Entries of Nagl, Maximilian on the publication server

Kozak, Jakob , Nagl, Cathrine, Nagl, Maximilian , Beracha, Eli and Schäfers, Wolfgang (2025) Does Real Estate Determine REIT Bond Risk Premia? Journal of Real Estate Finance and Economics.

Jenett, Hendrik, Nagl, Cathrine, Nagl, Maximilian , Price, S. McKay and Schäfers, Wolfgang (2025) Dynamics of REIT Returns and Volatility: Analyzing Time-Varying Drivers Through an Explainable Machine Learning Approach. The Journal of Real Estate Finance and Economics.

Leonhard, Heiko, Nagl, Maximilian and Schäfers, Wolfgang (2025) Virtual land in the metaverse? Exploring the dynamic correlation with physical real estate. Journal of European Real Estate Research. Fulltext not available.

Billand, Alicia, Nagl, Maximilian and Rösch, Daniel (2025) Carbon Markets—Catalyst for Portfolio Growth and Responsible Investing. The Journal of Alternative Investments 28 (2), pp. 7-63. Fulltext not available.

Nagl, Matthias, Nagl, Maximilian and Rösch, Daniel (2024) Non-linearity and the distribution of market-based loss rates. OR Spectrum.

Nagl, Maximilian (2024) Intricacy of cryptocurrency returns. Economics Letters 239, p. 111746.

Nagl, Cathrine, Nagl, Maximilian , Rösch, Daniel, Schäfers, Wolfgang and Freybote, Julia (2023) Time Varying Dependences Between Real Estate Crypto, Real Estate and Crypto Returns. Journal of Real Estate Research, pp. 1-29. Fulltext not available.

Häffner, Sonja, Hofer, Martin , Nagl, Maximilian and Walterskirchen, Julian (2023) Introducing an Interpretable Deep Learning Approach to Domain-Specific Dictionary Creation: A Use Case for Conflict Prediction. Political Analysis, pp. 1-19.

Nagl, Matthias, Nagl, Maximilian and Rösch, Daniel (2022) Quantifying uncertainty of machine learning methods for loss given default. Frontiers in Applied Mathematics and Statistics 8, p. 1076083.

Büchel, Patrick, Kratochwil, Michael, Nagl, Maximilian and Rösch, Daniel (2022) Deep calibration of financial models: turning theory into practice. Review of Derivatives Research 25, pp. 109-136.

Betz, Jennifer , Nagl, Maximilian and Rösch, Daniel (2022) Credit line exposure at default modelling using Bayesian mixed effect quantile regression. Journal of the Royal Statistical Society: Series A (Statistics in Society), pp. 1-38.

Nagl, Maximilian (2022) Statistical and machine learning for credit and market risk management. PhD, Universität Regensburg.

Kellner, Ralf, Nagl, Maximilian and Rösch, Daniel (2022) Opening the black box – Quantile neural networks for loss given default prediction. Journal of Banking & Finance 134, p. 106334. Fulltext not available.

Pfeuffer, Marius, Nagl, Maximilian , Fischer, Matthias and Rösch, Daniel (2020) Parameter estimation, bias correction and uncertainty quantification in the Vasicek credit portfolio model. Journal of Risk 22, pp. 1-30. Fulltext not available.