Prof. Dr. Jörg Robert Osterrieder


Prof. Dr. Jörg Robert Osterrieder Dozent

  • Address Berner Fachhochschule
    Business School
    Institut Applied Data Science & Finance
    Brückenstrasse 73
    3005 Bern


  • Professor of Sustainable Finance

  • Action Chair COST Action 19130 Fintech and Artificial Intelligence in Finance, 200+ researchers from 49 countries

  • Principal Investigator SNF project "Anomaly and fraud detection in blockchain networks"

  • Co-Principal Investigator SNF project "Network-based credit risk models in P2P lending markets"

  • External reviewer Horizon Europe: European Innovation Council Accelerator Pilot

  • Coordinator Marie Sklodowska-Curie Action for an Industrial Doctoral Network on Digital Finance

  • Principal Investigator SNF project: Narrative Digital Finance

  • Associate Professor Fintech and Artificial Intelligence, University of Twente, Netherlands

  • External reviewer H2020: Executive Agency for Small & Medium-sized Enterprises


  • Master in Business Administration

  • Master in Business Informatics

  • Bachelor in International Business Administration

  • Digital Finance

  • Artificial Intelligence for Finance

  • Machine Learning for Finance

  • Sustainable Finance


  • Artificial Intelligence in Finance

  • Machine Learning in Finance

  • Sustainable Finance

  • Digital Finance


  • Joerg Osterrieder is Professor of Sustainable Finance at Bern Business School, Switzerland and Associate Professor of Finance and Artifcial Intelligence at the University of Twente, Netherlands. He has 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 globally. He was the director of studies for an executive education course on "Big Data Analytics, Blockchain and Distributed Ledger", 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.
    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.
  • 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. 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.
  • Research 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:
    * 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, Swiss National Science Foundation
  • More details:
    * 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
  • 2022 - Professor of Sustainable Finance Bern Business School. Switzerland
  • 2021 - Associate Professor of Finance and Artificial Intelligence University of Twente, Netherlands
  • 2015 - 2022 Professor of Finance and Risk Management ZHAW. Switzerland
  • 2012 - 2015 Portfolio Management and Quantitative Analysis Man Investments, Pfäffikon, Switzerland
  • 2012 - 2012 Senior Vice President, Regulatory Projects Credit Suisse Group, Zürich, Switzerland
  • 2009 - 2012 Vice President Global Markets Goldman Sachs, London, UK
  • 2007 - 2009 Associate Global Markets Merrill Lynch, London, UK
  • 2003 - 2007 PhD Financial Mathematics ETH Zürich, Switzerland
  • 1998 - 2002 MSc Business Mathematics University of Ulm, Germany
  • 2000 - 2002 MSc Mathematics Syracuse University, US
  • 2018 CAS University Didactics PH ZH, Zürich, Switzerland


  • Action Chair COST Action 19130 Fintech and Artificial Intelligence in Finance (300 researchers from 51 countries globally)

  • Coordinator Marie Sklodowska-Curie Action for an Industrial Doctoral Network on Digital Finance (70 researchers from 18 institutions, academy and industry)


