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• "Credit line exposure at default modelling using Bayesian mixed effect quantile regression", Betz, Nagl, Rösch, 2022

  Publikation

  For banks, credit lines play an important role exposing both liquidity and credit risk. In the advanced internal ratings-based approach, banks are...

  Publikation auf epub.uni-regensburg.de: "Credit line exposure at default modelling using Bayesian mixed effect quantile regression" (externer Link, öffnet neues Fenster)

• "Deep calibration of financial models: turning theory into practice", Büchel, Kratochwil, Nagl, Rösch, 2022

  Publikation

  The calibration of financial models is laborious, time-consuming and expensive, and needs to be performed frequently by financial institutions....

  Publikation auf epub.uni-regensburg.de: "Deep calibration of financial models: turning theory into practice" (externer Link, öffnet neues Fenster)

• "Quantifying uncertainty of machine learning methods for loss given default", Nagl, Nagl, Rösch, 2022

  Publikation

  Machine learning has increasingly found its way into the credit risk literature. When applied to forecasting credit risk parameters, the approaches...

  Publikation auf epub.uni-regensburg.de: "Quantifying uncertainty of machine learning methods for loss given default" (externer Link, öffnet neues Fenster)

• "Introducing an Interpretable Deep Learning Approach to Domain-Specific Dictionary Creation: A Use Case for Conflict Prediction", Häffner, Hofer, Nagl, Walterskirchen, 2023

  Publikation

  Recent advancements in natural language processing (NLP) methods have significantly improved their performance. However, more complex NLP models are...

  Publikation auf epub.uni-regensburg.de: "Introducing an Interpretable Deep Learning Approach to Domain-Specific Dictionary Creation: A Use Case for Conflict Prediction" (externer Link, öffnet neues Fenster)

• "Time Varying Dependences Between Real Estate Crypto, Real Estate and Crypto Returns", Nagl, Nagl, Rösch, Schäfers, Freybote, 2023

  Publikation

  In recent years, blockchain-based platforms such as Propy and Elysia have emerged that apply tokenization to commercial real estate. They issue real...

  Publikation auf epub.uni-regensburg.de: "Time Varying Dependences Between Real Estate Crypto, Real Estate and Crypto Returns" (externer Link, öffnet neues Fenster)

• "Intricacy of cryptocurrency returns", Nagl, 2024

  Publikation

  This paper quantifies the intricacy, i.e., non-linearity and interactions of predictor variables, in explaining cryptocurrency returns. Using data...

  Publikation auf epub.uni-regensburg.de: "Intricacy of cryptocurrency returns" (externer Link, öffnet neues Fenster)

• "Non-linearity and the distribution of market-based loss rates", Nagl, Nagl, Rösch, 2024

  Publikation

  We synthesize the extended linear beta regression with a neural network structure to model and predict the mean and precision of market-based loss...

  Publikation auf epub.uni-regensburg.de: "Non-linearity and the distribution of market-based loss rates" (externer Link, öffnet neues Fenster)

• "Uncertainty-aware machine learning with applications to credit risk", Nagl, 2024

  Publikation

  This cumulative doctoral thesis aims to shed light on the application of uncertainty-aware machine learning to credit risk problems. Over the last...

  Publikation auf epub.uni-regensburg.de: "Uncertainty-aware machine learning with applications to credit risk" (externer Link, öffnet neues Fenster)

• "Carbon Markets—Catalyst for Portfolio Growth and Responsible Investing", Billand, Nagl, Rösch, 2025

  Publikation

  The financial sector, particularly investors, can make a significant contribution to the fight against climate change. They can drive the green...

  Publikation auf epub.uni-regensburg.de: "Carbon Markets—Catalyst for Portfolio Growth and Responsible Investing" (externer Link, öffnet neues Fenster)

• "Optimal portfolio selection with parameter estimation risks: Statistical modeling and empirical applications", Kircher, 2025

  Publikation

  This cumulative dissertation proposes and evaluates new approaches for improving the out-of-sample performance of mean-variance optimized portfolios...

  Publikation auf epub.uni-regensburg.de: "Optimal portfolio selection with parameter estimation risks: Statistical modeling and empirical applications" (externer Link, öffnet neues Fenster)