Main Conference Day 1: Thursday 25th September
08.00 – 09.00: Registration and Morning Welcome Coffee
Morning Stream Chair:
Christopher Kantos:
Managing Director and Head of Quantitative Research, Alexandria Technology
Christopher Kantos:
Christopher Kantos: Managing Director and Head of Quantitative Research, Alexandria Technology
Mr. Christopher Kantos is a Managing Director and Head of Quantitative Research at Alexandria Technology. In this role, he focuses on maintaining and growing new business in EMEA, and exploring ways in which natural language processing and machine learning can be applied in the financial domain. Prior, he spent 15 years working in financial risk at Northfield Information Services as a Director and Senior Equity Risk Analyst. Mr. Kantos earned a BS in computer engineering from Tufts University.
09.00 – 09.45: “LLMs for Time Series: an Application for Single Stocks and Statistical Arbitrage”
Recently, LLMs (Large Language Models) have been adapted for time series prediction with significant success in pattern recognition. However, the common belief is that these models are not suitable for predicting financial market returns, which are known to be almost random. We aim to challenge this misconception through a counterexample. Specifically, we utilized the Chronos model from Ansari et al. (2024) and tested both pretrained configurations and fine-tuned supervised forecasts on the largest American single stocks using data from Guijarro-Ordonnez et al. (2022). We constructed a long/short portfolio, and the performance simulation indicates that LLMs can in reality handle time series that are nearly indistinguishable from noise, demonstrating an ability to identify inefficiencies amidst randomness and generate alpha. Finally, we compared these results with those of specialized models and smaller deep learning models, highlighting significant room for improvement in LLM performance to further enhance their predictive capabilities.
Sébastien Valeyre:
Portfolio Manager, Machina Capital
Sébastien Valeyre:
Sébastien Valeyre: Portfolio Manager, Machina Capital
Sébastien Valeyre is the portfolio manager of Machina Capital’s systematic futures strategy, Machina Electron. Machina Capital is a Paris-based investment firm, founded by seasoned equity derivatives traders and quantitative researchers. The firm specializes in mid-frequency systematic strategies for equities and futures, aiming to generate absolute and uncorrelated returns.
Prior to joining Machina Capital, Sébastien was a partner at John Locke Investments, where he launched a statistical arbitrage fund, the John Locke Equity Market Neutral Fund. Sébastien successfully managed this equity strategy while also contributing research to the firm’s systematic CTA strategy. Before that, Sébastien was head of research at BPHI Capital, which employed a blended fundamental and quantitative approach. Sébastien began his career at France’s Authority of Nuclear Safety and Atomic Energy Commission.
Sébastien holds a PhD in Economics from Sorbonne Paris Cité University, a Master of Science from Imperial College, a Master of Science in Finance from Dauphine University, and a Master of Science in Physics from École Supérieure de Physique et Chimie Industrielles de Paris (ESPCI).
09.45 – 10.30: Financial Reasoning Agents: In-Context Reinforcement Learning and Test-Time Compute
Large Language Models (LLMs) are increasingly being integrated with reinforcement learning (RL) to push the boundaries of generalist AI agents. In finance, where real-time decision-making is critical, test-time compute efficiency plays a pivotal role in ensuring models can adapt dynamically to evolving market conditions. In-context reinforcement learning (ICRL) is emerging as a transformative approach, enabling LLMs to learn and refine on the fly without explicit fine-tuning. ICRL enhances adaptability in trading, risk assessment, and portfolio optimization. This paradigm shift moves us closer to AI agents capable of robust decision-making, paving the way for more autonomous and generalizable systems in high-stakes applications.
Nicole Königstein:
Chief Data Scientist, Head of AI & Quant Research, Wyden Capital AG
Nicole Königstein:
Nicole Königstein: Chief Data Scientist, Head of AI & Quant Research, Wyden Capital AG
Nicole Königstein is a distinguished Data Scientist and Quantitative Researcher, currently working as Data Science and Technology Lead at impactvise, an ESG analytics company, and as Head of AI and Quantitative Research at Quantmate, an innovative FinTech startup focused on alternative data in predictive modeling. Alongside her roles in these organizations, she serves as an AI consultant across diverse industries, leading workshops and guiding companies from the conceptual stages of AI implementation through to final deployment.
As a guest lecturer, Nicole shares her expertise in Python, machine learning, and deep learning at various universities. She is a regular speaker at renowned AI and Data Science conferences, where she conducts workshops and educational sessions. In addition, she is an influential voice in the data science community, regularly reviewing books in her field and offering her insights and critiques. Nicole is also the author of the well-received online course, “Math for Machine Learning.
10.30 – 11.00: Morning Break and Networking Opportunities
11.00 – 11.45: Pricing Derivatives with a Generative Adversarial Network Approach.
- Motivation: Deep Learning Approximations with Generative ML
- Taxonomy of Generative Methods
- An Introduction to GANs, Conditional GANs and Regression GANs
- Theoretical Principles for Training GANs
- Wasserstein GANs and the Earth-Mover Distance
- Applications
Youssef Elouerkhaoui:
Managing Director, Global Head of Markets Quantitative Analysis, Citi
Youssef Elouerkhaoui:
Youssef Elouerkhaoui: Managing Director, Global Head of Markets Quantitative Analysis, Citi
Youssed Elouerkhaoui is the global Head of Credit Quantitive Analysis at Citi. His group supports all aspects of modelling and product development across desks, thais includes: Flow Credit Trading, Correlation Trading, CDOs, Exotics and Emering Markets.
He also supports CVA, Funding and Regulatory Capital for Credit Markets. Prior to this, he was a Director in the Fixed Income Derivatives Quantitative Research Group at UBS, where he was in charge of developing and implementing models for the Structured Credit Desk. Before joining UBS, Youssef was a Quantitative Research Analyst at Credit Lyonnais supporting the Interest Rates Exotics business. He has also worked as a Senior Consultant in the Risk Analytics and Research Group at Ernst & Young. He is a graduate of Ecole Centrale Paris and he holds a PhD in Mathematics from Paris-Dauphine University.
