Prof. Barry Quinn

Professor of Finance and Financial Technology

Prof. Barry Quinn

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Personal Statement

Professor Barry Quinn is Professor of Finance & Financial Technology at Ulster University Business School and Director of the Centre for Finance and Responsible Technology. The Centre is guided by three pillars: statistical rigour and intellectual humility; practical industry relevance; and responsible algorithmic innovation.

Barry is a Chartered Statistician and views econometrics as an applied statistical science. His work combines applied econometrics and causal inference with trustworthy machine learning and computational approaches to produce decision-relevant evidence for markets, risk, market integrity, and regulatory compliance. In practice, that means making assumptions explicit, quantifying uncertainty, stress-testing results, and being clear about limits—so we can say plainly when evidence does (and does not) support confident conclusions.

His research spans causal policy evaluation, algorithmic trading risk detection, and trustworthy AI methods, and is collaborative and interdisciplinary—bridging finance, statistics, computer science, and law.

His research sits at the intersection of finance, statistical learning, and responsible use of algorithms, with a focus on markets and institutions, risk measurement, and evidence for regulation and compliance. He works collaboratively across disciplines and with external partners, aiming to reduce avoidable complexity and produce analysis that stands up under operational and regulatory scrutiny.

Before entering academia, Barry worked in financial markets, specialising in currency trading and liquidity management. He holds a PhD in Finance and an MSc in Artificial Intelligence (Distinction) from Queen’s University Belfast. He teaches across quantitative finance, econometrics, and AI applications in finance, emphasising ethical practice, reproducibility, and critical thinking.

Education and Professional Qualifications

Qualification Institution Year
B.Sc.(Hons) Accounting and Finance Queen’s University Belfast 1995
MSc Quantitative Finance RMIT University Melbourne 2006
Ph.D. Finance Queen’s University Belfast 2012
Chartered Statistician Royal Statistical Society 2019
Advanced Data Science Professional Royal Statistical Society 2023
MSc Artificial Intelligence (Distinction) Queen’s University Belfast 2025

Teaching

I prepare students to reason carefully about finance and technology—teaching them to make assumptions explicit, quantify uncertainty, and be honest about what evidence does and does not support. My goal is to develop analysts who are technically capable, intellectually honest, and able to produce work that is transparent and reproducible. These qualities—rigour, humility, and critical thinking—equip students for roles where decisions carry real consequences.

I have extensive teaching experience at both undergraduate and postgraduate levels, specialising in:

  1. Algorithmic Trading and Investment: A postgraduate course grounded in the López de Prado framework for machine learning in financial markets. Covers the full pipeline from financial data structures and feature engineering to portfolio construction, backtesting, and strategy evaluation—with emphasis on avoiding the methodological pitfalls (backtest overfitting, data snooping, and leakage) that plague practitioner and academic research alike.

  2. Financial Econometrics: Taught as an applied statistical science rather than a recipe book. Students learn to treat econometric models as tools for quantifying uncertainty and stress-testing assumptions—not as black boxes that produce publishable numbers. The course confronts the replication crisis and the statistical practices that drive it, asking students to be explicit about what their models can and cannot establish.

  3. FinTech and Data Science (Ulster University): The disciplined study of variation and uncertainty in financial data—covering return predictability, volatility modelling, factor models, and ML for cross-sectional analysis. Emphasises distinguishing signal from noise, proper model validation, and intellectual humility about the limits of prediction in noisy markets. Supported by an open companion textbook, Statistical Science for Finance: Rigorous Methods for Technology-Enabled Markets.

  4. Trading Principles (Queen’s University Belfast): A postgraduate learning-by-doing course in market microstructure, built around approximately 18 live in-class trading simulations using UpTick technology integrated with Bloomberg Terminal data. Students assume distinct industry roles—market maker, speculator, liquidity trader—and their collective decisions endogenously determine prices and liquidity, making core concepts such as the law of one price, price formation, market efficiency, and event arbitrage directly observable consequences of their own behaviour. Simulation performance counts toward the final grade, removing the gap between doing and understanding. The course pairs foundational academic work (Kyle 1985; Glosten-Milgrom 1985) with industry research to bridge theory and practice.

