cCorrGAN swMATH ID: 44878 Software Authors: Marti, Gautier; Goubet, Victor; Nielsen, Frank Description: cCorrGAN: conditional correlation GAN for learning empirical conditional distributions in the elliptope. We propose a methodology to approximate conditional distributions in the elliptope of correlation matrices based on conditional generative adversarial networks. We illustrate the methodology with an application from quantitative finance: Monte Carlo simulations of correlated returns to compare risk-based portfolio construction methods. Finally, we discuss about current limitations and advocate for further exploration of the elliptope geometry to improve results. Homepage: https://arxiv.org/abs/2107.10606 Keywords: generative adversarial networks; correlation matrices; elliptope geometry; empirical distributions; quantitative finance; Monte Carlo simulations Related Software: geomstats; CorrGAN; QuantGAN; POT Cited in: 2 Documents Standard Articles 1 Publication describing the Software, including 1 Publication in zbMATH Year cCorrGAN: conditional correlation GAN for learning empirical conditional distributions in the elliptope. Zbl 07495261Marti, Gautier; Goubet, Victor; Nielsen, Frank 2021 Cited by 5 Authors 1 Goubet, Victor 1 Marti, Gautier 1 Nielsen, Frank 1 Pennec, Xavier 1 Thanwerdas, Yann Cited in 1 Serial 1 SIAM Journal on Matrix Analysis and Applications Cited in 5 Fields 2 Linear and multilinear algebra; matrix theory (15-XX) 1 Differential geometry (53-XX) 1 Global analysis, analysis on manifolds (58-XX) 1 Statistics (62-XX) 1 Computer science (68-XX) Citations by Year