11.45 – 12.30: Morphing Distributions using Gaussian Mixtures and Optimal Transport
Jörg Kienitz:
Independent Consultant, Adjunct Prof (UCT), Assistant Prof (BUW)
Jörg Kienitz:
Jörg Kienitz: Independent Consultant, Adjunct Prof (UCT), Assistant Prof (BUW)
Jörg Kienitz is a partner at Quaternion, Acadia’s Quant Services division. He owns the finciraptor.de website – an educational platform for Quantitative Finance and Machine Learning. Jörg consults on the development, implementation, and validation of quantitative models. He is an Assistant Professor at the University of Wuppertal and an Adjunct Associate Professor in AIFMRM at the University of Cape Town. He regularly addresses major conferences, including Quant Minds, RISK or the WBS Quant Conference. Jörg has authored four books, Monte Carlo Frameworks (with Daniel J. Duffy), Financial Modelling (with Daniel Wetterau), and Interest Rate Derivatives Explained I and II (with Peter Caspers). He also co-authored research articles that appeared in leading journals like Quantitative Finance, RISK or Mathematics in Industry.
12.30 – 13.45: Lunch
Afternoon Stream Chair: TBC
13.45 – 14.30: Filtered not Mixed: Stochastic Filtering-Based Online Gating for Mixture of Large Language Models
We propose MoE-F – a formalized mechanism for combining N pre-trained Large Language Models (LLMs) for online time-series prediction by adaptively forecasting the best weighting of LLM predictions at every time step. Our mechanism leverages the conditional information in each expert’s running performance to forecast the best combination of LLMs for predicting the time series in its next step. Diverging from static (learned) Mixture of Experts (MoE) methods, our approach employs time-adaptive stochastic filtering techniques to combine experts. By framing the expert selection problem as a finite state-space, continuous-time Hidden Markov model (HMM), we can leverage the Wohman-Shiryaev filter. Our approach first constructs N parallel filters corresponding to each of the N individual LLMs. Each filter proposes its best combination of LLMs, given the information that they have access to. Subsequently, the N filter outputs are optimally aggregated to maximize their robust predictive power, and this update is computed efficiently via a closed-form expression, generating our ensemble predictor.
Blanka Horvath:
Associate Professor in Mathematical and Computational Finance, University of Oxford
Blanka Horvath:
Blanka Horvath: Associate Professor in Mathematical and Computational Finance, University of Oxford and Researcher, The Alan Turing Institute
Blanka research interests are in the area of Stochastic Analysis and Mathematical Finance.
Including asymptotic and numerical methods for option pricing, smile asymptotics for local- and stochastic volatility models (the SABR model and fractional volatility models in particular), Laplace methods on Wiener space and heat kernel expansions.
Blanka completed her PhD in Financial Mathematics at ETHZürich with Josef Teichmann and Johannes Muhle-Karbe. She holds a Diploma in Mathematics from the University of Bonn and an MSc in Economics from the University of Hong Kong.
14.30 – 15.15: Large Language Models in Financial Services: FAIR -A Framework for Implementation, Risk Mitigation, and Remediation
Miquel Noguer Alonso:
Co – Founder and Chief Science Officer, Artificial Intelligence Finance Institute – AIFI
Miquel Noguer Alonso:
Miquel Noguer Alonso: Co – Founder and Chief Science Officer, Artificial Intelligence Finance Institute – AIFI
Miquel Noguer is a financial markets practitioner with more than 20 years of experience in asset management, he is currently Head of Development at Global AI ( Big Data Artificial Intelligence in Finance company ) and Head on Innovation and Technology at IEF.
He worked for UBS AG (Switzerland) as Executive Director.for the last 10 years. He worked as a Chief Investment Office and CIO for Andbank from 2000 to 2006.
He is professor of Big Data in Finace at ESADE and Adjunct Professor at Columbia University teaching Asset Allocation, Big Data in Finance and Fintech. He received an MBA and a Degree in business administration and economics in ESADE in 1993. In 2010 he earned a PhD in quantitative finance with a Summa Cum Laude distinction (UNED – Madrid Spain).
15.15 – 15.45: Afternoon Break and Networking Opportunities
15.45 – 16.30: Machine Learning with Smart Sampling
- The strengths (and weaknesses) of traditional Machine Learning
- Smart Sampling Machine Learning:
- How to do it
- benefits (and pitfalls)
- Numerical results & applications.
Ignacio Ruiz:
Ignacio Ruiz:
Ignacio Ruiz: Founder, MoCaX Intelligence
Ignacio Ruiz has been the Head of Counterparty Credit Risk Measurement and Analytics, Scotiabank, the head strategist for Counterparty Credit Risk, exposure measurement, for Credit Suisse, as well as the Head of Risk Methodology, equities, for BNP Paribas. In 2010, Ignacio set up iRuiz Consulting as an independent advisory business in this field. In 2014, Ignacio founded iRuiz Technologies to develop and commercialise MoCaX Intelligence.
Ignacio has several publications in the space of quantitative risk management and pricing. He has also published a comprehensive guide to the subject of XVA Desks and Risk Management.
He holds a PhD in nano-physics from Cambridge University.
16.30 – 17.15: The Psychology of LLMs
- AI and humans perform surprisingly alike in classic behavioral psychology experiments
- These experiments show that AI shares many cognitive biases of humans and is prone to human-like errors of logical reasoning and recall
- We will examine the reasons for this surprising and perhaps even shocking finding, some superficial and some profound
- Our analysis will lead to concrete, practical techniques for avoiding these biases and increasing the reliability of AI in business settings
Alexander Sokol:
Executive Chairman and Head of Quant Research, CompatibL
Alexander Sokol:
Alexander Sokol: Executive Chairman and Head of Quant Research, CompatibL
Alexander Sokol is the founder, Executive Chairman, and Head of Quant Research at CompatibL, a trading and risk technology company. He is also the co-founder of Numerix, where he served as CTO from 1996 to 2003, and the co-founder of Duality Group, where he served as CTO from 2017 to 2020.