Teaching Publications

  • Quinn, Barry (2026). Statistical Science for Finance: Rigorous Methods for Technology-Enabled Markets. Open educational resource and companion textbook for FIN306, Ulster University Business School. https://quinfer.github.io/financial-data-science/

  • Quinn, Barry, Hanna, Alan, Gallagher, Aine (2018). Queen’s Student Managed Fund: Investing in the Student Experience. Reflections, 27, pp. 16–17.

Research

I have published fourteen peer-reviewed academic papers (1 ABS4, 11 ABS3s, and 2 ABS2s), three commissioned research reports, and two statistical software packages. My research sits at the intersection of finance, statistical learning, and responsible use of algorithms—with a focus on markets and institutions, risk measurement, and evidence for regulation and compliance. The work is collaborative, crossing disciplines and industry boundaries, and aims to reduce avoidable complexity: producing analysis that is transparent, reproducible, and stands up under operational and regulatory scrutiny.

Research Expertise

Three methodological strands recur across my programme. The first is trustworthy machine learning for market integrity and risk. With colleagues at Queen’s University Belfast I have developed representation-learning methods for detecting market manipulation in high-frequency equity data — a dual-branch self-supervised framework combining frequency-informed anomaly synthesis with domain-specific features (Dai, Quinn, Kearney, Liu, Spence, Rafferty & Wang, under review at Information Processing and Management), and a signal-amplification technique for rare-event manipulation detection (Dai, Quinn, Kearney & Wang, under review at Economics Letters). Related work applies transformer models to sentiment-conditioned crash-risk modelling (Birem, Abidi Perier, Quinn & Kearney, under review at the European Journal of Operational Research). The methodological commitment running through this strand is that model performance and model trustworthiness are separable properties, and both must be evidenced before machine learning is deployed in operational or regulatory settings.

The second strand is computer vision for socio-economic measurement — using vision models on real-world imagery to produce auditable indicators of phenomena that are otherwise hard to quantify consistently. This includes the Hannon, French, Quinn & O’Hagan geospatial study of vehicle crime in Northern Ireland (submitted to Insurance: Mathematics and Economics), which extracts environmental features from street-level imagery, and the hierarchical flag-classification programme developed during my MSc AI dissertation at Queen’s (4,501-image Northern Ireland dataset; 70→16→7 hierarchy-aware taxonomy; ViT-H-14 baseline at 94.78% on the 7-category task), currently in manuscript preparation. Both projects treat vision pipelines as instruments of measurement, and are evaluated on measurement-science grounds rather than on benchmark accuracy alone.

The third strand is causal and statistical evidence for governance and regulation. This covers the Kearney, Quinn & Pramanick study of innovation signals and strategic exits in computational approaches to financial regulation (under review at the Journal of Business Venturing); the Zhang, Quinn & Sheenan analysis of ownership dynamics, risk and regulation in Chinese banking (Centre for Responsible Banking & Finance Working Paper 25-017); and the collaborative doctoral partnerships with Pytillia, Napier AI and Funds Axis that apply causal-inference and econometric methods to live regulatory and compliance problems. In this strand the methodological priority is that evidence survive operational and regulatory scrutiny — assumptions explicit, uncertainty quantified, and claims proportionate to what the data can support.

Peer-Reviewed Publications

  • Wang, Hui, Dai, Yongsheng, Spence, Ivor, Rafferty, Karen, Quinn, Barry, Huang, Ji (2025). TDSRL: Time Series Dual Self-Supervised Representation Learning for Anomaly Detection from Different Perspectives. IEEE Internet of Things Journal

  • McKillop, Donal, Liu, Kailong, Quinn, Barry, Peng, Qiao (Forthcoming). Modelling and Predicting Credit Union Failures. International Journal of Forecasting (ABS3)

  • Liu, Weilong, Zhang, Yong, Liu, Kailong, Quinn, Barry, Yang, Xingyu, Peng, Qiao (2024). Evolutionary Multi-Objective Optimisation for Large-Scale Portfolio Selection With Both Random and Uncertain Returns. IEEE Transactions on Evolutionary Computation (ABS4)

