Nonparametric Estimation of the Expected Shortfall Regression for Quasi-Associated Functional Data

In this paper, we study the nonparametric estimation of the expected shortfall regression when the exogenous observation is functional. The constructed estimator is obtained by combining the double kernels estimator of both conditional value at risk and conditional density function. The asymptotic p...

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Bibliografiska uppgifter

Huvudupphov:	Larbi Ait-Hennani, Zoulikha Kaid, Ali Laksaci, Mustapha Rachdi
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	MDPI AG 2022-11-01
Serie:	Mathematics
Ämnen:	functional data complete convergence (a.co.) risk analysis expected shortfall regression kernel method bandwidth parameter
Länkar:	https://www.mdpi.com/2227-7390/10/23/4508
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