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J.R.O. Osterrieder (Jörg)

Associate Professor of Artificial Intelligence and Finance

About Me

I have been working in the area of financial statistics, quantitative finance, algorithmic trading, and digitisation of the finance industry for more than 15 years.

Joerg is the Action Chair of the European COST Action 19130 Fintech and Artificial Intelligence in Finance, an interdisciplinary research network combining 200+ researchers and 49 countries world-wide.

He was the director of studies for an executive education course on "Big Data Analytics, Blockchain and Distributed Ledger" for six consecutive courses, co-director of studies for "Machine Learning and Deep Learning in Finance" and has been the main organizer of an annual research conference series on Artificial Intelligence in Industry and Finance since 2016.

He is a founding associate editor of Digital Finance, an editor of Frontiers Artificial Intelligence in Finance and frequent reviewer for academic journals, among them the European Journal of Finance and the Journal of Investment Strategies.

In addition, he serves as an expert reviewer for the European Commission on the "Executive Agency for Small & Medium-sized Enterprises" and the "European Innovation Council Accelerator Pilot" programmes.

Previously he worked as an executive director at Goldman Sachs and Merrill Lynch, as quantitative analyst at AHL as well as a member of the senior management at Credit Suisse Group. Joerg is now also active at the intersection of academia and industry, focusing on the transfer of research results to the financial services sector in order to implement practical solutions.

My education:

  • Diploma in Business Mathematics, University of Ulm, Germany, 2002
  • Master of Science Mathematics, Syracuse University, USA, 2002
  • PhD in Financial Mathematics, ETH Zurich, Switzerland, 2007

Expertise

Business & Economics
Bitcoin
Cryptocurrency
Neural Networks
Statistical Analysis
Volatility Index
Engineering & Materials Science
Finance
Financial Markets
Time Series

Research

European COST (Cooperation in Science and Technology) Action 19130 Fintech and Artificial Intelligence in Finance

I am the Action Chair of the COST Action Fintech and AI in Finance. With a network of 49 countries and 200+ researchers, we are working on a substantial number of research topics, including, but not limited to: Reinforcement learning for trading, Sentiment analysis for Finance, Machine learning for Finance, Fintech applications, Blockchain and Cryptocurrencies.

Global reseearch cooperations

I have close research cooperations with academics from around the globe

  • Professor Ali Hirsa, Columbia University, US, jointly working on synthetic data generation, reinforcement learning for finance, explainable artificial intelligence, co-supervising MSc and PhD students
  • Professor Stephan Sturm, Worcester Polytechnic Institute, US, working on financial mathematics, including reinforcement learning for Finance, co-supervising MSc and PhD students
  • Dr. Alex Posth, Zurich University of Applied Sciences, Switzerland, working on self-play algorithms for Finance
  • Professor Stephen Chan, American University of Sharjah, UAE, working on blockchain and cryptocurrencies
  • Professor Saralees Nadarajah, Manchester University, UK, working on statistical properties of cryptocurrencies
  • Professor Codruta Mare, Babes-Bolyai University, Romania, working on sentiment analysis for Finance
  • Professor Ioana-Florina Coita, University of Oradea, Romania, working on sentiment analysis for Finance
  • Professor Branka Hadji Misheva, Bern University of Applied Sciences, Switzerland, working on reinforcement learning for finance and explainable AI for Finance
  • Professor Ronald Hochreiter, Vienna University of Business and Economics, Austria, working on AI and financial technology

PhD Co-supervision and PhD committees

I am involved in the PhD Co-Supervision and PhD committees of several universities in Europe and the US.