  • Bouri, E., Quinn, B., Sheenan, L. & Tang, Y. (2024). Investigating extreme linkage topology in the aerospace and defence industry. International Review of Financial Analysis (ABS3)

  • Quinn, Barry, Gallagher, Ronan, Kuosmanen, Timo (2023). Lurking in the shadows: The impact of CO2 emissions target setting on carbon pricing in the Kyoto agreement period. Energy Economics (ABS3)

  • Liu, Jiadong, Papailias, Fotis, Quinn, Barry (2021). Direction-of-change forecasting in commodity futures markets. International Review of Financial Analysis (ABS3)

  • Gallagher, Ronan, Quinn, Barry (2020). Regulatory own goals: The unintended consequences of economic regulation in professional football. European Sport Management Quarterly (ABS3)

  • McKillop, Donal, French, Declan, Quinn, Barry, Sobiech, Anna L, Wilson, John OS (2020). Cooperative financial institutions: A review of the literature. International Review of Financial Analysis (ABS3)

  • Quinn, Barry, Hanna, Alan, MacDonald, Fred (2018). Picking up the pennies in front of the bulldozer: The profitability of gilt based trading strategies. Finance Research Letters (ABS2)

  • McKillop, Donal G, Quinn, Barry (2017). Irish credit unions: Differential regulation based on business model complexity. The British Accounting Review (ABS3)

  • Ayadi, Rym, Naceur, Sami Ben, Casu, Barbara, Quinn, Barry (2016). Does Basel compliance matter for bank performance? Journal of Financial Stability (ABS3)

  • Glass, J, McKillop, Donal, Quinn, Barry (2015). Modelling the Performance of Irish Credit Unions, 2002-2010. Financial Accountability & Management (ABS3)

  • McKillop, Donal G, Quinn, Barry (2015). Web adoption by Irish credit unions: Performance implications. Annals of Public and Cooperative Economics (ABS2)

  • Glass, J Colin, McKillop, Donal G, Quinn, Barry, Wilson, John (2014). Cooperative bank efficiency in Japan: a parametric distance function analysis. The European Journal of Finance (ABS3)

  • Quinn, Barry, McKillop, Donal (2009). Internet banking and Irish credit unions. International Journal of Cooperative Management (ABS2)

  • Quinn, Barry, McKillop, Donal (2009). Cost performance of Irish credit unions. Journal of Cooperative Studies (ABS2)

Software Publications

Software Publications
Package Year Description Metrics
Time Series Econometrics (tsfe) 2022 R Package for time series analysis GitHub stars
Financial Machine Learning (fml) 2020 R Package for financial ML GitHub stars

Working Papers

  • Birem, AbderRaouf, Abidi Perier, Zineb, Quinn, Barry, Kearney, Fearghal (Under Review). Transformer-Based Sentiment Analysis for Stock Market Crash Risk. Under Review at European Journal of Operational Research. Manuscript EJOR-S-26-00902.

  • Dai, Yongsheng, Quinn, Barry, Kearney, Fearghal, Wang, Hui (Submitted). Amplifying Market Manipulation Detection Signals. Submitted to Economics Letters. Manuscript EL66561.

  • Dai, Yongsheng, Quinn, Barry, Kearney, Fearghal, Liu, Weilong, Spence, Ivor, Rafferty, Karen, Wang, Hui (Submitted). Detecting Market Manipulation with Dual-branch Self-supervised Learning: A Unified Framework Integrating Frequency-informed Anomaly Synthesis and Domain-Specific Features. Submitted to Information Processing and Management. Manuscript IPM-D-25-06138.

  • Zhang, Ying (Veronica), Quinn, Barry, Sheenan, Lisa (2025). Ownership Dynamics, Risk and Regulation in Chinese Banking: New Evidence. Centre for Responsible Banking & Finance Working Paper Series, WP No. 25-017.

  • Kearney, Fearghal, Quinn, Barry, Pramanick, Abhishek (Under Review at Journal of Business Venturing). Innovation Signals and Strategic Exits: How Technological Readiness Shapes Outcomes in Computational Approaches to Financial Regulation.