Alexander won the Quant of the Year Award in 2018 together with Leif Andersen and Michael Pykhtin, for their joint work revealing the true scale of the settlement gap risk that remains even in the presence of initial margin. Alexander’s other notable research contributions include systemic wrong-way risk (with Michael Pykhtin, Risk Magazine), joint measure models, and the local price of risk (with John Hull and Alan White, Risk Magazine), and mean reversion skew (Risk Books, 2014).
Alexander earned his BA from the Moscow Institute of Physics and Technology at the age of 18, and a PhD from the L. D. Landau Institute for Theoretical Physics at the age of 22. He was the winner of the USSR Academy of Sciences Medal for Best Student Research of the Year in 1988.
17.15 – 18.00: QFC AI Panel
- In capital markets, can AI be trusted for:
- Knowledgebase and document repository search and ranking of results
- Internal or regulatory document generation with human review and approval
- Fully automated or human-supervised data extraction from unstructured text
- AI is not to be trusted for anything
- Which AI model family you found to be most effective in your AI applications – GPT, LLAMA, Mistral, Gemini, Anthropic?
- Why many banks are not yet comfortable with cloud-based AI even as they widely use the cloud for their most sensitive data?
- When can we expect to see tangible benefits from using AI – now, next year, in five years, or never?
Moderator:
Alexander Sokol:
Executive Chairman and Head of Quant Research, CompatibL
Alexander Sokol:
Alexander Sokol: Executive Chairman and Head of Quant Research, CompatibL
Alexander Sokol is the founder, Executive Chairman, and Head of Quant Research at CompatibL, a trading and risk technology company. He is also the co-founder of Numerix, where he served as CTO from 1996 to 2003, and the co-founder of Duality Group, where he served as CTO from 2017 to 2020.
Alexander won the Quant of the Year Award in 2018 together with Leif Andersen and Michael Pykhtin, for their joint work revealing the true scale of the settlement gap risk that remains even in the presence of initial margin. Alexander’s other notable research contributions include systemic wrong-way risk (with Michael Pykhtin, Risk Magazine), joint measure models, and the local price of risk (with John Hull and Alan White, Risk Magazine), and mean reversion skew (Risk Books, 2014).
Alexander earned his BA from the Moscow Institute of Physics and Technology at the age of 18, and a PhD from the L. D. Landau Institute for Theoretical Physics at the age of 22. He was the winner of the USSR Academy of Sciences Medal for Best Student Research of the Year in 1988.
Nicole Königstein:
Chief Data Scientist, Head of AI & Quant Research, Wyden Capital AG
Nicole Königstein:
Nicole Königstein: Chief Data Scientist, Head of AI & Quant Research, Wyden Capital AG
Nicole Königstein is a distinguished Data Scientist and Quantitative Researcher, currently working as Data Science and Technology Lead at impactvise, an ESG analytics company, and as Head of AI and Quantitative Research at Quantmate, an innovative FinTech startup focused on alternative data in predictive modeling. Alongside her roles in these organizations, she serves as an AI consultant across diverse industries, leading workshops and guiding companies from the conceptual stages of AI implementation through to final deployment.
As a guest lecturer, Nicole shares her expertise in Python, machine learning, and deep learning at various universities. She is a regular speaker at renowned AI and Data Science conferences, where she conducts workshops and educational sessions. In addition, she is an influential voice in the data science community, regularly reviewing books in her field and offering her insights and critiques. Nicole is also the author of the well-received online course, “Math for Machine Learning.
Ignacio Ruiz:
Ignacio Ruiz:
Ignacio Ruiz: Founder, MoCaX Intelligence
Ignacio Ruiz has been the Head of Counterparty Credit Risk Measurement and Analytics, Scotiabank, the head strategist for Counterparty Credit Risk, exposure measurement, for Credit Suisse, as well as the Head of Risk Methodology, equities, for BNP Paribas. In 2010, Ignacio set up iRuiz Consulting as an independent advisory business in this field. In 2014, Ignacio founded iRuiz Technologies to develop and commercialise MoCaX Intelligence.
Ignacio has several publications in the space of quantitative risk management and pricing. He has also published a comprehensive guide to the subject of XVA Desks and Risk Management.
He holds a PhD in nano-physics from Cambridge University.
Gala Dinner: Thursday 25th September, 20.00 til late.
Lo Stand Florio Restaurant – The Gala Dinner is complimentary for all conference delegates.
The Florio Stand, commissioned by Vincenzo Florio Jr. to Ernesto Basile in the early 1900s, was built during the Belle Epoque, a fine example of Art Nouveau architecture with incursions into Moorish art. The original idea was to create a large space for sports, entertainment, entertainment and socializing.
The Gala Dinner is complimentary for all conference delegates.
