Applied Machine Learning in Empirical Finance
A collaborative research initiative between University of Twente and Quoniam Asset Management, advancing the application of machine learning methods in portfolio optimization and risk management.
Project Overview
Bridging academic research and industry practice in quantitative finance
About the Project
This industry-funded PhD project, associated with the MSCA Doctoral Network "Digital Finance", started in December 2025 and investigates the application of advanced machine learning techniques to empirical problems in finance. The research focuses on developing novel approaches for portfolio optimization, risk management, and investment decision-making across multiple asset classes.
The collaboration brings together academic expertise from the University of Twente's Financial Engineering & Business Information Systems (FEBIS) group with practical insights from Quoniam Asset Management, one of Europe's leading quantitative asset managers.
Research Focus Areas
Asset Classes
Research Team
Joerg Osterrieder
Axel Gross-Klussmann
Xiaohong Huang
Dennis Hoffmann
Our Partners
Industry-University collaboration driving innovation
University of Twente
Financial Engineering & Business Information Systems (FEBIS)
The University of Twente is a leading Dutch technical university with strong expertise in data science, artificial intelligence, and financial engineering. The BMS Faculty (Behavioural, Management and Social Sciences) hosts research on quantitative methods in finance and economics.
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Quoniam Asset Management
Quantitative Research
Quoniam Asset Management is one of Europe's leading quantitative asset managers, headquartered in Frankfurt, Germany. With a rigorous research-driven approach, Quoniam develops and implements systematic investment strategies across asset classes.
Visit Quoniam WebsiteResearch Networks
Part of a broader ecosystem of academic and industry collaboration
COST Action: Fintech and AI in Finance
European research network advancing the understanding of financial technology and artificial intelligence applications in financial services.
Learn more
MSCA Digital Finance
Marie Skłodowska-Curie Actions network focused on digital transformation in financial services and training the next generation of researchers.
Learn moreDigital-AI-Finance
Open research organization on GitHub promoting open science and reproducible research in machine learning for finance.
View OrganizationProject Timeline
Key milestones and expected deliverables
Project Launch
Official start of the PhD research project. Dennis Hoffmann begins his industry PhD at Quoniam Asset Management in collaboration with University of Twente.
Literature Review (In Progress)
Comprehensive review of ML methods in portfolio optimization and risk management. Identification of research gaps.
First Paper (Planned)
Development and submission of first research paper on ML-based portfolio optimization methods.
Core Research (Planned)
Deep investigation into risk management applications, novel methodology development, and additional publications.
Industry Application & Validation
Practical implementation and validation of research findings at Quoniam.
Thesis Completion (Planned)
Thesis writing, final publications, industry validation, and PhD defense.
Expected Outputs
5+ Academic Publications
Peer-reviewed papers in finance and machine learning journals.
Open Source Code
Reproducible implementations released under MIT license.
Industry Applications
Practical methodologies implemented in production environments.
PhD Thesis
Comprehensive dissertation on ML applications in empirical finance.
Interested in Our Research?
Explore our open research questions and get involved in advancing ML in finance.