  • Hannon, James (Corresponding Author), French, Declan, Quinn, Barry, O’Hagan, Adrian (Submitted). Geospatial modeling of vehicle crime in Northern Ireland using computer vision to identify environmental factors. Submitted to Insurance: Mathematics and Economics. Manuscript IME-D-25-00419.

  • Quinn, Barry (2025). Hierarchical Flag Classification through Economic Domain Knowledge: A Vision Transformer Approach for Cultural Symbol Recognition. MSc thesis and reproducible research codebase (economic-flag-classification), Queen’s University Belfast; manuscript for journal submission in preparation.

  • Quinn, Barry, Gallagher, Ronan. Great Expectations: Managerial Turnover and Market Expectation in Association Football.

Research Reports

  • Bryon Graham, Barry Quinn (2019). Price comparison and web analytics (commissioned by InvestNI).
  • Bryon Graham, Barry Quinn (2017). Machine learning and predictive analytics in the mall retail business (commissioned by InvestNI).
  • Fearghal Kearney, Barry Quinn (2020). The theoretical foundations of value at risk modelling (commissioned by InvestNI and Funds Axis Ltd).
  • French, Declan, McKillop, Donal, Quinn, Barry (2018). Landscape review of Northern Ireland Credit Union Sector (commissioned by the NI Department of Communities and Rural Affairs).
  • McKillop, Donal, Quinn, Barry (2012). Report of the Irish Commission on Credit Unions — An Efficiency Study (4* REF 2014 Impact Case).

Research Impact and Knowledge Transfer

  1. Three PhD Scholarships — Centre for Finance and Responsible Technology (Department of the Economy NI, £360K, 2025), including two collaborative doctoral partnerships with local firms: Pytillia and Napier AI.
  2. Understanding and Enhancing regulatory compliance in the Investment Management industry using AI with Funds Axis Ltd and Momentum 1.0 (UKFin+ / UKRI, November 2024 – November 2025).
  3. Anomaly detection of large heterogeneous trading transaction and communication data with Citigroup Belfast and Momentum 1.0 (2022–2023).
  4. AI and Advanced Retail Analytics with Pearlai Ltd and Dr Byron Graham (KTP, 2017–2019).
  5. E.S.G. Fair Value Analytics with Research Associates Dr Lisa Sheenan and Dr Byron Graham (KTP, 2021).
  6. Tail Risk Analytics, Stress Testing and Scenario Analytics with Funds Axis Ltd, Dr Fearghal Kearney and Dr Colm Kelly (KTP, 2021–2023).
  7. Financial Conduct Authority Tech Sprint Mentor (2023–present).
  8. AI and the Future of Financial Regulation with Fearghal Kearney and Abhishek Pramanick, published in The Economic Observatory (2023).
  9. Hierarchical Flag Classification for Cultural-Symbol Monitoring (QUB MSc AI project, 2024–2025): developed a 4,501-image Northern Ireland street-scene dataset and a hierarchy-aware taxonomy (70→16→7) with a ViT-H-14 baseline achieving 94.78% on the 7-category task; code and methods are documented in economic-flag-classification.

Completed PhD Supervisions

  1. Dr Jiadong Liu (graduated 2018): Momentum in Empirical Asset Pricing (Principal Supervisor).
  2. Dr Ashleigh Neil (graduated 2019): Law and Financial Stability (Principal Supervisor).
  3. Dr Colm Kelly (graduated 2021): Machine Learning in Empirical Asset Pricing (Principal Supervisor).
  4. Veronica Zhang (2024): Capital Policy and State Sponsorship in Chinese Banking (Principal Supervisor).
  5. Dr Kevin Johnson (graduated 2019): A Case Study in Industrial Consolidation — The Irish Credit Union Sector (Co-Supervisor).
  6. Dr Qiao (Olivia) Peng (graduated 2021): US Credit Union Mergers — Causes and Consequences (Co-Supervisor).

