Dependencia entre garantías en el ramo autos de una empresa aseguradora. Un análisis a través de la Teoría de cópulas

Carmen Ruiz Arellano

doi:10.26360/2021_2

Authors

Carmen Ruiz Arellano Plus Ultra Seguros Generales y Vida, S.A. (España)

DOI:

https://doi.org/10.26360/2021_2

Keywords:

Copula theory, empirical copula, statistical distributions, insurance, vehicles

Abstract

The present work tries to analyse the relationships between different auto-insurance guarantees through the application of the copula theory. The analysis of the data allows to shed light on the dependency relationships existing between the risk of insurance policies through various statistical functions. The results show how important are the effects derived from the analysis on the segmentation of customers and on the ways of pricing.

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References

Brechmann, E. y Schepsmeier, U. (2013). Cdvine: Modeling dependence with c-and d-vine copulas in r. Journal of Statistical Software, 52(3), 1-27.

Galton, F. (1885). International Health Exhibition. mimeo. Illanes, G. (2013). Cópulas paramétricas y no paramétricas. Obtenido de https://www.fing.edu.uy/sites/default/files/biblio/9476/c%c3%b3pulas%20param%c3%a9tricas%20y%20no%20param%c3%a9tricas_2013.pdf

Li, F., y Kang, Y. (2018). Improving forecasting performance using covariate-dependent copula models. International Journal of Forecasting, 34(3), 456-476.

Liu, Z., Zhou, P., Chen, X., y Guan, Y. (2015). A multivariate conditional model for streamflow prediction and spatial precipitation refinement. Journal of Geophysical Research: Atmospheres, 120(19), 10-116.

Marius Hofert, I. K. (19 de 05 de 2020). https://cran.r-project.org/web/packages/copula/copula.pdf. Obtenido de https://cran.r-project.org/web/packages/copula/copula.pdf

Scrucca, L. (2004). qcc: an R package for quality control charting and statistical process control. dim (pistonrings), 1(200), 3.