Abstract
We show that Sarmanov copula and kernel estimation can be mixed to estimate the risk of an economic loss. We use a bivariate sample from a real data base. We show that the estimation of the dependence parameter of the copula using double transformed kernel estimation to estimate marginal cumulative distribution functions provides balanced risk estimates.
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Bahraoui, Z., Bolancé, C., Alemany, R. (2013). Estimating Risk with Sarmanov Copula and Nonparametric Marginal Distributions. In: Fernández-Izquierdo, M.Á., Muñoz-Torres, M.J., León, R. (eds) Modeling and Simulation in Engineering, Economics, and Management. MS 2013. Lecture Notes in Business Information Processing, vol 145. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38279-6_10
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DOI: https://doi.org/10.1007/978-3-642-38279-6_10
Publisher Name: Springer, Berlin, Heidelberg
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