretian distribution and three finite-variance, time-independent distributions applied to daily stock-return series. Previous empirical comparisons have, in general, ignored the existence and effects of skewness on the process parameters of stable laws. The results of log-likelihood ratio and log-odds tests indicate that finite-variance models still dominate after accounting for documented skewness. In particular, the mixed diffusion-jump and compound normal models appear to be the most descriptive time-independent models.

Suggested Citation

  • Tucker, Alan L, 1992. "A Reexamination of Finite- and Infinite-Variance Distributions as Models of Daily Stock Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(1), pages 73-81, January.
    • Handle: RePEc:bes:jnlbes:v:10:y:1992:i:1:p:73-81
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    Cited by:

    1. Natalia Khorunzhina & Jean-François Richard, 2019. "Finite Gaussian Mixture Approximations to Analytically Intractable Density Kernels," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 991-1017, March.
    2. Debabrata Mukhopadhyay & Nityananda Sarkar, 2013. "Stock Returns Under Alternative Volatility and Distributional Assumptions: The Case for India," International Econometric Review (IER), Econometric Research Association, vol. 5(1), pages 1-19, April.
    3. Jondeau, E. & Rockinger, M., 1999. "The Tail Behavior of Sotck Returns: Emerging Versus Mature Markets," Working papers 66, Banque de France.
    4. Wai Mun Fong, 1997. "Robust beta estimation: Some empirical evidence," Review of Financial Economics, John Wiley & Sons, vol. 6(2), pages 167-186.
    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. Xu, Yang & Han, Liyan & Wan, Li & Yin, Libo, 2019. "Dynamic link between oil prices and exchange rates: A non-linear approach," Energy Economics, Elsevier, vol. 84(C).
    7. Rui Albuquerque, 2012. "Skewness in Stock Returns: Reconciling the Evidence on Firm Versus Aggregate Returns," The Review of Financial Studies, Society for Financial Studies, vol. 25(5), pages 1630-1673.
    8. K. D. Patterson & S. M. Heravi, 2003. "The impact of fat-tailed distributions on some leading unit roots tests," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(6), pages 635-667.
    9. Tian, Yisong Sam, 1998. "A Trinomial Option Pricing Model Dependent on Skewness and Kurtosis," International Review of Economics & Finance, Elsevier, vol. 7(3), pages 315-330.
    10. Wan, Li & Han, Liyan & Xu, Yang & Matousek, Roman, 2021. "Dynamic linkage between the Chinese and global stock markets: A normal mixture approach," Emerging Markets Review, Elsevier, vol. 49(C).
    11. Henri Bertholon & Alain Monfort & Fulvio Pegoraro, 2006. "Pricing and Inference with Mixtures of Conditionally Normal Processes," Working Papers 2006-28, Center for Research in Economics and Statistics.
    12. Fong, Wai Mun, 1997. "Robust beta estimation: Some empirical evidence," Review of Financial Economics, Elsevier, vol. 6(2), pages 167-186.
    13. Nawrocki, David N., 1995. "Expectations, technological change, information and the theory of financial markets," International Review of Financial Analysis, Elsevier, vol. 4(2-3), pages 85-105.
    14. Bhattacharyya, Malay & Madhav R, Siddarth, 2012. "A Comparison of VaR Estimation Procedures for Leptokurtic Equity Index Returns," MPRA Paper 54189, University Library of Munich, Germany.
    15. Victor DeMiguel & Francisco J. Nogales, 2009. "Portfolio Selection with Robust Estimation," Operations Research, INFORMS, vol. 57(3), pages 560-577, June.
    16. Greg Hannsgen, 2011. "Infinite-variance, Alpha-stable Shocks in Monetary SVAR: Final Working Paper Version," Economics Working Paper Archive wp_682, Levy Economics Institute.
    17. Meintanis, Simos G. & Tsionas, Efthimios, 2010. "Testing for the generalized normal-Laplace distribution with applications," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3174-3180, December.
    18. Michael C. Fu & Bingqing Li & Guozhen Li & Rongwen Wu, 2017. "Option Pricing for a Jump-Diffusion Model with General Discrete Jump-Size Distributions," Management Science, INFORMS, vol. 63(11), pages 3961-3977, November.
    19. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    20. Klar, Bernhard & Meintanis, Simos G., 2005. "Tests for normal mixtures based on the empirical characteristic function," Computational Statistics & Data Analysis, Elsevier, vol. 49(1), pages 227-242, April.
    21. 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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