Current PhD Supervisions

  1. Fei Li: Sustainable Investing, Reporting and Gender Diversity (fully-funded QBS scholarship) (Principal Supervisor).
  2. Abhishek Pramanick: AI and the Future of Financial Regulation (fully-funded QBS scholarship) (Principal Supervisor).
  3. Dongwei (Jeffrey) Li: The Economics of AI Patents and Productivity in Finance (fully-funded DofE scholarship) (Principal Supervisor).
  4. Yuqi Ding: The Economics of Generative AI in Finance (fully-funded QBS scholarship) (Principal Supervisor).
  5. Yongsheng Dai: Market Manipulation and Financial Anomaly Detection (fully-funded PWC scholarship) (Co-Supervisor).
  6. Brandon Cochrane: Economic Cost of Cultural Displays in Northern Ireland (fully-funded DofE CAST scholarship) (Co-Supervisor).

Visiting PhD Supervision

  1. Weilong Liu (2022; Lingnan University College of Sun Yat-sen University, Guangzhou): Market Manipulation and AI Anomaly Detection.
  2. James Hannon (2023; University College Dublin): Leveraging Computer Vision to Understand and Enhance Insurance Pricing.
  3. Birem Abderraouf (2025; UPEC Paris): Generative AI in Capital Markets.

Conference Presentations

  • Invited Speaker, Dynamic Signal Weighting of Performance Signals for Managerial Turnover Decisions: Evidence from Professional Football, INFINIT Conference, Edinburgh Napier University, Jun 2025.
  • Invited Talk, Rethinking Research Impact: Combining Effect Sizes and Economic Significance in Finance, Royal Statistical Society Annual Conference, Brighton UK, Sep 2024.
  • Keynote Speaker, Estimating Systemic Risk, Irish Finance Association, Maynooth University, Ireland, April 2023.
  • Invited Talk, Teaching Data Science in the Age of FinTech, Royal Statistical Society Annual Conference, Aberdeen UK, Sep 2022.
  • Invited Talk, Carbon Pricing and Machine Learning, Multidisciplinary Workshop on Fintech, Islamic Finance and Sustainability (online), Hamad Bin Khalifa University, Qatar, Nov 2022.
  • Invited Speaker, Understanding Fintech and Financial Stability, International Workshop on Financial System Architecture and Stability, Bayes Business School, London, Sep 2018.
  • Invited Speaker, Systemic Risk and Basel Compliance, British Accounting and Finance Association Annual Conference, London, Apr 2018.
  • Invited Speaker, Differential Regulation of Irish Credit Unions: Does One Size Fit All?, 2nd Conference on Contemporary Issues in Banking, Centre for Responsible Banking and Finance, St Andrews, Dec 2017.
  • Invited Speaker, Business Model Diversity, Efficiency and Productivity of Cooperatives, European Workshop in Efficiency and Productivity Analysis, Aalto University, Finland, Jun 2017.
  • Invited Panellist, Statistical Inference and Credibility in Finance, Emerging Scholars in Banking and Finance, Bayes Business School, London, Dec 2016.
  • Invited Speaker, Capital Regulation Compliance and the Performance of European Banks, International Workshop on Financial System Architecture and Stability, HEC Montreal, Aug 2016.
  • Participant, Bloomberg Annual Educational Symposium, Bloomberg London HQ, Sep 2015.

