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Current and prospective estimate of counterparty risk throu..:
Alessio Agnese
;
Pier Giuseppe Giribone
;
Francesca Querci
https://www.aifirm.it/wp-content/uploads/2022/08/RMM-2022-02-Excerpt-5.pdf. , 2022
Link:
https://doi.org/10.47473/2020rmm0112
RT Journal T1 <Title>Current and prospective estimate of counterparty risk through dynamic neural networks</Title> UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:a92d2cc176464bddabd7e951d9421b50&Exemplar=1&LAN=DE A1 Alessio Agnese A1 Pier Giuseppe Giribone A1 Francesca Querci PB AIFIRM YR 2022 K1 default probability K1 counterparty risk K1 credit default swap K1 corporate bond K1 kmv model K1 nonlinear auto-regressive (nar) network K1 forecasting K1 Risk in industry. Risk management K1 HD61 JF https://www.aifirm.it/wp-content/uploads/2022/08/RMM-2022-02-Excerpt-5.pdf LK http://dx.doi.org/https://doi.org/10.47473/2020rmm0112 DO https://doi.org/10.47473/2020rmm0112 SF ELIB - SuUB Bremen
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