Jump to: 2026 | 2025 | 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2009 | 2007 | 2006 | 2005
2026
Risk management in digital finance: Assessment and pricing in an emerging fintech era (2026) [Thesis › PhD Thesis - Research UT, graduation UT] . University of Twente . Baals, L. J. https://doi.org/10.3990/1.9789036571234 Digital assets: risks, regulations, mitigation (2026) Financial Innovation, 12(1) . Article 65 . Teng, H. W. , Härdle, W. K. , Osterrieder, J. , Pele, D. T. , Baals, L. J. , Papavassiliou, V. , Bolesta, K. , Kabašinskas, A. , Filipovska, O. , Thomaidis, N. S. , Moukas, A. I. , Goundar, S. , Nasir, J. A. , Weinberg, A. I. , Arakelian, V. , Truică, C. O. , Akar, M. , Kabaklarlı, E. , Apostol, E. S. , … Xhumari, E. https://doi.org/10.1186/s40854-025-00848-y
2025
Advancing credit risk assessment in the retail banking industry: A hybrid approach using time series and supervised learning models (2025) Data & knowledge engineering, 160 . Article 102490 . Goldmann, S. H. , Machado, M. R. & Osterrieder, J. R. https://doi.org/10.1016/j.datak.2025.102490 An analytical approach to credit risk assessment using machine learning models (2025) Decision Analytics Journal, 16 . Article 100605 . Machado, M. R. , Chen, D. T. & Osterrieder, J. R. https://doi.org/10.1016/j.dajour.2025.100605 How can consumers without credit history benefit from the use of information processing and machine learning tools by financial institutions? (2025) Information processing & management, 62(2) . Article 103972 . van Braak, B. , Osterrieder, J. R. & Machado, M. R. https://doi.org/10.1016/j.ipm.2024.103972 Modeling commodity price co-movement: building on traditional time series models and exploring applications of machine learning algorithms (2025) Decisions in economics and finance . Article 109283 (E-pub ahead of print/First online) . Kozian, L. L. , Machado, M. R. & Osterrieder, J. R. https://doi.org/10.1007/s10203-025-00512-1 Predicting retail customers' distress in the finance industry: An early warning system approach (2025) Journal of Retailing and Consumer Services, 82 . Article 104101 . Beltman, J. , Machado, M. R. & Osterrieder, J. R. https://doi.org/10.1016/j.jretconser.2024.104101
2024
How can artificial intelligence help customer intelligence for credit portfolio management? A systematic literature review (2024) International Journal of Information Management Data Insights, 4(2) . Article 100234 . Amato, A. , Osterrieder, J. R. & Machado, M. R. https://doi.org/10.1016/j.jjimei.2024.100234 Stylized facts of metaverse non-fungible tokens (2024) Physica A, 653 . Article 130103 . Chan, S. , Chandrashekhar, D. , Almazloum, W. , Zhang, Y. , Lord, N. , Osterrieder, J. & Chu, J. https://doi.org/10.1016/j.physa.2024.130103 Leveraging network topology for credit risk assessment in P2P lending: A comparative study under the lens of machine learning (2024) Expert systems with applications, 252(Part B) . Article 124100 . Liu, Y. , Baals, L. J. , Osterrieder, J. & Hadji-Misheva, B. https://doi.org/10.1016/j.eswa.2024.124100 Network centrality and credit risk: A comprehensive analysis of peer-to-peer lending dynamics (2024) Finance Research Letters, 63 . Article 105308 . Liu, Y. , Baals, L. J. , Osterrieder, J. & Hadji-Misheva, B. https://doi.org/10.1016/j.frl.2024.105308 Leveraging Network Topology for Credit Risk Assessment in P2P Lending: A Comparative Study under the Lens of Machine Learning (2024) [Working paper › Preprint] . Social Science Research Network (SSRN) . Liu, Y. , Baals, L. J. , Osterrieder, J. & Hadji-Misheva, B. https://doi.org/10.2139/ssrn.4726481 Network Centrality and Credit Risk: A Comprehensive Analysis of Peer-to-Peer Lending Dynamics (2024) [Working paper › Preprint] . Social Science Research Network (SSRN) . Liu, Y. , Baals, L. J. , Osterrieder, J. & Hadji-Misheva, B. https://doi.org/10.2139/ssrn.4726490 Forecasting Commercial Customers Credit Risk Through Early Warning