08.00 – 09.00: Registration and Morning Welcome Coffee
All Streams
09.00 – 09.45: Legends in Quants Finance – Bruno Dupire introduced by Helyette Geman
Followed by Keynote address: “Imputing the Price of Options in the Absence of a Market”
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.
Helyette Geman:
Ralph O’Connors Sustainable Energy Institute, Johns Hopkins University
Helyette Geman:
Helyette Geman: PhD, PhD: Ralph O’Connors Sustainable Energy Institute, Johns Hopkins University, Visiting Professor, Inland Norway University of Applied Sciences
Director, Commodity Finance Centre, Birkbeck-University of London
Ralph O’Connors Sustainable Energy Institute, Johns Hopkins University
Hélyette Geman is a Graduate of Ecole Normale Superieure in Mathematics and holds PhDs in Probability and Finance and a Masters’ degree in Theoretical Physics.
She has published more than 100 papers in Quantitative Finance; her book ‘Commodities and Commodity Derivatives’ is the reference in the field.
Hélyette Geman has taught in a number of prestigious Institutions worldwide and consulted for trading entities such as Louis Dreyfus, EDF Trading or Total Gas & Power.
Named ‘Financial Engineer of the Year 2022’ by the International Association for Quantitative Finance.
All Streams
09.45 – 10.30: Panel: Topic to be confirmed
10.30 – 11.00: Morning Break and Networking Opportunities
Morning Stream Chair:
To be confirmed
AI / LLMs / ML Stream
11.00 – 11.45: “Beating the Memory Wall: Tile Computing Patterns for Quant Finance”
To be confirmed
Ioana Boier:
Senior Principal Solutions Architect, NVIDIA
Ioana Boier:
Ioana Boier: Senior Principal Solutions Architect, NVIDIA
I have a Ph.D. in Computer Science from Purdue University. In addition, I have completed graduate coursework in Financial Mathematics at NYU and Big Data at Harvard University. Prior to joining Citadel, I was a Director in the Global Markets Division at BNP Paribas where I managed the Interest Rate Options & Inflation quantitative research team. Before transitioning into Finance, I was a research staff member at the IBM T. J. Watson Research Center.
AI / LLMs / ML Stream
11.45 – 12.30: AI Model Risk: Measurement, Reporting and Mitigation
Alexander Sokol:
Head of Quant Research, CompatibL
Alexander Sokol:
Alexander Sokol: 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 a co-founder of Numerix, where he served as CTO from 1996 to 2003.
Alexander won the 2018 Quant of the Year Award together with Leif Andersen and Michael Pykhtin for their joint work revealing the true scale of the settlement gap risk that remains in the presence of initial margin. Alexander’s other notable research contributions include systemic wrong-way risk (with Michael Pykhtin), joint measure models and the local price of risk (with John Hull and Alan White), the use of autoencoder manifolds for interest rate modelling (with Andrei Lyashenko and Fabio Mercurio), and the mean reversion skew.
Alexander graduated from high school at the age of 14 and earned 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.
12.30 – 13.45: Lunch
Afternoon Stream Chair:
To be confirmed
AI / LLMs / ML Stream
13.45 – 14.30: Practical Applications of Quantum Machine Learning in Quantitative Finance
Alexei Kondratyev:
Head of Risk at SW7 Group and Visiting Professor: Imperial College London
Alexei Kondratyev:
Alexei Kondratyev: Head of Risk at SW7 Group and Visiting Professor: Imperial College London
Alexei Kondratyev is Head of Risk at SW7 Group and previously the Quantitative Research and Development Lead at Abu Dhabi Investment Authority (ADIA). He has also 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.
