Abstract
In what follows, we consider a random vector (X, Y) and we study the distribution of \(X+Y\) and the copula associated to the random vector \((X,X+Y)\). Since this represents the basic concept of the book, we include proofs, even if they are also presented in Cherubini et al., (Dynamic copula methods in finance, 2012) (see also Cherubini et al., Journal of Multivariate Analysis, 2011).
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Cherubini, U., Gobbi, F., Mulinacci, S. (2016). Convolution-Based Processes. In: Convolution Copula Econometrics. SpringerBriefs in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-48015-2_4
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DOI: https://doi.org/10.1007/978-3-319-48015-2_4
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