Signals Data: A Machine Learning based Approach (2024) [Working paper › Preprint] . Social Science Research Network (SSRN) . Machado, M. , Osterrieder, J. & Chen, D. https://doi.org/10.2139/ssrn.4754568 Hypothesizing Multimodal Influence: Assessing the Impact of Textual and Non-Textual Data on Financial Instrument Pricing Using NLP and Generative AI (2024) [Working paper › Preprint] . Social Science Research Network (SSRN) . Bolesta, K. , Taibi, G. , Mare, C. , Hadji-Misheva, B. , Hopp, C. & Osterrieder, J. https://doi.org/10.2139/ssrn.4698153 Towards a new PhD Curriculum for Digital Finance (2024) Open Research Europe, 4 . Article 7 . Baals, L. J. , Osterrieder, J. R. , Hadji-Misheva, B. & Liu, Y. https://doi.org/10.12688/openreseurope.16513.1 AI 4 Crowdfunding: A hands-on roadmap to study and understand crowdfunding data using critical thinking AI (2024) [Working paper › Working paper] . Social Science Research Network (SSRN) . Belbe, S. , Gomez, L. , Stanca, L. , Wenzlaff, K. , Mare, C. , Elitzur, R. , Bolesta, K. , Huang, X. , Yilmaz, G. N. , Sinan Bernard, F. , Osterrieder, J. , Coita, I. F. , Filipovska, O. , Skaftadóttir, H. K. , van Teunenbroek, C. , Pisoni, G. & Spaeth, S. https://doi.org/10.2139/ssrn.4941279 SNSF Narrative Digital Finance: a tale of structural breaks, bubbles & market narratives (2024) [Other contribution › Other contribution] . Osterrieder, J. & Hopp, C.
2023
Modelling taxpayers’ behaviour based on prediction of trust using sentiment analysis (2023) Finance Research Letters, 58(Part C) . Article 104549 . Coita, I. F. , Belbe, S. (. , Mare, C. (. , Osterrieder, J. & Hopp, C. https://doi.org/10.1016/j.frl.2023.104549 Examining share repurchase executions: insights and synthesis from the existing literature (2023) Frontiers in Applied Mathematics and Statistics, 9 . Article 1265254 . Osterrieder, J. & Seigne, M. https://doi.org/10.3389/fams.2023.1265254 Share buybacks: A theoretical exploration of genetic algorithms and mathematical optionality (2023) Frontiers in Artificial Intelligence, 6 . Article 1276804 . Osterrieder, J. https://doi.org/10.3389/frai.2023.1276804 The Great Deception: A Comprehensive Study of Execution Strategies in Corporate Share Buy-Backs (2023) [Working paper › Preprint] . Seigne, M. & Osterrieder, J. Navigating the Environmental, Social, and Governance (ESG) landscape: constructing a robust and reliable scoring engine - insights into Data Source Selection, Indicator Determination, Weighting and Aggregation Techniques, and Validation Processes for Comprehensive ESG Scoring Systems (2023) Open Research Europe, 3 . Article 119 . Liu, Y. , Osterrieder, J. , Hadji Misheva, B. , Koenigstein, N. & Baals, L. https://doi.org/10.12688/openreseurope.16278.1 Preface (2023) In Enterprise Applications, Markets and Services in the Finance Industry: 11th International Workshop, FinanceCom 2022, Twente, The Netherlands, August 23–24, 2022, Revised Selected Papers (pp. vii-viii) (Lecture notes in business information processing; Vol. 467) . van Hillegersberg, J. , Osterrieder, J. , Rabhi, F. , Abhishta, A. , Marisetty, V. & Huang, X. https://doi.org/10.1007/978-3-031-31671-5 Digital Finance: Reaching New Frontiers (2023) Open Research Europe, 3 . Article 38 . Osterrieder, J. , Hadji Misheva, B. & Machado, M. https://doi.org/10.12688/openreseurope.15386.1
2022
Feature Selection via the Intervened Interpolative Decomposition and its Application in Diversifying Quantitative Strategies (2022) [Working paper › Preprint] . ArXiv.org . Lu, J. & Osterrieder, J. Editorial: Artificial intelligence in finance and industry: Highlights from 6 European COST conferences (2022) Frontiers in Artificial Intelligence, 5 . Article 1007074 . Henrici, A. & Osterrieder, J. https://doi.org/10.3389/frai.2022.1007074 Discussion on: “Programmable money: next generation blockchain based conditional payments” by Ingo Weber and Mark Staples (2022) Digital Finance, 4(2-3) , 