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The Role of Asymmetric Families of Distributions in Eliminating Risk

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Theory and Practice of Risk Assessment

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 136))

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Abstract

Modeling is always a crucial component of the risk assessment process. The use of adequate classes of distributions to model real data sets seems sensible to accommodate specific peculiarities of the data and enable us to implement resistant procedures, less sensitive to changes in the model. Despite the practical advantages of using the normal distribution, it is recognized that most of the data from diverse areas of application, such as economics, environment, finance, insurance, meteorology, reliability and statistical quality control, among others, usually exhibit moderate to strong asymmetry and heavier tails than the normal tail. This study motivates the use of two classes of skew-normal distributions that include highly skewed and heavy-tailed distributions as well as models that are close to the Gaussian family. Some guidelines for inference on the parameters of the model are suggested, and applications to real data sets are presented.

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Acknowledgments

Research partially supported by National Funds through FCT—Fundação para a Ciência e a Tecnologia, projects PEst-OE/MAT/UI0006/2014, PEst-OE /MAT /UI0006 /2011 (CEAUL) and EXTREMA, PTDC /MAT /101736 /2008. The authors would like to acknowledge the helpful suggestions of the anonymous reviewers and the editor.

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Authors and Affiliations

  1. FEP, Universidade do Porto, and CEAUL, Rua Dr Roberto Frias, 4200-464, Porto, Portugal

    Fernanda Otília Figueiredo

  2. FCUL, DEIO and CEAUL, Universidade de Lisboa, Campo Grande, 1749-016, Lisbon, Portugal

    Maria Ivette Gomes

Authors
  1. Fernanda Otília Figueiredo
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  2. Maria Ivette Gomes
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Corresponding author

Correspondence to Fernanda Otília Figueiredo .

Editor information

Editors and Affiliations

  1. Technological Educational Institute of Athens, Athens, Greece

    Christos P. Kitsos

  2. Universidade Aberta, Palácio Ceia, Lisbon, Portugal

    Teresa A. Oliveira

  3. Democritus University, Thrace, Germany

    Alexandros Rigas

  4. Florida International University, Miami, Florida, USA

    Sneh Gulati

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© 2015 Springer International Publishing Switzerland

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Figueiredo, F.O., Gomes, M.I. (2015). The Role of Asymmetric Families of Distributions in Eliminating Risk. In: Kitsos, C., Oliveira, T., Rigas, A., Gulati, S. (eds) Theory and Practice of Risk Assessment. Springer Proceedings in Mathematics & Statistics, vol 136. Springer, Cham. https://doi.org/10.1007/978-3-319-18029-8_20

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