Prof. Barry Quinn

Professor of Finance and Financial Technology

Prof. Barry Quinn

Contact Information

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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 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

  • 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 — 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. MiniMBA in FinTech and Responsible Data Science (Ulster University, Magee Campus, 2026–): A DfE-sponsored, credit-bearing four-day intensive (one day delivered online) at UUBS/Magee, structured around three pillars that mirror the Centre for Finance and Responsible Technology’s mission: the economics of FinTech (cost puzzle, platforms, prediction economics); responsible data science (validation discipline, overfitting, walk-forward testing, evidence standards); and AI in finance with a regulatory compliance focus, drawing directly on CFRT/UKFin+ research into governance and graduated automation. Course materials are published at quinfer.github.io/minimba with interactive Google Colab labs. The inaugural 2026 cohort produced a Compare NI FinTech Scholarship winner. Next delivery: Spring 2027.

  5. Trading Principles (Queen’s University Belfast): A postgraduate learning-by-doing course in market microstructure, built around approximately 18 live in-class trading simulations. 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. The simulation platform has since been extended as TickLab, an open web-based teaching environment for market microstructure.

This commitment to experiential learning extends beyond the classroom. At Queen’s I co-founded the Queen’s Student Managed Fund (2012–2024), giving students stewardship of a real investment portfolio. At Ulster I am co-founder and incoming Chair (from September 2026) of a Trading and Investment Group with Veronica Zhang and Edwin Koenck, funded by a £100K alumni philanthropic donation in partnership with Innovation Ulster Ltd. The Chair role is governance and oversight, including engagement with Innovation Ulster Ltd, bringing the same learning-by-doing philosophy to a new institutional context.

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 (2026). TickLab: Web-based trading simulation for market microstructure and trading dynamics. Open teaching software for classroom use, with interactive tutorials, an online simulation engine, and academic foundations. www.ticklab.co.uk

  • 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 seventeen peer-reviewed academic papers (1 ABS4, 10 ABS3s, and 5 ABS2s in ranked journals, plus one additional journal article), 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

My research develops across three methodological strands.

The first is trustworthy machine learning for market integrity and risk. This includes representation-learning approaches to market-manipulation detection, including work published in Information Processing & Management, and related projects on anomaly detection, signal amplification, and sentiment-conditioned crash-risk modelling. The methodological commitment throughout is that model performance and model trustworthiness are separable properties, both of which must be evidenced before deployment in operational or regulatory settings.

The second is computer vision for socio-economic measurement. This work uses real-world imagery to develop auditable indicators of social, economic, and regulatory phenomena, including projects on environmental correlates of vehicle crime and the measurement of cultural-symbol displays in Northern Ireland. The aim is to treat vision pipelines as measurement instruments rather than accuracy-maximising systems alone.

The third is causal and statistical evidence for governance and regulation. This includes work on innovation signals and strategic exits in RegTech, Basel III’s cross-border transmission through foreign bank subsidiaries, credit-union risk and resilience, and collaborative doctoral partnerships with industry partners including Pytilia, Napier AI, and Funds Axis. Across all three strands, the 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

Software Publications

Working Papers

  • Birem, AbderRaouf, Abidi Perier, Zineb, Quinn, Barry, Kearney, Fearghal. Transformer-Based Sentiment Analysis for Stock Market Crash Risk. Under revision.

  • Dai, Yongsheng, Quinn, Barry, Kearney, Fearghal, Wang, Hui. Signal Amplification and Strategic Deterrence in Market Surveillance. Working paper.

  • Dai, Yongsheng, Huang, Ji, Ren, Spence, Ivor, Rafferty, Karen, Quinn, Barry, Wang, Hui. FMISD: Fine-grained Multi-Scale Modeling for Inexact Supervised Anomaly Detection of Time Series. Under revision at IEEE Transactions on Cybernetics (ABS3).

  • Quinn, Barry, Sheenan, Lisa, Zhang, Ying (Veronica). Regulatory Reach or Regulatory Arbitrage? Basel III’s Cross-Border Transmission Through Foreign Bank Subsidiaries. Centre for Responsible Banking & Finance Working Paper 25-017.

  • Kearney, Fearghal, Quinn, Barry, Pramanick, Abhishek. Innovation Signals and Strategic Exits: How Technological Readiness Shapes Outcomes in Computational Approaches to Financial Regulation. Working paper.

  • Hannon, James (Corresponding Author), French, Declan, Quinn, Barry, O’Hagan, Adrian. Geospatial modeling of vehicle crime in Northern Ireland using computer vision to identify environmental factors. Under revision.

  • Cochrane, Brandon, Bryan, Dominic, Quinn, Barry, Graham, Bryon, French, Declan (Corresponding Author) (2026). Flying the Flag: Cultural Expression as Territorial Demarcation. Institute for Global Peace, Security and Justice Working Paper WP 02/26, Queen’s University Belfast. https://www.qub.ac.uk/sites/institute-for-global-peace-security-justice/FileStore/WP-02-26.pdf

  • Campbell, Gareth, Kelly, Colm, Quinn, Barry. When Simplicity Beats Sophistication: Market Size and the Limits of Optimal Factor Construction. Working paper.

  • Quinn, Barry. Sensitivity Analysis and Partial Identification for Covariate Effects in Structural Topic Models. Working paper.