  • Patchara Santawisook, August 2022, "Price Impact of VIX Futures and Two Order Book Mean-Field Games", member of the PhD Committee, main supervisor: Prof. Dr. Stephan Sturm, Worcester Polytechnic University (WPI), US. Dissertation Committee: Dr. Stephan Sturm, WPI (Advisor), Dr. Marcel Y. Blais, WPI, Dr. Jörg Osterrieder, University of Twente, Dr. Andrew Papanicolaou, North Carolina State University, Dr. Qingshuo Song, WPI Dr. Frank Zou, WPI
  • Sebastian Singer, 2021 - 2025, co-advisor and member of the PhD Committee, main supervisor: Prof. Dr. Ronald Hochreiter, WU Vienna, Austria
  • Dr. Piotr Kotlarz, 2019 - 2023, local advisor, PhD at University of Liechtenstein
  • Dr. Branka Hadji Misheva, 2019 - 2023, local advisor, PhD at University of Pavia, Italy
  • Dr. Rui Li, 2020, PhD examiner, main supervisor: Saralees Nadarajah, University of Manchester, UK
  • Dr. Idika Okorie, 2019, PhD examiner, main supervisor: Saralees Nadarajah, University of Manchester, UK
  • Dr. M. Weibel, 2019, PhD examiner, main supervisor: Juri Hinz, University of Technology, Sydney, Australia

ING Group - University of Twente Cooperation - Associate Professorship Finance and Artificial Intelligence

I am working closing with ING Group, the Global Analytics team, on advanced, quantitative, data-driven research projects, relevant both for academia and industry.

1. Applications of synthetic data generation for Finance

Testing trading strategies robustness, comparing portfolio construction methods, estimating the risk of a portfolio or a strategy, alternative pricing and hedging of options and other derivatives, generating trading signals, detecting anomalies in fundamental data, with a particular focus on using generative adversarial networks.

Synthetic generator for (arbitrage-free) volatility surfaces

Synthetic data generators that are differentially private, i.e. do not leak information about the original data, and still have enough features

2. Research on risk management related topics

3. Privacy-enhancing techniques for storing and analysing confidential data

4. Federated Learning. This is a machine learning technique that trains an algorithm across multiple servers holding local data samples, without exchanging them. Research is needed into how this can be used in Finance applications, especially those that use confidential data.

5. Applications of Reinforcement learning in Finance. Existing applications include portfolio optimization and optimal trade execution. Further research is needed to extend this technique to other areas in finance.

6. The value of innovation projects in Finance. Innovative projects have a high-risk of failure and are often also focused on cost reduction and loss-avoidance topics. Therefore the impact on the P&L of the company is not immediately clear. The project is supposed to find ways of measuring the cost/benefit ratio and provide a conceptual approach.

7. The use of "meta labeling" technique (tailored to non-HFT strategies). The approach consist in building a secondary ML model that learns how to use a primary exogenous model. It can help build an ML system on top of a white box (like a fundamental model founded on economic theory). The advantages of the approach is that it uses a way higher signal to noise ratio than when applying ML directly to (very noisy) traditional financial data. 

8. Early warning systems for credit risk. Despite many years of research into credit risk, large and unexpected losses still happen frequently. Research on the causal relationships between market prices and external ratings as well as applying machine learning techniques and using new datasets for predicting downgrading and default  of loans is beneficial to reduce credit losses.

Publications

Recent
Liu, Y., Baals, L. J. , Osterrieder, J., & Hadji-Misheva, B. (2024). Network centrality and credit risk: A comprehensive analysis of peer-to-peer lending dynamics. Finance Research Letters, 63, Article 105308. Advance online publication. https://doi.org/10.1016/j.frl.2024.105308
Baals, L. J. , Osterrieder, J. R., Hadji-Misheva, B., & Liu, Y. (2024). Towards a new PhD Curriculum for Digital Finance. Open Research Europe, 4, Article 7. Advance online publication. https://doi.org/10.12688/openreseurope.16513.1
Coita, I. F., Belbe, S., Mare, C. , Osterrieder, J., & Hopp, C. (2023). Modelling taxpayers’ behaviour based on prediction of trust using sentiment analysis. Finance Research Letters, 58(Part C), Article 104549. https://doi.org/10.1016/j.frl.2023.104549
van Hillegersberg, J. , Osterrieder, J., Rabhi, F. , Abhishta, A., Marisetty, V. , & Huang, X. (2023). Preface. 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). https://doi.org/10.1007/978-3-031-31671-5
Jevtic, D., Deleze, R. , & Osterrieder, J. (2022). AI for trading strategies.
Hadji Misheva, B., Jaggi, D., Posth, J.-A., Gramespacher, T. , & Osterrieder, J. (2021). Audience-Dependent Explanations for AI-Based Risk Management Tools: A Survey. Frontiers in Artificial Intelligence, 4, Article 794996. https://doi.org/10.3389/frai.2021.794996

