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The Distribution of Stock Returns: New Evidence against the Stable Model

Citations

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Cited by:

  1. Lakshman A. Alles & John L. Kling, 1994. "Regularities In The Variation Of Skewness In Asset Returns," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 17(3), pages 427-438, September.
  2. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.
  3. Jungjun Choi & In Choi, 2019. "Maximum likelihood estimation of autoregressive models with a near unit root and Cauchy errors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(5), pages 1121-1142, October.
  4. Errunza, Vihang & Hogan, Kedreth Jr. & Mazumdar, Sumon C., 1996. "Behavior of international stock return distributions: A simple test of functional form," International Review of Economics & Finance, Elsevier, vol. 5(1), pages 51-61.
  5. J. Ignacio Peña, 1992. "On meteor showers in stock markets: New York vs Madrid," Investigaciones Economicas, Fundación SEPI, vol. 16(2), pages 225-234, May.
  6. Goddard, John & Onali, Enrico, 2012. "Self-affinity in financial asset returns," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 1-11.
  7. 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.
  8. Daniel Fricke & Thomas Lux, 2015. "On the distribution of links in the interbank network: evidence from the e-MID overnight money market," Empirical Economics, Springer, vol. 49(4), pages 1463-1495, December.
  9. J. Francisco Rubio & Neal Maroney & M. Kabir Hassan, 2018. "Can Efficiency of Returns Be Considered as a Pricing Factor?," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 25-54, June.
  10. Kaehler, Jürgen, 1993. "On the modelling of speculative prices by stable Paretian distributions and regularly varying tails," ZEW Discussion Papers 93-25, ZEW - Leibniz Centre for European Economic Research.
  11. D. M. Mahinda Samarakoon & Keith Knight, 2009. "A Note on Unit Root Tests with Infinite Variance Noise," Econometric Reviews, Taylor & Francis Journals, vol. 28(4), pages 314-334.
  12. Fabio Pizzutilo, 2013. "The Distribution of the Returns of Japanese Stocks and Portfolios," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 3(9), pages 1249-1259, September.
  13. Srilakshminarayana G, 2021. "Tail Behaviour of the Nifty-50 Stocks during Crises Periods," Advances in Decision Sciences, Asia University, Taiwan, vol. 25(4), pages 115-151, December.
  14. Lau, Hon-Shiang & Lau, Amy Hing Ling, 1997. "The confounding effects of distribution mixtures on some basic methods for handling stable-Paretian distributions," European Journal of Operational Research, Elsevier, vol. 100(1), pages 60-71, July.
  15. 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.
  16. Ioannis A. Tampakoudis & Demetres N. Subeniotis & Ioannis G. Kroustalis, 2012. "Modelling volatility during the current financial crisis: an empirical analysis of the US and the UK stock markets," International Journal of Trade and Global Markets, Inderscience Enterprises Ltd, vol. 5(3/4), pages 171-194.
  17. Tsionas, Efthymios G., 1998. "Monte Carlo inference in econometric models with symmetric stable disturbances," Journal of Econometrics, Elsevier, vol. 88(2), pages 365-401, November.
  18. Lux, Thomas, 2006. "Financial power laws: Empirical evidence, models, and mechanism," Economics Working Papers 2006-12, Christian-Albrechts-University of Kiel, Department of Economics.
  19. Paolella, Marc S., 2017. "Asymmetric stable Paretian distribution testing," Econometrics and Statistics, Elsevier, vol. 1(C), pages 19-39.
  20. Grobys, Klaus, 2023. "Correlation versus co-fractality: Evidence from foreign-exchange-rate variances," International Review of Financial Analysis, Elsevier, vol. 86(C).
  21. 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.
  22. Lau, Hon-Shiang & Lau, Amy Hing-Ling & Kottas, John F., 2000. "A comparison of procedures for estimating the parent probability distribution from a given set of fractiles," European Journal of Operational Research, Elsevier, vol. 120(3), pages 657-670, February.
  23. Joro, Tarja & Na, Paul, 2006. "Portfolio performance evaluation in a mean-variance-skewness framework," European Journal of Operational Research, Elsevier, vol. 175(1), pages 446-461, November.
  24. Richard Harris & C. Coskun Kucukozmen & Fatih Yilmaz, 2004. "Skewness in the conditional distribution of daily equity returns," Applied Financial Economics, Taylor & Francis Journals, vol. 14(3), pages 195-202.
  25. M. F. Omran, 1998. "An investigation of the maximal moments of exchange rates," Applied Economics Letters, Taylor & Francis Journals, vol. 5(10), pages 603-606.
  26. Kaehler, Jürgen & Marnet, Volker, 1993. "Markov-switching models for exchange-rate dynamics and the pricing of foreign-currency options," ZEW Discussion Papers 93-03, ZEW - Leibniz Centre for European Economic Research.
  27. Hon-Shiang Lau & Amy Hing-Ling Lau & Chrwan-Jyh Ho, 1998. "Improved Moment-Estimation Formulas Using More Than Three Subjective Fractiles," Management Science, INFORMS, vol. 44(3), pages 346-351, March.
  28. Hans Dillen & Bo Stoltz, 1999. "The distribution of stock market returns and the market model," Finnish Economic Papers, Finnish Economic Association, vol. 12(1), pages 41-56, Spring.
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