Menu:
Primo Piatto – First Course
Busiate alla Norma con melanzane fritte, salsa di pomodoro, ricotta salata e basilico
Busiate alla Norma with fried aubergines, tomato sauce, salted ricotta cheese and basil
Secondo Piatto – Second Course
Filetto di spigola al pan di agrumi siciliani, patate mascotte al rosmarino e pomodoro gratinato
Seabass fillet with Sicilian citrus breading, rosemary-scented mascotte potatoes and gratinated tomato
Dessert
Cannolo con ricotta home made
Cannolo with ricotta cheese home made
Bevande – Beverage
Mineral and sparkling water
Vino Tasca D’Almerita, Sallier de la Tour, Grillo
Amaro Florio
Contact Information:
- via Messina Marine, 40 – 90123 Palermo
- +39 091 730 8360
- info@standflorio.it
- Location Map
08.00 – 09.00: Registration and Morning Welcome Coffee
Morning Stream Chair:
Peter Jaeckel:
Independent financial mathematics and analytics consultant. OTC Analytics
Peter Jaeckel:
Peter Jaeckel: Independent financial mathematics and analytics consultant. OTC Analytics
Peter Jäckel received his DPhil from Oxford University in 1995. In 1997, he moved into quantitative analysis and financial modelling when he joined Nikko Securities. Following that he worked as a quantitative analyst at NatWest, Commerzbank Securities, ABN AMRO, and now VTB Capital where he is the Deputy Head of Quantitative Research. Peter is the author of “Monte Carlo Methods in Finance” published by John Wiley & Sons. Some of his publications can be found at WWW.JAECKEL.ORG.
09.00 – 09.45: ‘A New Class of Tractable Local Vol Models’
Dominique Bang:
Managing Director, FICC Quantitative Modelling Lead, Bank Of America
Dominique Bang:
Dominique Bang: Managing Director, FICC Quantitative Modelling Lead, Bank Of America Paris
Dominique Bang received his PhD from Observatory of Paris (2002) in the field of ‘Mathematical Methods applied to Celestial Mechanics’. He moved into quantitative finance in 2006. Dominique has since been working in Bank Of America in the interest rates and hybrid quantitative team where he is covering every aspect ranging from plain vanilla to exotic structured products.
09.45 – 10.30: Next Gen Finite Difference Grids
Stability and accuracy of fd solution: myths, facts and orthodoxy
Discrete consistency: backwards, forwards, Dupire fd solution, monte carlo.
- local volatility and absence of arbitrage
Dividends.
- stochastic volatility
- jumps
- american options
- bids and offers of listed options
- monte-carlo simulation, likelihood ratio tricks and adjoint differentiation
Jesper Andreasen:
Head of Quantitative Analytics, Verition Fund Management LLC
Jesper Andreasen:
Jesper Andreasen: Head of Quantitative Analytics, Verition Fund Management LLC
Jesper Andreasen is head of Quantitative Analytics at Verition Fund Management LLC. Jesper has previously held senior positions in the quantitative research departments of Saxo Bank, Danske Bank, Bank of America, Nordea, and General Re Financial Products. Jesper’s recent research focusses on efficient and accurate methods for computing credit and market risk. Jesper holds a PhD in mathematical finance from Aarhus University, Denmark. He received Risk Magazine’s Quant of the Year awards in 2001 and 2012, joint with Leif Andersen and Brian Huge respectively, and is an honorary professor of mathematical finance at Copenhagen University.
10.30 – 11.00: Morning Break and Networking Opportunities
11.00 – 11.45: The Arbitrage Free Autoencoder
Brian Norsk Huge:
Head of Financial Modeling, Trafigura
Brian Norsk Huge:
Brian Norsk Huge: Head of Financial Modeling, Trafigura
Brian Huge is working as the head of financial modeling at Trafigura. Before joining Trafigura, Brian was head of quants at Saxo Bank and previously as a quant for 20 years at Danske Bank. Brian has a Ph.D. in Mathematical Finance from University of Copenhagen. In 2012 he was awarded Quant of the Year for his work on Volatility Interpolation and Random Grids.
11.45 – 12.30: “A General Approach to Statistical Arbitrage”
Bruno Dupire:
Head of Quantitative Research, Bloomberg
Bruno Dupire:
Bruno Dupire: Head of Quantitative Research, Bloomberg
Bruno Dupire is the Global Head of Quantitative Research, CTO Office at Bloomberg, which he joined in 2004. Prior to this assignment in New York, he has headed the Derivatives Research teams at Société Générale, Paribas Capital Markets and Nikko Financial Products where he was a Managing Director. He is best known for having pioneered the widely used Local Volatility model (simplest extension of the Black-Scholes-Merton model to fit all option prices) in 1993 and the Functional Itô Calculus (framework for path dependency) in 2009. He is a Fellow and Adjunct Professor at NYU and he is in the Risk magazine “Hall of Fame”. He is the recipient of the 2006 “Cutting edge research” award of Wilmott Magazine and of the Risk Magazine “Lifetime Achievement” award for 2008. He runs and organizes the Bloomberg Quant (BBQ) seminar, the largest monthly event of this kind.
12.30 – 13.45: Lunch
Afternoon Stream Chair:
Nikolai Nowaczyk:
Quantitative Analytics, Director, NatWest Group
Nikolai Nowaczyk:
Nikolai Nowaczyk: Quantitative Analytics, Director, NatWest Group
13.45 – 14.30: Towards the lower bound for Bermudans
- An achievable lower bound for a Bermudan is not always the max European
- Finding a robust (model-free) lower bound for Bermudans is surprisingly difficult
- It is important for designing “Bermudan discount” adjustment models prevalent in the industry for the last 30+ years
- We make some progress towards this goal
Vladimir Piterbarg:
MD, Head of Quantitative Analytics and Quantitative Development, NatWest Markets
Vladimir Piterbarg:
Vladimir Piterbarg: MD, Head of Quantitative Analytics and Quantitative Development at NatWest Markets
14.30 – 15.15: Discovering fundamental financial laws: Universal regimes across full rates spectrum
- Universal regimes for nominal, real and inflation rates
- Universal regimes across economic periods and across markets
- Fundamentals behind the universal regimes. Critical role of Central Banks. Tenor dimension
- Universal regimes across P and Q universes
- Expanding Fisher equation from rate levels to its volatilities: is knowing two out of three enough?