UT Research Information System

Google Scholar Link

Education

  • Reinforcement Learning for Finance (MSc)
  • Information Systems for the Financial Services Industry (MSc)
  • Applications of Artificial Intelligence in Business (MSc)

For students:

  • I have several graduation internships available (MSc and BSc), in cooperation with ING Group, Amsterdam. Programming experience needed.
  • If you are interested in writing your BSc or MSc thesis with me, please contact me directly. I have a substantial number of topics that would qualify for a thesis.

General topics for MSc and BSc thesis:

  • Quantitative Finance
  • Artificial Intelligence and Machine Learning
  • Cryptocurrencies
  • Reinforcement Learning
  • Other topics possible on request

Affiliated Study Programmes

Bachelor

Master

Courses Academic Year  2023/2024

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.
 

Courses Academic Year  2022/2023

Projects

Since 2015, I have worked on more than 30 research projects, mainly as project lead or principal investigator, funded by Europe Horizon 2020, Horizon Europe, Swiss National Science Foundation, Innosuisse and the Finance industry. The topics cover many aspects of quantitative, data-driven topics for Finance, ranging from trading strategies, efficient markets to machine learning and artificial intelligence in Finance, including latest developments such as blockchain, virtual currencies, Fintech and sustainable Finance.

Most notable international projects:

  • MSCA Industrial Doctoral Network on Digital Finance, Coordinator, 2024 - 2027, 4.5 Mio EUR
  • Narrative Digital Finance: a tale of structural breaks, bubbles & market narratives / Project leader / Swiss National Science Foundation / 236'118 CHF / August 2023 - August 2026
  • Cooperation ING Group - University of Twente
  • Action Chair COST Action 19130 Fintech and Artificial Intelligence, Horizon Europe
  • FIN-TECH – Financial Supervision and Technology Compliance Training Programme, EU Horizon 2020
  • Network-based credit risk models in P2P lending markets / Project leader / Swiss National Science Foundation / 347'836 CHF / August 2022 - August 2025

More details:

