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Communications in Statistics - Theory and Methods Volume 36, 2007 - Issue 1
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DISTRIBUTION THEORY

Tukey-Type Distributions in the Context of Financial Data

Matthias Fischer Department of Statistics and Econometrics, University of Erlangen, Nürnberg, GermanyCorrespondence[email protected]
,
Armin Horn Department of Statistics and Econometrics, University of Erlangen, Nürnberg, Germany
&
Ingo Klein Department of Statistics and Econometrics, University of Erlangen, Nürnberg, Germany
Pages 23-35 | Received 02 Jul 2003, Accepted 09 Sep 2005, Published online: 18 Feb 2007

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Linda Möstel, Matthias Fischer, Fabian Pfälzner & Marius Pfeuffer. (2021) Parameter estimation of Tukey-type distributions: A comparative analysis. Communications in Statistics - Simulation and Computation 50:4, pages 957-992.
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Ingrida Vaiciulyte, Zivile Kalsyte, Leonidas Sakalauskas & Darius Plikynas. (2017) Assessment of market reaction on the share performance on the basis of its visualization in 2D space. Journal of Business Economics and Management 18:2, pages 309-318.
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Yulei He & Trivellore E. Raghunathan. (2012) Multiple imputation using multivariate gh transformations. Journal of Applied Statistics 39:10, pages 2177-2198.
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Filippo Domma, Sabrina Giordano & Pier Francesco Perri. (2009) Statistical Modeling of Temporal Dependence in Financial Data via a Copula Function. Communications in Statistics - Simulation and Computation 38:4, pages 703-728.
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Michele Haynes, Kerrie Mengersen & Paul Rippon. (2008) Generalized Control Charts for Non-Normal Data Using g-and-k Distributions. Communications in Statistics - Simulation and Computation 37:9, pages 1881-1903.
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Articles from other publishers (11)

Marco Bee, Julien Hambuckers, Flavio Santi & Luca Trapin. (2021) Testing a parameter restriction on the boundary for the g-and-h distribution: a simulated approach. Computational Statistics 36:3, pages 2177-2200.
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Gareth Peters. (2018) General Quantile Time Series Regressions for Applications in Population Demographics. Risks 6:3, pages 97.
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Gareth Peters, Wilson Chen & Richard Gerlach. (2016) Estimating Quantile Families of Loss Distributions for Non-Life Insurance Modelling via L-Moments. Risks 4:2, pages 14.
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M. C. Jones. (2015) On Families of Distributions with Shape Parameters. International Statistical Review 83:2, pages 175-192.
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Marcelo G. Cruz, Gareth W. Peters & Pavel V. Shevchenko. 2015. Fundamental Aspects of Operational Risk and Insurance Analytics. Fundamental Aspects of Operational Risk and Insurance Analytics 851 891 .
Gareth W. Peters & Pavel V. Shevchenko. 2015. Advances in Heavy Tailed Risk Modeling. Advances in Heavy Tailed Risk Modeling 597 622 .
Christopher C. Drovandi & Anthony N. Pettitt. (2011) Likelihood-free Bayesian estimation of multivariate quantile distributions. Computational Statistics & Data Analysis 55:9, pages 2541-2556.
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Matthias Fischer. (2008) Generalized Tukey-type distributions with application to financial and teletraffic data. Statistical Papers 51:1, pages 41-56.
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Gareth William Peters. (2017) Tutorial on General Quantile Time Series Constructions. SSRN Electronic Journal.
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Gareth William Peters, Wilson Y. Chen & Richard H. Gerlach. (2016) Estimating Quantile Families of Loss Distributions for Non-Life Insurance Modelling via L-Moments. SSRN Electronic Journal.
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Jochen Mandl. (2007) A Data-Analytic Examination of the Risk in Hedge Funds Returns: The g-and-h Distributions. SSRN Electronic Journal.
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