cCorrGAN: Conditional Correlation GAN for Learning Empirical Conditional Distributions in the Elliptope

Gautier Marti, Victor Goubet and Frank Nielsen

Papers from arXiv.org

Abstract: 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.

Date: 2021-07
New Economics Papers: this item is included in nep-cmp, nep-ecm and nep-rmg
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Published in GSI 2021: Geometric Science of Information pp 613-620

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