137-138 . Osterrieder, J. https://doi.org/10.1007/s42521-022-00063-9 Simulating financial time series using attention (2022) [Working paper › Preprint] . Fu, W. , Hirsa, A. & Osterrieder, J. Applications of Reinforcement Learning in Finance -- Trading with a Double Deep Q-Network (2022) [Working paper › Preprint] . Zejnullahu, F. , Moser, M. & Osterrieder, J. https://doi.org/10.48550/arXiv.2206.14267 High-Frequency Causality in the VIX Index and its derivatives: Empirical Evidence (2022) [Working paper › Preprint] . Farokhnia, K. & Osterrieder, J. AI for trading strategies (2022) [Working paper › Preprint] . Jevtic, D. , Deleze, R. & Osterrieder, J. The Efficient Market Hypothesis for Bitcoin in the context of neural networks (2022) [Working paper › Preprint] . Kraehenbuehl, M. & Osterrieder, J. Enterprise Applications, Markets and Services in the Finance Industry: 11th International Workshop, FinanceCom 2022, Twente, The Netherlands, August 23–24, 2022, Revised Selected Papers (2022) [Book/Report › Book editing] 11th International Workshop on Enterprise Applications, Markets and Services in the Finance Industry, FinanceCom 2022 . Springer . van Hillegersberg, J. , Osterrieder, J. , Rabhi, F. , Abhishta, A. , Marisetty, V. & Huang, X. https://doi.org/10.1007/978-3-031-31671-5
2021
Wasserstein GAN: Deep Generation applied on Bitcoins financial time series (2021) [Working paper › Preprint] . Samuel, R. , Nico, B. D. , Moritz, P. & Joerg, O. Deep reinforcement learning on a multi-asset environment for trading (2021) [Working paper › Preprint] . Hirsa, A. , Osterrieder, J. , Hadji-Misheva, B. & Posth, J.-A. Generative Adversarial Networks in finance: an overview (2021) [Working paper › Preprint] . Eckerli, F. & Osterrieder, J. The Applicability of Self-Play Algorithms to Trading and Forecasting Financial Markets (2021) Frontiers in Artificial Intelligence, 4 . Article 668465 . Posth, J.-A. , Kotlarz, P. K. , Hadji-Misheva, B. , Osterrieder, J. & Schwendner, P. https://doi.org/10.3389/frai.2021.668465 Explainable AI in Credit Risk Management (2021) [Working paper › Working paper] . ArXiv.org . Osterrieder, J. , Misheva, B. H. , Hirsa, A. , Kulkarni, O. & Lin, S. F. https://doi.org/10.48550/arXiv.2103.00949 The VIX index under scrutiny of machine learning techniques and neural networks (2021) [Working paper › Working paper] . ArXiv.org . Hirsa, A. , Osterrieder, J. , Misheva, B. H. , Cao, W. , Fu, Y. , Sun, H. & Wong, K. W. https://doi.org/10.48550/arXiv.2102.02119 Audience-Dependent Explanations for AI-Based Risk Management Tools: A Survey (2021) Frontiers in Artificial Intelligence, 4 . Article 794996 . Hadji Misheva, B. , Jaggi, D. , Posth, J.-A. , Gramespacher, T. & Osterrieder, J. https://doi.org/10.3389/frai.2021.794996
2020
Neural networks and arbitrage in the VIX: A deep learning approach for the VIX (2020) Digital Finance, 2 , 97-115 . Osterrieder, J. , Kucharczyk, D. , Rudolf, S. & Wittwer, D. https://doi.org/10.1007/s42521-020-00026-y
2019
Editorial: AI and financial technology (2019) Frontiers in Artificial Intelligence, 2 . Article 25 . Giudici, P. , Hochreiter, R. , Osterrieder, J. , Papenbrock, J. & Schwendner, P. https://doi.org/10.3389/frai.2019.00025 Neural Networks and Arbitrage in the VIX: A Deep Learning Approach for the VIX (2019) [Working paper › Working paper] . Kucharczyk, D. , Osterrieder, J. , Rudolf, S. & Wittwer, D. https://doi.org/10.2139/ssrn.3305686 The VIX volatility index-A very thorough look at it (2019) SSRN ELibrary, 2019 . Article 3311727 . Osterrieder, J. , Vetter, L. & Röschli, K. https://doi.org/10.2139/ssrn.3311727 Editorial on the Special Issue on Cryptocurrencies (2019) Digital Finance, 1 , 1-4 . Osterrieder, J. & Barletta, A. https://doi.org/10.1007/s42521-019-00015-w Machine Learning Tools for Probability of Default and Rating Downgrades of Corporate and Government Bonds (2019) SSRN ELibrary . Article 3461558 . Choudary, J. & Osterrieder, J.
