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q-fin.RM2024
Measuring Name Concentrations through Deep Learning
Eva Lütkebohmert, Julian Sester
We propose a new deep learning approach for the quantification of name concentration risk in loan portfolios. Our approach is tailored for small portfolios and allows for both an a…
q-fin.RM2023
On the Relevance and Appropriateness of Name Concentration Risk Adjustments for Portfolios of Multilateral Development Banks
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…
q-fin.RM2021
Robust deep hedging
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 we…