Maria Makarova:
Assistant Vice President Quantitative Analyst, BNP Paribas
Maria Makarova:
Maria Makarova: Assistant Vice President Quantitative Analyst, BNP Paribas
Maria Makarova has been a Risk Methodology Quantitative Analyst at BNP Paribas since 2018. She splits her time between performing research of interest rate modelling, and delivering improvements to the Market and Counterparty Risk methodologies. Maria has previously worked for Barclays, developing Market Risk models and helping to adapt the bank’s framework to FRTB requirements. Before starting her career in Financial Markets, she has briefly worked as a managements consultant with McKinsey. Maria holds a Master degree in Applied Maths from Moscow Institute of Physics and Technology.
Vladimir Chorniy:
Managing Director, Head of Risk Model Fundamentals and Research Lab, Senior Technical Lead, BNP Paribas
Vladimir Chorniy:
15.15 – 15.45: Afternoon Break and Networking Opportunities
15.45 – 16.30: Approaches to Learning Basis Functions for Least-Squares Monte Carlo Methods
- LSMC for future values, sensis, conditional percentiles to support XVA, risk and capital projections Active research into moving from regression to neural networks, other modern specifications
- Solves the basis specification problem, particularly onerous in higher dimensions
- More expensive than simple regression as we’re learning the basis (extracting features) at calc time
- Stagger the problem by pre-learning the basis? Something between fully-online and fully-offline methods?
Andrew McClelland:
Director, Quantitative Research, Numerix
Andrew McClelland:
Andrew McClelland: Director, Quantitative Research, Numerix
Andrew McClelland’s work at Numerix focuses on counterparty credit risk issues including valuation adjustments and counterparty exposure production for structured products. He also works on numerical methods for efficient production of risk profiles under real-world measures.
Andrew received his Ph.D. in finance at the Queensland University of Technology in financial econometrics. His research involved markets exhibiting crash feedback, option pricing, and parameter estimation using particle filtering methods. His work has been published in the Journal of Banking and Finance, the Journal of Econometrics, and the Journal of Business and Economic Statistics.
16.30 – 17.15: A Hair for A Square
Subtitle: Standard Error and Goodness of Fit in American Monte Carlo
Authors: Andrew Greene, Nikolai Nowaczyk
– review statistical framework for model validation of regression pricing
– explore advanced metrics using hairy simulation
Nikolai Nowaczyk:
Quantitative Analytics, Director, NatWest Group
Nikolai Nowaczyk:
Nikolai Nowaczyk: Quantitative Analytics, Director, NatWest Group
Andrew Greene:
Andrew Greene:
Andrew Greene: Director, CVA Quantitative Analyst, NatWest Markets
Andrew gained a degree in Physics and Theoretical Physics at Cambridge University, followed by a PhD degree in experimental High Energy Physics at Imperial College London. This was followed by a transition from FORTRAN to C++ in the computer game industry, which set him up for a move into quantitative finance. After a stint at JPMorgan working for the commodity exotics desk, he moved to the then RBS, now NatWest Markets, and has been developing the xVA model and systems at NatWest Markets ever since.
17.15 – 18.00: QFC AI Panel
- In capital markets, can AI be trusted for:
- Knowledgebase and document repository search and ranking of results
- Internal or regulatory document generation with human review and approval
- Fully automated or human-supervised data extraction from unstructured text
- AI is not to be trusted for anything
- Which AI model family you found to be most effective in your AI applications – GPT, LLAMA, Mistral, Gemini, Anthropic?
- Why many banks are not yet comfortable with cloud-based AI even as they widely use the cloud for their most sensitive data?
- When can we expect to see tangible benefits from using AI – now, next year, in five years, or never?
Moderator:
Alexander Sokol:
Executive Chairman and Head of Quant Research, CompatibL
Alexander Sokol:
Alexander Sokol: Executive Chairman and Head of Quant Research, CompatibL
Alexander Sokol is the founder, Executive Chairman, and Head of Quant Research at CompatibL, a trading and risk technology company. He is also the co-founder of Numerix, where he served as CTO from 1996 to 2003, and the co-founder of Duality Group, where he served as CTO from 2017 to 2020.
Alexander won the Quant of the Year Award in 2018 together with Leif Andersen and Michael Pykhtin, for their joint work revealing the true scale of the settlement gap risk that remains even in the presence of initial margin. Alexander’s other notable research contributions include systemic wrong-way risk (with Michael Pykhtin, Risk Magazine), joint measure models, and the local price of risk (with John Hull and Alan White, Risk Magazine), and mean reversion skew (Risk Books, 2014).
Alexander earned his BA from the Moscow Institute of Physics and Technology at the age of 18, and a PhD from the L. D. Landau Institute for Theoretical Physics at the age of 22. He was the winner of the USSR Academy of Sciences Medal for Best Student Research of the Year in 1988.
Nicole Königstein:
Chief Data Scientist, Head of AI & Quant Research, Wyden Capital AG
Nicole Königstein:
Nicole Königstein: Chief Data Scientist, Head of AI & Quant Research, Wyden Capital AG
Nicole Königstein is a distinguished Data Scientist and Quantitative Researcher, currently working as Data Science and Technology Lead at impactvise, an ESG analytics company, and as Head of AI and Quantitative Research at Quantmate, an innovative FinTech startup focused on alternative data in predictive modeling. Alongside her roles in these organizations, she serves as an AI consultant across diverse industries, leading workshops and guiding companies from the conceptual stages of AI implementation through to final deployment.
As a guest lecturer, Nicole shares her expertise in Python, machine learning, and deep learning at various universities. She is a regular speaker at renowned AI and Data Science conferences, where she conducts workshops and educational sessions. In addition, she is an influential voice in the data science community, regularly reviewing books in her field and offering her insights and critiques. Nicole is also the author of the well-received online course, “Math for Machine Learning.
Ignacio Ruiz:
Ignacio Ruiz:
Ignacio Ruiz: Founder, MoCaX Intelligence
Ignacio Ruiz has been the Head of Counterparty Credit Risk Measurement and Analytics, Scotiabank, the head strategist for Counterparty Credit Risk, exposure measurement, for Credit Suisse, as well as the Head of Risk Methodology, equities, for BNP Paribas. In 2010, Ignacio set up iRuiz Consulting as an independent advisory business in this field. In 2014, Ignacio founded iRuiz Technologies to develop and commercialise MoCaX Intelligence.
Ignacio has several publications in the space of quantitative risk management and pricing. He has also published a comprehensive guide to the subject of XVA Desks and Risk Management.
He holds a PhD in nano-physics from Cambridge University.
Gala Dinner: Thursday 25th September, 20.00 til late.
Lo Stand Florio Restaurant – The Gala Dinner is complimentary for all conference delegates.
The Florio Stand, commissioned by Vincenzo Florio Jr. to Ernesto Basile in the early 1900s, was built during the Belle Epoque, a fine example of Art Nouveau architecture with incursions into Moorish art. The original idea was to create a large space for sports, entertainment, entertainment and socializing.
The Gala Dinner is complimentary for all conference delegates.
Menu:
Primo Piatto – First Course
Busiate alla Norma con melanzane fritte, salsa di pomodoro, ricotta salata e basilico
Busiate alla Norma with fried aubergines, tomato sauce, salted ricotta cheese and basil
Secondo Piatto – Second Course
Filetto di spigola al pan di agrumi siciliani, patate mascotte al rosmarino e pomodoro gratinato
Seabass fillet with Sicilian citrus breading, rosemary-scented mascotte potatoes and gratinated tomato
Dessert
Cannolo con ricotta home made
Cannolo with ricotta cheese home made
Bevande – Beverage
Mineral and sparkling water
Vino Tasca D’Almerita, Sallier de la Tour, Grillo
Amaro Florio
Contact Information:
- via Messina Marine, 40 – 90123 Palermo
- +39 091 730 8360
- info@standflorio.it
- Location Map
08.00 – 09.00: Registration and Morning Welcome Coffee
Morning Stream Chair: TBC
09.00 -09.45: The Paradigm Shift in Yield Curve Modeling
Andrei Lyashenko:
Head of Market Risk and Pricing Models, Quantitative Risk Management (QRM), Inc.
Andrei Lyashenko:
Andrei Lyashenko: Head of Market Risk and Pricing Models, Quantitative Risk Management (QRM), Inc.
Andrei Lyashenko is the head of Market Risk and Pricing Models at the Quantitative Risk Management (QRM), Inc. in Chicago. His team is responsible for research, implementation and support of pricing and risk models across multiple asset classes. In November 2019, he was awarded the prestigious Quant of the Year award, jointly with Fabio Mercurio from Bloomberg, L.P., for their Risk Magazine paper on modeling backward-looking rates.
Andrei is also adjunct professor at the Illinois Institute of Technology. Before joining the QRM in 1997, Andrei was on the mathematical faculty at the University of Illinois at Chicago and Iowa State University. Prior to coming to the US, he conducted academic research in applied math in Russia, Japan and Italy and published numerous research papers in the area of fluid stability in major mathematical journals. He holds a BSc in Mathematics from the Novosibirsk State University, Russia and a PhD in Mathematics from the Russian Academy of Science.
09.45 -10.30: Auto-encoding term-structure models – An arbitrage-free low-dimensionality interest rate model
Alexander Sokol:
Executive Chairman and Head of Quant Research, CompatibL
Alexander Sokol:
Alexander Sokol: Executive Chairman and Head of Quant Research, CompatibL
Alexander Sokol is the founder, Executive Chairman, and Head of Quant Research at CompatibL, a trading and risk technology company. He is also the co-founder of Numerix, where he served as CTO from 1996 to 2003, and the co-founder of Duality Group, where he served as CTO from 2017 to 2020.
Alexander won the Quant of the Year Award in 2018 together with Leif Andersen and Michael Pykhtin, for their joint work revealing the true scale of the settlement gap risk that remains even in the presence of initial margin. Alexander’s other notable research contributions include systemic wrong-way risk (with Michael Pykhtin, Risk Magazine), joint measure models, and the local price of risk (with John Hull and Alan White, Risk Magazine), and mean reversion skew (Risk Books, 2014).
Alexander earned his BA from the Moscow Institute of Physics and Technology at the age of 18, and a PhD from the L. D. Landau Institute for Theoretical Physics at the age of 22. He was the winner of the USSR Academy of Sciences Medal for Best Student Research of the Year in 1988.
10.30 – 11.00: Morning Break and Networking Opportunities
11.00 – 11.45: Curve Building, Autoencoders v PCA
Ivan Saroka:
Senior Quantitative Analyst, Schonfeld
Ivan Saroka:
11.45 – 12.30: Forecasting inflation and creating inflation based macro systematic trading strategies
In this talk we shall discuss an approach to forecasting inflation in both DM and EM using machine learning models, contrasting it to more traditional approaches, alongside a discussion of the types of data required. We shall also be discussing how such an approach has performed historically. Later, we discuss ways we can utilise such inflation forecasts within the systematic trading strategies for macro assets such as FX, and how they have performed in a live environment.
Saeed Amen
Saeed Amen
Saeed Amen: Turnleaf Analytics / Cuemacro / Visiting Lecturer at QMUL
Saeed has a decade of experience creating and successfully running systematic trading models at Lehman Brothers and Nomura. He is the founder of Cuemacro, Cuemacro is a company focused on understanding macro markets from a quantitative perspective. He is the author of ‘Trading Thalesians – What the ancient world can teach us about trading today’ (Palgrave Macmillan), and graduated with a first class honours master’s degree from Imperial College in Mathematics& Computer Science.
12.30 – 13.45: Lunch
Afternoon Stream Chair: TBC
13.45 – 14.30: Advances in Quantum Machine Learning
Quantum Machine Learning (QML) is an exciting area of quantum computing research that promises to be the first to deliver tangible quantum advantage and quantum utility since many of its algorithms are resistant to some types of noise and do not require large fault-tolerant quantum computers. QML is ideally suited to conducting experiments on the Noisy Intermediate-Scale Quantum (NISQ) computers. We are investigating what is behind the power of QML models and present the latest generation of QML algorithms with applications in quantitative finance.
Alexei Kondratyev:
Research Fellow: ADIA Lab and Visiting Professor: Imperial College London
Alexei Kondratyev:
Alexei Kondratyev: Research Fellow: ADIA Lab and Visiting Professor: Imperial College London
Alexei Kondratyev is Quantitative Research and Development Lead at Abu Dhabi Investment Authority (ADIA). Prior to joining ADIA in July 2021, he held quantitative research and data analytics positions at Standard Chartered, Barclays Capital and Dresdner Bank. Alexei holds MSc in Theoretical Physics from Taras Shevchenko National University of Kiev and PhD in Mathematical Physics from the Institute for Mathematics, National Academy of Sciences of Ukraine. He was the recipient of 2019 Risk magazine Quant of the Year award.
14.30 – 15.15: Quantum-Inspired Algorithms for Enhanced Cross-Sectional Dispersion Trading
There are areas in Finance where computational power has traditionally been the limiting factor — cross-sectional dispersion (CSD) is one of them. Quantum-inspired algorithms offer a breakthrough: they solve complex combinatorial optimization problems efficiently on classical hardware, removing the need to wait for quantum computing advancements.
Financial assets and portfolios exhibit rich qualitative and quantitative structures, forming complex clusters and hierarchies. Previously, unsupervised learning techniques were used to approximate this complexity. Now, leveraging quantum-inspired methods developed over decades at the Centro Superior de Investigaciones Científicas (CSIC) in Spain by the founders of the startup Inspiration-Q, it is possible to fully capture and monitor the entire clustering and hierarchical structure across asset features.
This approach enables, for the first time, an exact solution for market cross-sectional dispersion — where previously only approximations were possible.
Alejandro Rodríguez Domínguez:
Head of Quantitative Research & Analysis, Miraltabank
Alejandro Rodríguez Domínguez:
Alejandro Rodríguez Domínguez: Head of Quantitative Research & Analysis, Miraltabank
Alejandro Rodriguez Dominguez is Head of Quantitative Analysis at Miralta Bank since 2018, a Spanish bank with a focus on private and institutional investments, and more than 1 Bn of AUM. His team is responsible for the R&D of data-driven and AI-based solutions across the institution. His research focuses mainly on the applications of machine learning and statistics to portfolio risk diversification, correlation structures and causality, and developing risk management indicators. He is also a quant advisor at Inspiration-Q, working in the R&D of quantum-inspired systematic investment strategies.
Previously, Alejandro worked in London and Paris for several years in Société Générale, Nomura, BBVA and BNP Paribas since 2012, in trading and financial engineering roles. Alejandro pursues a PhD at University of Reading in Artificial Intelligence, and holds a M. Eng in Mining Engineering, a MSc in Financial Engineering from Imperial College London, a MSc in Computational Statistics, and a MSc in Artificial Intelligence from Cork Institute of Technology.
15.15 – 15.45: Afternoon Break and Networking Opportunities
15.45 – 16.30: Topic to be confirmed.
Dmitri Goloubentsev:
CTO, Head of Automatic Adjoint Differentiation, Matlogica
Dmitri Goloubentsev:
Dmitri Goloubentsev: CTO, Head of Automatic Adjoint Differentiation, Matlogica
Dmitri has 15 years of combined experience in model development working on C++ quant libraries. He worked as a Senior Quant Analyst in interest rate derivatives and played a leading role in delivering XVA solution at a major Canadian bank. Prior to focusing on AAD, he was responsible for construction of SIMM/MVA model. Dmitri earned his degree in Maths and Applied Maths from the Moscow State University.
16.30 – 17.15: “Risk-Aware Trading Portfolio Optimization”
We investigate portfolio optimization in financial markets from a trading and risk management perspective. We term this task Risk-Aware Trading Portfolio Optimization (RATPO), formulate the corresponding optimization problem, and propose an efficient Risk-Aware Trading Swarm (RATS) algorithm to solve it. The key elements of RATPO are a generic initial portfolio P, a specific set of Unique Eligible Instruments (UEIs), their combination into an Eligible Optimization Strategy (EOS), an objective function, and a set of constraints. RATS searches for an optimal EOS that, added to P, improves the objective function repecting the constraints.
RATS is a specialized Particle Swarm Optimization method that leverages the parameterization of P in terms of UEIs, enables parallel computation with a large number of particles, and is fully general with respect to specific choices of the key elements, which can be customized to encode financial knowledge and needs of traders and risk managers.
We showcase two RATPO applications involving a real trading portfolio made of hundreds of different financial instruments, an objective function combining both market risk (VaR) and profit&loss measures, constrains on market sensitivities and UEIs trading costs. In the case of small-sized EOS, RATS successfully identifies the optimal solution and demonstrates robustness with respect to hyper-parameters tuning. In the case of large-sized EOS, RATS markedly improves the portfolio objective value, optimizing risk and capital charge while respecting risk limits and preserving expected profits.
Our work bridges the gap between the implementation of effective trading strategies and compliance with stringent regulatory and economic capital requirements, allowing a better alignment of business and risk management objectives.
Marco Bianchetti:
Head of Market and Counterparty Risk IMA Methodologies, Intesa Sanpaolo
Marco Bianchetti:
Marco Bianchetti: Head of Market and Counterparty Risk IMA Methodologies, Intesa Sanpaolo
Marco holds a M.Sc. in theoretical nuclear physics (1995) and a Ph.D. in theoretical condensed matter physics (2000) from Università degli Studi di Milano. In 2000 he joined the Financial Engineering team of Banca Caboto (now IMI CIB Division of Intesa Sanpaolo), developing pricing models and applications for trading desks. In 2008 he moved to the Financial and Market Risk Management area of Intesa Sanpaolo. In 2015 he was appointed head of Fair Value Policy, developing the global fair/prudent/IPV policies and the valuation risk management framework of Intesa Sanpaolo Group. In 2021 he was appointed head of IMA Market Risk, in charge of regulatory market risk models and RWAs under Basel 2.5 and FRTB. Since Sept. 2024 he is head of Market and Counterparty Risk IMA Methodologies for Intesa Sanpaolo Group.
His work covers pricing and risk management of financial instruments, market risk, valuation risk, interest rates, XVAs, quasi-Monte Carlo, financial bubbles and portfolio optimization. He is the author of a few research papers, adjunct professor at Università di Bologna (2015-present) and at Università di Torino (2018-2023), member of Conference/Ph.D/Master Advisory Boards, and a frequent speaker at international conferences.
See also the LinkedIn profile.
17.15 – 18.00: QFC AI Panel
- In capital markets, can AI be trusted for:
- Knowledgebase and document repository search and ranking of results
- Internal or regulatory document generation with human review and approval
- Fully automated or human-supervised data extraction from unstructured text
- AI is not to be trusted for anything
- Which AI model family you found to be most effective in your AI applications – GPT, LLAMA, Mistral, Gemini, Anthropic?
- Why many banks are not yet comfortable with cloud-based AI even as they widely use the cloud for their most sensitive data?
- When can we expect to see tangible benefits from using AI – now, next year, in five years, or never?
Moderator:
Alexander Sokol:
Executive Chairman and Head of Quant Research, CompatibL
Alexander Sokol:
Alexander Sokol: Executive Chairman and Head of Quant Research, CompatibL
Alexander Sokol is the founder, Executive Chairman, and Head of Quant Research at CompatibL, a trading and risk technology company. He is also the co-founder of Numerix, where he served as CTO from 1996 to 2003, and the co-founder of Duality Group, where he served as CTO from 2017 to 2020.
Alexander won the Quant of the Year Award in 2018 together with Leif Andersen and Michael Pykhtin, for their joint work revealing the true scale of the settlement gap risk that remains even in the presence of initial margin. Alexander’s other notable research contributions include systemic wrong-way risk (with Michael Pykhtin, Risk Magazine), joint measure models, and the local price of risk (with John Hull and Alan White, Risk Magazine), and mean reversion skew (Risk Books, 2014).
Alexander earned his BA from the Moscow Institute of Physics and Technology at the age of 18, and a PhD from the L. D. Landau Institute for Theoretical Physics at the age of 22. He was the winner of the USSR Academy of Sciences Medal for Best Student Research of the Year in 1988.
Nicole Königstein:
Chief Data Scientist, Head of AI & Quant Research, Wyden Capital AG
Nicole Königstein:
Nicole Königstein: Chief Data Scientist, Head of AI & Quant Research, Wyden Capital AG
Nicole Königstein is a distinguished Data Scientist and Quantitative Researcher, currently working as Data Science and Technology Lead at impactvise, an ESG analytics company, and as Head of AI and Quantitative Research at Quantmate, an innovative FinTech startup focused on alternative data in predictive modeling. Alongside her roles in these organizations, she serves as an AI consultant across diverse industries, leading workshops and guiding companies from the conceptual stages of AI implementation through to final deployment.
As a guest lecturer, Nicole shares her expertise in Python, machine learning, and deep learning at various universities. She is a regular speaker at renowned AI and Data Science conferences, where she conducts workshops and educational sessions. In addition, she is an influential voice in the data science community, regularly reviewing books in her field and offering her insights and critiques. Nicole is also the author of the well-received online course, “Math for Machine Learning.
Ignacio Ruiz:
Ignacio Ruiz:
Ignacio Ruiz: Founder, MoCaX Intelligence
Ignacio Ruiz has been the Head of Counterparty Credit Risk Measurement and Analytics, Scotiabank, the head strategist for Counterparty Credit Risk, exposure measurement, for Credit Suisse, as well as the Head of Risk Methodology, equities, for BNP Paribas. In 2010, Ignacio set up iRuiz Consulting as an independent advisory business in this field. In 2014, Ignacio founded iRuiz Technologies to develop and commercialise MoCaX Intelligence.
Ignacio has several publications in the space of quantitative risk management and pricing. He has also published a comprehensive guide to the subject of XVA Desks and Risk Management.
He holds a PhD in nano-physics from Cambridge University.
Gala Dinner: Thursday 25th September, 20.00 til late.
Lo Stand Florio Restaurant – The Gala Dinner is complimentary for all conference delegates.
The Florio Stand, commissioned by Vincenzo Florio Jr. to Ernesto Basile in the early 1900s, was built during the Belle Epoque, a fine example of Art Nouveau architecture with incursions into Moorish art. The original idea was to create a large space for sports, entertainment, entertainment and socializing.
The Gala Dinner is complimentary for all conference delegates.
Menu:
Primo Piatto – First Course
Busiate alla Norma con melanzane fritte, salsa di pomodoro, ricotta salata e basilico
Busiate alla Norma with fried aubergines, tomato sauce, salted ricotta cheese and basil
Secondo Piatto – Second Course
Filetto di spigola al pan di agrumi siciliani, patate mascotte al rosmarino e pomodoro gratinato
Seabass fillet with Sicilian citrus breading, rosemary-scented mascotte potatoes and gratinated tomato
Dessert
Cannolo con ricotta home made
Cannolo with ricotta cheese home made
Bevande – Beverage
Mineral and sparkling water
Vino Tasca D’Almerita, Sallier de la Tour, Grillo
Amaro Florio
Contact Information:
- via Messina Marine, 40 – 90123 Palermo
- +39 091 730 8360
- info@standflorio.it
- Location Map
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