2018
Pattern Learning Via Artificial Neural Networks for Financial Market Predictions (2018) SSRN ELibrary . Article 3243479 . Gabler, A. , Perez, D. , Sutter, U. , Kucharczyk, D. , Osterrieder, J. & Reitenbach, M. Pricing, Loss and Sensitivity Analysis of Barrier Options via Regression (2018) SSRN ELibrary . Article 3194111 . Gabler, A. , Wiegand, M. & Osterrieder, J.
2017
GARCH Modelling of Cryptocurrencies (2017) Journal of Risk and Financial Management, 10(4) . Article 17 . Chu, J. , Chan, S. , Nadarajah, S. & Osterrieder, J. https://doi.org/10.3390/jrfm10040017 A Dynamic Market Microstructure Model with Market Orders and Random Order Book Depth (2017) [Working paper › Working paper] . Osterrieder, J. https://doi.org/10.2139/ssrn.2984315 A Statistical Analysis of Cryptocurrencies (2017) Journal of Risk and Financial Management, 10(2) . Article 12 . Chan, S. , Chu, J. , Nadarajah, S. & Osterrieder, J. https://doi.org/10.3390/jrfm10020012 Momentum and trend following trading strategies for currencies revisited-combining academia and industry (2017) [Working paper › Preprint] . Social Science Research Network (SSRN) . Rohrbach, J. , Suremann, S. & Osterrieder, J. https://doi.org/10.2139/ssrn.2949379 A statistical risk assessment of bitcoin and its extreme tail behavior (2017) Annals of Financial Economics, 12(01) . Article 1750003 . Osterrieder, J. & Lorenz, J. https://doi.org/10.1142/s2010495217500038 A Statistical Analysis of Carry Trading (2017) SSRN ELibrary . Fritzmann, S. , Jaggi, D. & Osterrieder, J. https://doi.org/10.2139/ssrn.2993902 Bitcoin and Cryptocurrencies—Not for the Faint-Hearted (2017) International Finance and Banking, 4(1) , 56-94 . Osterrieder, J. , Strika, M. & Lorenz, J. https://doi.org/10.5296/ifb.v4i1.10451 GARCH Modeling of Cryptocurrencies (2017) [Working paper › Working paper] . Chu, J. , Chan, S. , Nadarajah, S. & Osterrieder, J. https://doi.org/10.2139/ssrn.3047027 The Statistics of Bitcoin and Cryptocurrencies (2017) In Proceedings of the 2017 International Conference on Economics, Finance and Statistics (ICEFS 2017) (Advances in Economics, Business and Management Research; Vol. 26) . Osterrieder, J. https://doi.org/10.2991/icefs-17.2017.33
2009
Simulation of a limit order driven market (2009) The Journal Of Trading, 4(1) , 23-30 . Lorenz, J. & Osterrieder, J. https://jot.pm-research.com/content/4/1/23
2007
Arbitrage, the limit order book and market microstructure aspects in financial market models (2007) [Thesis › PhD Thesis - Research external, graduation external] . ETH Zurich . Osterrieder, J. R. https://doi.org/10.3929/ethz-a-005369031
2006
A Theoretical Model of the Limit Order Book and Some Applications (2006) SSRN ELibrary . Osterrieder, J. https://doi.org/10.2139/ssrn.881274 Arbitrage opportunities in diverse markets via a non-equivalent measure change (2006) Annals of Finance, 2 , 287-301 . Osterrieder, J. R. & Rheinländer, T. https://doi.org/10.1007/s10436-006-0037-z