Joey O'Brien

Principal Consultant

LSEG

I am a Principal Consultant in the Quant Services division of LSEG, where I partner with tier-one investment banks, hedge funds, and risk technology teams to design, validate, and implement quantitative models for counterparty credit risk and derivative pricing. My work spans CVA, DVA, FVA, and PFE model validation, regulatory compliance with frameworks such as SS1/23 and FRTB, and the deployment of open-source risk infrastructure using the Open Source Risk Engine (ORE).

I hold a PhD in Applied Mathematics from the University of Limerick, where my research focused on describing the dynamics of complex systems (such as online social networks and popularity dynamics) using mathematical modelling and large-scale data analysis. This background in applied statistics and network science now informs my approach to building robust, mathematically rigorous financial risk analytics.

My technical toolkit includes Python (NumPy, SciPy, pandas, QuantLib Python), C++ for performance-critical pricing components, and R for statistical analysis and diagnostics. I also regularly contribute to LSEG’s Ahead of the Curve podcast series, discussing ORE developments, model risk regulation, and the future of quantitative risk management.

Quantitative Expertise Media & Podcasts Research & Papers Get in Touch

Interests

Counterparty Credit Risk (CCR)
XVA (CVA / DVA / FVA)
Derivative Pricing & Valuation
Model Risk Management
Quantitative Finance

Education

PhD in Applied Mathematics, 2017-2021
University of Limerick
BSc. in Financial Mathematics, 2013-2017
University of Limerick

News & Updates

July 2026 — Podcast: Featured on LSEG’s Ahead of the Curve podcast discussing the real-world impact and future of Agentic AI in quantitative risk management. Listen & Watch →
November 2025 — Conference & Lab: Attended and supported our APAC team’s ORE & Risk Analytics Lab in Tokyo, presenting to risk professionals from leading financial institutions on CVA frameworks, custom risk models, and capital efficiency.
March 2021 — New Scientist & PLOS ONE: Our mathematical research on Fantasy Premier League published in PLOS ONE and featured in New Scientist: Maths reveals the top strategies to win at fantasy football. Read Paper (PLOS ONE) | arXiv

View All News & Updates

Expertise

Quantitative Risk & Model Validation

I specialise in the validation and implementation of quantitative models across the trade lifecycle, with particular depth in:

XVA Modelling: CVA, DVA, FVA, MVA, and KVA frameworks; sensitivities and Greeks; regulatory capital
Counterparty Credit Risk: PFE simulation, ISDA SIMM, netting and collateral agreements
Derivative Pricing: Interest rate products (swaps, caps, floors, swaptions), credit derivatives, FX derivatives
Model Validation: Independent model review, backtesting, stress testing, regulatory documentation
Regulatory Compliance: SS1/23 (PRA Model Risk Management), FRTB, Basel IV
Open Source Risk Engine (ORE): Configuration, customisation, and validation against bespoke systems

Publications

Academic & Applied Mathematical Research

LSEG

2024

Backtesting Future Risk Factors Case Study

Joseph D O’Brien

This case study focuses on backtesting methodologies for Future Risk Factors within derivative exposure models, validating Simulated Exposure profiles against …

Source Document

Eur. Phys. J. B

2024

Persistence of chimera states and the challenge for synchronization in real-world networks

Riccardo Muolo, Joseph D O’Brien, Timoteo Carletti, Malbor Asllani

The emergence of order in nature manifests in different phenomena, with synchronization being one of the most representative examples. Understanding the role …

PDF Source Document

Phil. Trans. R. Soc. A

2021

Calibrating COVID-19 susceptible-exposed-infected-removed models with time-varying effective contact rates

James P Gleeson, Thomas Brendan Murphy, Joseph D O’Brien, Nial Friel, Norma Bargary, David JP O’Sullivan

We describe the population-based SEIR (susceptible, exposed, infected, removed) model developed by the Irish Epidemiological Modelling Advisory Group (IEMAG), …

Preprint PDF Code

Phys. Rev. Research

2021

Memory-cognizant generalization to Simon's random-copying neutral model

Joseph D O’Brien, James P Gleeson

Simon’s classical random-copying model, introduced in 1955, has garnered much attention for its ability, in spite of an apparent simplicity, to produce …

Preprint PDF

Phy. Rev. Research

2021

Hierarchical route to the emergence of leader nodes in real-world networks

Joseph D O’Brien, Kleber A Oliveira, James P Gleeson, Malbor Asllani

A large number of complex systems, naturally emerging in various domains, are well described by directed networks, resulting in numerous interesting features …

Preprint PDF Source Document

J. Complex Netw

2021

A complex networks approach to ranking professional Snooker players

Joseph D O’Brien, James P Gleeson

A detailed analysis of matches played in the sport of Snooker during the period 1968-2020 is used to calculate a directed and weighted dominance network based …

Preprint PDF Code Dataset

PLOS ONE

2021

Identification of skill in an online game: The case of Fantasy Premier League

Joseph D O’Brien, James P Gleeson, David JP O’Sullivan

In all competitions where results are based upon an individual’s performance the question of whether the outcome is a consequence of skill or luck arises. …

Preprint PDF

IEEE Transactions on Automatic Control

2020

A Generalized Framework for Simultaneous Long-Short Feedback Trading

Joseph D O’Brien, Mark E Burke, Kevin Burke

We present a generalization of the Simultaneous Long-Short (SLS) trading strategy described in recent control literature wherein we allow for different …

Preprint PDF Source Document

IEEE Control Systems Letters

2020

A generalization of the classical Kelly betting formula to the case of temporal correlation

Joseph D O’Brien, Kevin Burke, Mark E Burke, B. Ross Barmish

For sequential betting games, Kelly’s theory, aimed at maximization of the logarithmic growth of one’s account value, involves optimization of the …

Preprint PDF DOI

Physical Review E

2020

Quantifying uncertainty in a predictive model for popularity dynamics

Joseph D O’Brien, Alberto Aleta, Yamir Moreno, James P Gleeson

The Hawkes process has garnered attention in recent years for its suitability to describe the behavior of online information cascades. Here, we present a fully …

Preprint PDF DOI

New Journal of Physics

2019

Spreading of Memes on Multiplex Networks

Joseph D O’Brien, Ioannis K Dassios, James P Gleeson

A model for the spreading of online information or ‘memes’ on multiplex networks is introduced and analyzed using branching-process methods. The model …

Preprint PDF DOI

Media & Speaking

Podcasts, Keynotes, Industry Labs & Academic Seminars

FEATURED PODCAST LSEG Ahead of the Curve

Agentic AI in Quantitative Risk Management

Discussing the real-world operational transformation and governance challenges of deploying autonomous AI agents and Open Source Risk Engine (ORE) architectures on institutional trading and risk desks.

Key Discussion Topics: