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Testing asymmetry in financial time series

Author

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  • Francesco Lisi

Abstract

This paper examines the problem of evaluating the presence of asymmetry in the marginal distribution of financial returns by means of a suitable statistical test. After a brief description of existing tests, a bootstrap procedure is proposed. A Monte Carlo study showed that this test works properly and that, in terms of power, it is competitive with existing tests. An application to real financial time series is also presented.

Suggested Citation

  • Francesco Lisi, 2007. "Testing asymmetry in financial time series," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 687-696.
  • Handle: RePEc:taf:quantf:v:7:y:2007:i:6:p:687-696
    DOI: 10.1080/14697680701283739
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    Citations

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    Cited by:

    1. Matteo Grigoletto & Francesco Lisi, 2011. "Practical implications of higher moments in risk management," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(4), pages 487-506, November.
    2. Riccardo Borgoni & Piero Quatto & Giorgio Somà & Daniela Bartolo, 2010. "A geostatistical approach to define guidelines for radon prone area identification," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(2), pages 255-276, June.
    3. Julio Escolano & Vitor Gaspar, 2016. "Optimal Debt Policy Under Asymmetric Risk," IMF Working Papers 16/178, International Monetary Fund.
    4. So, Mike K.P. & Chan, Raymond K.S., 2014. "Bayesian analysis of tail asymmetry based on a threshold extreme value model," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 568-587.
    5. Valencia, Marisol & Bedoya, Alejandro, 2013. "Prueba de sesgo sobre rendimientos financieros en el mercado colombiano," REVISTA LECTURAS DE ECONOMÍA, UNIVERSIDAD DE ANTIOQUIA - CIE, issue 80, pages 79-102, November.
    6. Pelagatti Matteo M, 2009. "Modelling Good and Bad Volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(1), pages 1-20, March.

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