no code implementations • 25 Mar 2024 • Eva Lütkebohmert, Julian Sester
We propose a new deep learning approach for the quantification of name concentration risk in loan portfolios.
no code implementations • 23 Nov 2023 • Eva Lütkebohmert, Julian Sester, Hongyi Shen
Sovereign loan portfolios of Multilateral Development Banks (MDBs) typically consist of only a small number of borrowers and hence are heavily exposed to single name concentration risk.
1 code implementation • 3 Apr 2022 • Jonathan Ansari, Eva Lütkebohmert, Ariel Neufeld, Julian Sester
We show how inter-asset dependence information derived from market prices of options can lead to improved model-free price bounds for multi-asset derivatives.
1 code implementation • 18 Jun 2021 • Eva Lütkebohmert, Thorsten Schmidt, Julian Sester
We study pricing and hedging under parameter uncertainty for a class of Markov processes which we call generalized affine processes and which includes the Black-Scholes model as well as the constant elasticity of variance (CEV) model as special cases.