  • MSCA Industrial Doctoral Network on Digital Finance, Coordinator, 2024 - 2027, 4.5 Mio EUR
  • Strategic Research fund within the BMS Research Theme Emerging Technologies & Societal Transformations  “Digital Transformation of Finance and Society / PI / 20'000 EUR / January 2023 - December 2023
  • Narrative Digital Finance: a tale of structural breaks, bubbles & market narratives / Project leader / Swiss National Science Foundation / 236'118 CHF / August 2023 - August 2026
  • Network-based credit risk models in P2P lending markets / Project leader / Swiss National Science Foundation / 347'836 CHF / August 2022 - August 2025
  • Anomaly and fraud detection in blockchain networks / Project leader / Swiss National Science Foundation / 6'700 CHF / August 2022 - August 2023
  • Conferences on Artificial Intelligence in Finance / Innosuisse / Project leader / 80'000 CHF / Januar 2021 - July 2022
  • Strengthening Swiss Financial SMEs through Applicable Reinforcement Learning / Deputy project leader / Innosuisse / 312'315 CHF / April 2021 - July 2022
  • COST Action Fintech and Artificial Intelligence in Finance - Grant Holder / Project leader / Horizon Europe / 800'000 EUR / April 2020 - April 2025
  • Human-machine centered collaboration to crowdsource insights / Project leader / Innosuisse / 15'000 CHF / June 2021 - December 2021
  • Towards Explainable Artificial Intelligence and Machine Learning in Credit Risk Management / Project co-leader / Innosuisse / 282'969 CHF / Sept 2020 - Sept 2022
  • Decentralized financing of Fairtrade producers using a blockchain-based solution / Deputy project leader / Innosuisse / 250'539 CHF / August 2020 - January 2023
  • Advanced/AI-supported Rating Models for P2P systems / Project co-leader / Innosuisse / 15'000 CHF / July 2020 - July 2021
  • Currency hedging for SMEs and pension funds / Project leader / Innosuisse / 439'610 CHF / Oct 2018 - Oct 2021
  • Hybrid Approach for Robust Identification and Measurement of Investors Driving Corporate Sustainability and Innovation. Design of Policy Tools for Evaluating the Impact of Specific Investors and Assessing the Quality of Companies’ Investor Bases. / Project leader / Swiss National Science Foundation / 150'000 CHF / February 2020 - August 2021
  • Digitalisation non-bankable assets (specifically: art) / Deputy project leader / Innosuisse / 300k CHF / January 2020 - June 2020
  • Deep Learning & Neuronal Networks: Selbstständige KI-Agenten zur Entwicklung von neuartigen Handelsstrategien im Asset Management auf Basis von Self-Play / Deputy project leader / Innosuisse / 15'000 CHF / July 2019 - January 2020
  • Assessment of derivatives-based hedging solutions / Project co-leader / Swiss Asset Manager / 15'000 CHF / June 2021 - November 2021
  • Enhancing the Financing of Fairtrade Producers using Blockchain Technology / Innosuisse / Team member / 250'539 CHF/ August 2020 - January 2023
  • 6th European Conference on Artificial Intelligence in Finance and Industry 2021 / Project leader / 20'000 CHF / Industry funding / January 2021 - September 2021
  • 5th European Conference on Artificial Intelligence in Finance and Industry 2020 / Project leader / 20'000 CHF / Industry funding / January 2020 - September 2020
  • 4th European Conference on Artificial Intelligence in Finance and Industry 2019 / Project leader / 20'000 CHF / Industry funding / January 2019 - September 2019
  • 3th European Conference on Artificial Intelligence in Finance and Industry 2018 / Project leader / 20'000 CHF / Industry funding / January 2018 - September 2018
  • 2nd European Conference on Artificial Intelligence in Finance and Industry 2017 / Project leader / 20'000 CHF / Industry funding / January 2017 - September 2017
  • 1st European Conference on Artificial Intelligence in Finance and Industry 2016 / Project leader / 20'000 CHF / Industry funding /January 2016 - September 2016
  • FIN-TECH – Financial Supervision and Technology Compliance Training Programme / Project leader / 200'000 EUR / Europe Horizon 2020 / April 2018 - April 2021
  • Digitales Immobilien Dossier (DIGIM) / Project co-leader / Innosuisse / 204'012 CHF / November 2018 - April 2020
  • Swisscom E-Signatur TP Technik / Project leader / Swisscom / 80k CHF / January 2018 - December 2019
  • Blockchain and Virtual Currencies / Project co-leader / Swiss National Science Foundation / 100k CHF / January 2018 - December 2018
  • Large Scale Data-Driven Financial Risk Modelling / Team member / Innosuisse / 309'000 CHF / January 2017 - July 2019 /
  • Mathematics and Fintech: The next revolution in the digital transformation of the finance industry / Project leader / Swiss National Science Foundation / 300k CHF / January 2017 - December 2019 /
  • Swissnex Research Stay New York / Project leader / Swissnex / 10k CHF / July 2018
  • Quantitative trading strategies / Project leader / Industry funding / 80k CHF / April 2016 - December 2017
  • Long historical data for futures / Project leader / Industry funding / 20k CHF / April 2016 - December 2016
  • Automation and industrialization of quantitative research / Project leader / University funding / 10k CHF / April 2015 - December 2016
  • RENERG2 - RENewable enERGies in future energy supply / Innosuisse / Team member / 48'000 CHF / July 2013 - December 2016

Current Projects

In the press

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Contact Details

Visiting Address

University of Twente
Faculty of Behavioural, Management and Social Sciences
Ravelijn (building no. 10), room 3107
Hallenweg 17
7522NH  Enschede
The Netherlands

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Mailing Address

University of Twente
Faculty of Behavioural, Management and Social Sciences
Ravelijn  3107
P.O. Box 217
7500 AE Enschede
The Netherlands

Additional Contact Information

Office, 3rd floor, RA, facing the main square

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