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A Model for Stock Return Distribution

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  • Linden, Mikael

Abstract

The Laplace mixture distribution for stock share returns is derived from conditional N(0, sigma-squared) distribution. The conditioning variable, sigma-squared, is assumed to be an exponentially distributed random variable. This offers a natural stochastic interpretation of the risk involved with the stock share. Maximum likelihood (ML) estimates for returns of the 20 most traded shares and the aggregate index of the Helsinki stock market in late 1980s do not reject the Laplace distribution model. The results extend to returns over longer periods than 1 day. Copyright @ 2001 by John Wiley & Sons, Ltd. All rights reserved.

Suggested Citation

  • Linden, Mikael, 2001. "A Model for Stock Return Distribution," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 6(2), pages 159-169, April.
    • Handle: RePEc:ijf:ijfiec:v:6:y:2001:i:2:p:159-69
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    Cited by:

    1. Rodríguez, Mª Araceli, 2005. "Nueva Evidencia Empírica sobre las Turbulencias Cambiarias de la Peseta Española. 1989-1998/New Evidence about Turbulences on the Spanish Peseta. 1989-1998s," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 23, pages 207-230, Abril.
    2. Xuan Vinh Vo & Thi Tuan Anh Tran, 2021. "Higher-order comoments and asset returns: evidence from emerging equity markets," Annals of Operations Research, Springer, vol. 297(1), pages 323-340, February.
    3. K Autchariyapanitkul & S Chanaim & S Sriboonchitta & T Denoeux, 2014. "Predicting Stock Returns in the Capital Asset Pricing Model Using Quantile Regression and Belief Functions," Post-Print hal-01127790, HAL.
    4. Miguel Ángel Sánchez & Juan E Trinidad & José García & Manuel Fernández, 2015. "The Effect of the Underlying Distribution in Hurst Exponent Estimation," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-17, May.
    5. Markus Haas & Stefan Mittnik & Marc Paolella, 2006. "Modelling and predicting market risk with Laplace-Gaussian mixture distributions," Applied Financial Economics, Taylor & Francis Journals, vol. 16(15), pages 1145-1162.
    6. Stephen Chan & Jeffrey Chu & Saralees Nadarajah & Joerg Osterrieder, 2017. "A Statistical Analysis of Cryptocurrencies," JRFM, MDPI, vol. 10(2), pages 1-23, May.
    7. Chen, Shengming & Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023. "The Russia–Ukraine war and energy market volatility: A novel application of the volatility ratio in the context of natural gas," Resources Policy, Elsevier, vol. 85(PA).
    8. Marcin Wk{a}torek & Jaros{l}aw Kwapie'n & Stanis{l}aw Dro.zd.z, 2021. "Financial Return Distributions: Past, Present, and COVID-19," Papers 2107.06659, arXiv.org.
    9. Roch, Oriol & Alegre, Antonio, 2006. "Testing the bivariate distribution of daily equity returns using copulas. An application to the Spanish stock market," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1312-1329, November.
    10. Pär Stockhammar & Lars-Erik Öller, 2011. "On the probability distribution of economic growth," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(9), pages 2023-2041, November.
    11. Yan, Hanhuan & Han, Liyan, 2019. "Empirical distributions of stock returns: Mixed normal or kernel density?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 473-486.
    12. Saralees Nadarajah, 2012. "Models for stock returns," Quantitative Finance, Taylor & Francis Journals, vol. 12(3), pages 411-424, February.
    13. Naumoski, Aleksandar & Gaber, Stevan & Gaber-Naumoska, Vasilka, 2017. "Empirical Distribution Of Stock Returns Of Southeast European Emerging Markets," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 8(2), pages 67-77.
    14. Tomasz Kozubowski & Saralees Nadarajah, 2010. "Multitude of Laplace distributions," Statistical Papers, Springer, vol. 51(1), pages 127-148, January.
    15. Gel, Yulia R., 2010. "Test of fit for a Laplace distribution against heavier tailed alternatives," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 958-965, April.
    16. Saralees Nadarajah, 2009. "Laplace random variables with application to price indices," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 93(3), pages 345-369, September.
    17. Kaldasch, Joachim, 2014. "Evolutionary model of stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 449-462.
    18. Mahmood Ul Hassan & Pär Stockhammar, 2016. "Fitting probability distributions to economic growth: a maximum likelihood approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(9), pages 1583-1603, July.
    19. Higbee, Joshua D. & McDonald, James B., 2024. "A comparison of the GB2 and skewed generalized log-t distributions with an application in finance," Journal of Econometrics, Elsevier, vol. 240(2).
    20. John Douglas (J.D.) Opdyke, 2007. "Comparing Sharpe ratios: So where are the p-values?," Journal of Asset Management, Palgrave Macmillan, vol. 8(5), pages 308-336, December.
    21. Oriol Roch Casellas & Antonio Alegre Escolano, 2005. "Testing the bivariate distribution of daily equity returns using copulas. An application to the Spanish stock market," Working Papers in Economics 143, Universitat de Barcelona. Espai de Recerca en Economia.
    22. 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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