  • Osterrieder, Jörg R; Rheinländer, Thorsten; Arbitrage opportunities in diverse markets via a non-equivalent measure change,Annals of Finance,2,3,287-301,2006,Springer-Verlag
    Lorenz, Julian; Osterrieder, Jörg; ,Simulation of a limit order driven market,The Journal Of Trading,4,1,23-30,2008,Institutional Investor Journals Umbrella
    Osterrieder, Jörg Robert; ,"Arbitrage, the limit order book and market microstructure aspects in financial market models",2007,"Diss., Eidgenössische Technische Hochschule ETH Zürich, Nr. 17121
    Osterrieder, Joerg; Lorenz, Julian; ,A statistical risk assessment of Bitcoin and its extreme tail behavior,Annals of Financial Economics,12,01,1750003,2017,World Scientific Publishing Company
    Osterrieder, Joerg; A Dynamic Market Microstructure Model with Insider Information and Order Book,Available at SSRN 676028,2005,
    Osterrieder, Joerg; The statistics of bitcoin and cryptocurrencies,Available at SSRN 2872158,2016,
    Osterrieder, Joerg; A Theoretical Model of the Limit Order Book and Some Applications,Available at SSRN 881274,2006,
    Osterrieder, Joerg; Strika, Martin; Lorenz, Julian; ,Bitcoin and cryptocurrencies—not for the faint-hearted,International Finance and Banking,4,1,56,2017,
    Chan, Stephen; Chu, Jeffrey; Nadarajah, Saralees; Osterrieder, Joerg; ,A statistical analysis of cryptocurrencies,Journal of Risk and Financial Management,10,2,12,2017,MDPI
    Rohrbach, Janick; Suremann, Silvan; Osterrieder, Joerg; Momentum and trend following trading strategies for currencies revisited-combining academia and industry,Available at SSRN 2949379,,,,2017,
    Chu, Jeffrey; Chan, Stephen; Nadarajah, Saralees; Osterrieder, Joerg; GARCH modelling of cryptocurrencies,Journal of Risk and Financial Management,10,4,17,2017,MDPI
    Gabler, Andreas; Wiegand, Martin; Osterrieder, Joerg; ,"Pricing, Loss and Sensitivity Analysis of Barrier Options via Regression",Available at SSRN 3194111,,,,2018,
    Gabler, Andreas; Perez, Dominique; Sutter, Ueli; Kucharczyk, Daniel; Osterrieder, Joerg; Reitenbach, Markus; Pattern Learning Via Artificial Neural Networks for Financial Market Predictions,Availa
    Kucharczyk, Daniel; Osterrieder, Joerg; Rudolf, Silas; Wittwer, Daniel; ,Neural Networks and Arbitrage in the VIX–A Deep Learning Approach for the VIX,Available at SSRN 3305686,,,,2018,
    Osterrieder, Joerg; Vetter, Lars; Röschli, Kevin; ,The VIX volatility index-A very thorough look at it,Available at SSRN 3311727,2019,
    Giudici, Paolo; Hochreiter, Ronald; Osterrieder, Jörg; Papenbrock, Jochen; Schwendner, Peter; AI and financial technology,Frontiers in Artificial Intelligence,2,,25,2019,Frontiers Media SA
    Osterrieder, Jörg; Barletta, Andrea; ,Editorial on the Special Issue on Cryptocurrencies,Digital Finance,1,1,1-4,2019,Springer International Publishing
    Osterrieder, Joerg; Kucharczyk, Daniel; Rudolf, Silas; Wittwer, Daniel; ,Neural networks and arbitrage in the VIX,Digital Finance,2,1,97-115,2020,Springer International Publishing
    Choudary, Jabar; Osterrieder, Joerg; ,Machine Learning Tools for Probability of Default and Rating Downgrades of Corporate and Government Bonds,SSRN ELibrary,,,3461558,2019,Elsevier
    Osterrieder, Joerg; Barletta, Andrea; ,Special Issue on Cryptocurrencies,2020,
    Hirsa, Ali; Osterrieder, Joerg; Misheva, Branka Hadji; Cao, Wenxin; Fu, Yiwen; Sun, Hanze; Wong, Kin Wai; ,The VIX index under scrutiny of machine learning techniques and neural networks,arXiv prep
    Misheva, Branka Hadji; Osterrieder, Joerg; Hirsa, Ali; Kulkarni, Onkar; Lin, Stephen Fung; ,Explainable AI in credit risk management,arXiv preprint arXiv:2103.00949,2021,
    Posth, Jan-Alexander; Kotlarz, Piotr; Misheva, Branka Hadji; Osterrieder, Joerg; Schwendner, Peter; ,The applicability of self-play algorithms to trading and forecasting financial markets,Frontiers
    Odermatt, Leander; Beqiraj, Jetmir; Osterrieder, Joerg; ,Deep Reinforcement Learning for Finance and the Efficient Market Hypothesis,Available at SSRN 3865019,2021,
    Hirsa, Ali; Osterrieder, Joerg; Hadji-Misheva, Branka; Posth, Jan-Alexander; ,Deep reinforcement learning on a multi-asset environment for trading,arXiv preprint arXiv:2106.08437,2021,
    Eckerli, Florian; Osterrieder, Joerg; ,Generative Adversarial Networks in finance: an overview,arXiv preprint arXiv:2106.06364,2021,
    Samuel, Rikli; Nico, Bigler Daniel; Moritz, Pfenninger; Joerg, Osterrieder; ,Wasserstein GAN: Deep Generation applied on Bitcoins financial time series,arXiv preprint arXiv:2107.06008,2021,
    Pfenninger, Moritz; ,Generative Adversarial Network For synthetic data on Bitcoin returns,Available at SSRN 3864867,2021,
    Rosolia, Antonio; Osterrieder, Joerg; ,Analyzing Deep Generated Financial Time Series for Various Asset Classes,Available at SSRN 3898792,2021,
    Hadji Misheva, Branka; Jaggi, David; Posth, Jan-Alexander; Gramespacher, Thomas; Osterrieder, Joerg; Audience-Dependent Explanations for AI-Based Risk Management Tools: A Survey,Frontiers in Artif

  • Pfenninger, Moritz; Bigler, Daniel Nico; Rikli, Samuel; Osterrieder, Joerg; Wasserstein gan: Deep generation applied on financial time series,Available at SSRN 3885659,2021,
    Bucher, Chris; Osterrieder, Joerg; Risk Parity for Multi-Asset Futures Allocation–A Practical Analysis of the Equal Risk Contribution Portfolio,Available at SSRN 3858730,2021,
    Farokhnia, Kia; Osterrieder, Joerg; High-Frequency Causality between Stochastic Volatility Time Series: Empirical Evidence,Available at SSRN 4087569,2022,
    Farokhnia, Kia; Osterrieder, Joerg; High-Frequency Causality in the VIX Index and its derivatives: Empirical Evidence,arXiv preprint arXiv:2206.13138,2022,
    Zejnullahu, Frensi; Moser, Maurice; Osterrieder, Joerg; ,Applications of Reinforcement Learning in Finance--Trading with a Double Deep Q-Network,arXiv preprint arXiv:2206.14267,2022,
    Fu, Weilong; Hirsa, Ali; Osterrieder, Jörg; Simulating financial time series using attention,arXiv preprint arXiv:2207.00493,2022,
    Henrici, Andreas; Osterrieder, Jörg; "Artificial Intelligence in Finance and Industry: Highlights from 6 European COST Conferences",Frontiers in Artificial Intelligence,187,,Frontiers


  • Bachelier Finance Society

  • Kickstart AI - National Initiative to promote Artificial Intelligence in the Netherlands

  • American Finance Association