Research Grant Income

Research Grant Income
Source Role Start End People Title Full Economic Costs (ÂŁ) Type
(Department of the Economy NI) PI 2025 NA Pytillia Napier AI Three PhD scholarships to support the Centre for Finance and Responsible Technology (including two collaborative doctoral partnerships) ÂŁ360,000 Research
(UKFin+/EPSRC) PI 2024 2025 Jesus Del Rincon Martinez Abhishek Pramanick Darren Burrows (CEO of Funds Axis) Leveraging AI to understand and improve regulatory compliance in the Investment Management Industry ÂŁ100,000 Research
DofE CAST Award NI Co-I 2023 NA Declan French Exploring the Welfare Cost of Cultural Displays in Northern Ireland using multimodal Generative AI ÂŁ70,000 Research
Innovate UK PI 2022 2023 Lisa Sheenan Byron Graham E.S.G fair value analytics platform: using state-of-the-art financial data science and business analytics to design a fair-value ESG prediction engine ÂŁ173,000 Research
Innovate UK PI 2021 2023 Fearghal, Kearney Regulatory technology and portfolio analytics using state-of-the-art econometrics and financial machine learning ÂŁ173,000 Research
Innovate UK PI 2018 2021 Byron, Graham Designing and deploying a retail analytics platform using advanced analytics and machine learning ÂŁ165,000 Research
DofE CAST Award NI Co-I 2021 NA Donal McKillop PhD investigation into how AI innovation affect a highly valued financial service provision experience ÂŁ70,000 Research
Phoenix Natural Gas Ltd PI 2014 2015 Alan Hanna Fotis Papailias Forecasting daily demand for natural gas in Northern Ireland ÂŁ15,000 Consulting
DofE Co-I 2016 2018 Donal McKillop Declan French Landscape review of Northern Ireland Credit Unions ÂŁ32,000 Consulting
InvestNI Co-I 2018 NA Byron Graham Review of state-of-the-art machine learning in the context of retail analytics and monitoring ÂŁ5,000 Consulting
InvestNI Co-I 2019 2019 Byron Graham Review of AI and web analytics for price comparison ÂŁ5,000 Consulting
InvestNI Co-I 2021 2021 Fearghal Kearney Review of Value at Risk analytics at the intersection of econometrics and machine learning ÂŁ5,000 Consulting
QBS CEBR PI 2016 2019 Institute of Directors Estimating the costs and benefits of corporation tax policy change in Northern Ireland ÂŁ3,500 Research

Total Research Income: approximately ÂŁ1,176,500 in direct awards as PI or Co-I across 13 projects (source: data/Grant_income.csv).

Citizenship

Academic Service

  • Director, Centre for Finance and Responsible Technology, Ulster University Business School, 2025–.
  • Co-founder, Finance and AI Research Lab (with Dr Fearghal Kearney), Queen’s University Belfast, 2022–2024.
  • Lead Developer, Queen’s Business School Remote Analytics Lab Platform (Q-RaP), 2021–2024.
  • QUB Academic Lead, Steering Group for Northern Ireland Global Centre in Secure Connected Intelligence for Regulatory Technology in Finance, 2022–2024.
  • Programme Director, MSc Quantitative Finance, Queen’s University Belfast, 2018–2022.
  • Senior Research Fellow (Sabbatical), International Research Centre on Cooperative Finance, HEC Montreal University, Canada, May–September 2018.
  • Programme Director, MSc Computational Finance & Trading, Queen’s University Belfast, 2014–2018.
  • Co-founder, Queen’s Student Managed Fund, 2012–2024.
  • Implementation Team Member, Bloomberg Trading Room, Queen’s University Belfast.
  • External Grant Reviewer, UKFin+ (UKRI specialist funded project) — reviewed feasibility grant application (ÂŁ100K) for financial services innovation research, 2024.
  • Organiser, Symposium on AI and the Future of Financial Regulation, Queen’s University Belfast, November 2023.
  • Organiser, Symposium on Safety and Assurance in Finance, Queen’s Business School, November 2024.
  • Chair, Panel Debate on “Digital Regulation: Shaping Digital Markets and Safeguarding Consumer Rights in Northern Ireland”, Northern Ireland Competition Forum, May 2024.

Professional Accreditations

  • Chartered Statistician, Royal Statistical Society (2019).
  • Advanced Data Science Professional, Royal Statistical Society (2023).

Awards and Recognition

Professional Experience

Professional Experience
Period Position Institution
**2024 - Present** Professor of Finance and Financial Technology Ulster University Business School
**2024 - Present** Director, Centre for Finance and Responsible Technology Ulster University Business School
**2020 - 2024** Senior Lecturer in Finance, Technology and Data Science Queen's Management School
**2010 - 2020** Lecturer Department of Finance, Queen's Management School
**2009 - 2009** Teaching Fellow Business School, Ulster University
**2005 - 2005** Teaching Fellow and Quantitative Researcher Department of Finance, RMIT University Melbourne
**1998 - 2004** Currency Trader and Liquidity Manager Janus Henderson Investors, London
**1995 - 1998** Financial Adviser City Financial Partners, London

Skills and Expertise