  • Quinn, Barry, Gallagher, Ronan. Great Expectations: Relative Performance and Managerial Turnover in Professional Football. Working paper.

  • Quinn, Barry. Hierarchical Flag Classification through Economic Domain Knowledge: A Vision Transformer Approach for Cultural Symbol Recognition. Working paper.

  • Quinn, Barry, Wang, Ying (Veronica). The Efficiency Returns to Cloud Computing: Evidence from Staggered Data Protection Laws. Working paper.

  • Quinn, Barry, Gallagher, Ronan, Birem, AbderRaouf. Board Composition and M&A Announcement Returns. Working paper.

  • Quinn, Barry, Peng, Qiao (Olivia), Liu, Weilong. Climate Risk and Credit Union Lending: Channel-Specific State Heterogeneity. Working paper.

  • Walker, Clive, Quinn, Barry. Do Exogenous Shocks Reshape Financial Narratives?. Working paper.

  • Quinn, Barry. Adaptive Capital and Patent Boundary Indeterminacy. Working paper.

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: Pytilia 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 Northern Ireland street-scene dataset and hierarchy-aware taxonomy for measuring cultural-symbol displays from street-level imagery.
  10. AI Adoption, Opportunities & Impact for SMEs (Intertrade Ireland Tender Scheme; Academic Co-Lead Barry Quinn, with Sans Souci and Charles Vincent (QUB) as co-leads): funded research on all-island SME AI adoption, opportunities and impact; InterTradeIreland research report in preparation; academic publication under consideration.
  11. Trading and Investment Group, Ulster University Business School (co-founded with Veronica Zhang and Edwin Koenck; incoming Chair from September 2026; £100K alumni philanthropic donation, 2026; in partnership with Innovation Ulster Ltd): governance and oversight of a student-run trading and investment group at Ulster University Business School, including engagement with Innovation Ulster Ltd; launching September 2026.
  12. MiniMBA in FinTech and Responsible Data Science (DfE-sponsored, Magee Campus, Ulster University Business School, 2026): inaugural cohort of a credit-bearing four-day intensive (one day online) executive education programme covering the economics of FinTech, responsible data science and validation discipline, and AI in finance/regulation — with Day 3 drawing directly on CFRT/UKFin+ research. Course materials are published at quinfer.github.io/minimba. A student from the cohort was awarded the Compare NI FinTech Scholarship. Programme will run again Spring 2027.

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).

Doctoral Supervision in Completion (Queen’s University Belfast)

Ongoing formal supervision of doctoral researchers registered at Queen’s University Belfast.

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

  • DfE NI (PI, 2025) — Three PhD scholarships to support the Centre for Finance and Responsible Technology (including two collaborative doctoral partnerships) — £360,000 (Research)
  • UKFin+ (PI, 2024–2025) — Leveraging AI to understand and improve regulatory compliance in the Investment Management Industry — £100,000 (Research)
  • DofE CAST Award NI (Co-I, 2023) — Exploring the Welfare Cost of Cultural Displays in Northern Ireland using multimodal Generative AI — £70,000 (Research)
  • Innovate UK (PI, 2022–2023) — 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 — £173,000 (Research)
  • DofE CAST Award NI (Co-I, 2021) — PhD investigation into how AI innovation affect a highly valued financial service provision experience — £70,000 (Research)
  • InvestNI (Co-I, 2021–2021) — Review of Value at Risk analytics at the intersection of econometrics and machine learning — £5,000 (Consulting)
  • Innovate UK (PI, 2021–2023) — Regulatory technology and portfolio analytics using state-of-the-art econometrics and financial machine learning — £173,000 (Research)
  • InvestNI (Co-I, 2019–2019) — Review of AI and web analytics for price comparison — £5,000 (Consulting)
  • InvestNI (Co-I, 2018) — Review of state-of-the-art machine learning in the context of retail analytics and monitoring — £5,000 (Consulting)
  • Innovate UK (PI, 2018–2021) — Designing and deploying a retail analytics platform using advanced analytics and machine learning — £165,000 (Research)
  • DofE (Co-I, 2016–2018) — Landscape review of Northern Ireland Credit Unions — £32,000 (Consulting)
  • QBS CEBR (PI, 2016–2019) — Estimating the costs and benefits of corporation tax policy change in Northern Ireland — £3,500 (Research)
  • Phoenix Natural Gas Ltd (PI, 2014–2015) — Forecasting daily demand for natural gas in Northern Ireland — £15,000 (Consulting)

Total Research Income: approximately £1,176,500 in direct awards as PI or Co-I across 13 projects.

Citizenship

Academic Service

  • Director, Centre for Finance and Responsible Technology, Ulster University Business School, September 2025–.
  • Co-founder and incoming Chair (from September 2026; with Veronica Zhang and Edwin Koenck), Trading and Investment Group, Ulster University Business School, 2026– (£100K alumni philanthropic fund; in partnership with Innovation Ulster Ltd; governance and oversight, including engagement with Innovation Ulster Ltd).
  • Programme Lead, MiniMBA in FinTech and Responsible Data Science, Magee Campus, Ulster University Business School, 2026– (DfE-sponsored; credit-bearing four-day intensive (one day online); inaugural cohort 2026; Compare NI FinTech Scholarship winner from cohort; open materials at quinfer.github.io/minimba; next delivery Spring 2027).
  • 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 (£100K) 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

Skills and Expertise