AI / LLMs / ML Stream
14.30 – 15.15: “Using GenAI to estimate Geographical Exposures and mitigate Geo-Biases”
Arun Verma:
Head of Quantitative Research Solutions, Bloomberg
Arun Verma:
Arun Verma: Head of Quantitative Research Solutions, Bloomberg
Dr. Arun Verma joined the Bloomberg Quantitative Research group in 2003. Prior to that, he earned his Ph.D from Cornell University in the areas of computer science & applied mathematics. At Bloomberg, Mr. Verma’s work initially focused on Stochastic Volatility Models for Derivatives & Exotics pricing and hedging. More recently, he has enjoyed working at the intersection of diverse areas such as data science (for structured & unstructured data), innovative quantitative & machine learning methods and finally interactive visualizations to help reveal embedded signals in financial data.
15.15 – 15.45: Afternoon Break and Networking Opportunities
AI / LLMs / ML Stream
15.45 – 16.30: The 3 Steps to Optimal ML Function Approximation
Often, machine learning approaches struggle not due to lack of data or compute, but because they fail to address the fundamental mathematical challenges of high-dimensional approximation.
This talk outlines what is truly required—and what is not—to achieve robust ML approximation, focusing on key objectives: accuracy, fast evaluation, economically viable calibration, and full transparency.
We present a structured 3-step framework:
Managing the curse of dimensionality
Ensuring optimal convergence behaviour
Maintaining structural control of the approximation framework
Finally, we discuss the Model Risk Management implications, showing how a structured approach leads to more stable, explainable, and regulator-friendly models.
Ignacio Ruiz:
Founder, MoCaX Intelligence
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.
He holds a PhD in nano-physics from Cambridge University.
AI / LLMs / ML Stream
16.30 – 17.15: ‘Meet Claire: Your AI Co-Trader’
Is an AI co-trader actually possible today (or just hype)?
What tasks it can reliably own vs what must stay human
Architecture: tools, data pipelines, execution layer, and infrastructure
Evals: measuring edge, robustness, and failure modes
Guardrails: risk limits, compliance constraints, monitoring, and kill switches
Valer Zetocha:
Senior Quantitative Analyst, ED, Julius Baer
Valer Zetocha:
Valer Zetocha: Senior Quantitative Analyst, ED, Julius Baer
AI / LLMs / ML Stream
17.15 – 18.00: Garbage In, Garbage Out: How training data drives PnL
In quantitative finance, model architecture often receives the spotlight, yet training data frequently determines real world performance. This talk investigates the impact of training data selection in financial NLP by systematically evaluating four variations of the FinBERT framework across distinct training regimes.
We compare:
1. A standalone FinBERT model pre-trained on a 61GB+ financial corpus (FinancialWeb, Yahoo Finance, Reddit Finance QA, Wikipedia, and BooksCorpus)
2. FinBERT fine-tuned on synthetic financial sentiment data
3. FinBERT fine-tuned on GoEmotions – a 58k human-annotated Reddit dataset spanning 27 emotion categories
4. FinBERT fine-tuned on document and domain specific analyst labels derived from earnings call transcripts
Each model is evaluated on out-of-sample earnings call classification to assess real world generalisation. We then translate sentiment outputs into systematic long short trading strategies and compare their performance, isolating the economic value attributable solely to differences in training data.
Building on these findings, the talk concludes with a bottom up sector rotation strategy constructed exclusively from the document and domain specific model’s earnings call classifications. This framework demonstrates how high-fidelity, domain aligned training data can scale from individual security selection to sector level capital allocation.
The results underscore a central message: in financial AI applications, data provenance, label quality, and distributional alignment are often more consequential than incremental architectural innovation – with direct implications for alpha generation and portfolio construction.
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.
Gala Dinner: Thursday 1st October, 20.00 til late.
Palazzo Preca Restaurant – The Gala Dinner is complimentary for all conference delegates.
At Palazzo Preca, we’re more than just a restaurant – we’re a celebration of the Preca family’s love of food and a tribute to their culinary legacy. Founded by sisters Ramona and Roberta Preca, our restaurant is the culmination of years of hard work, dedication, and a deep appreciation for the power of food to bring people together.
08.00 – 09.00: Registration and Morning Welcome Coffee
Volatility / Options / Monte Carlo Stream
09.00 – 09.45: Legends in Quants Finance – Bruno Dupire introduced by Helyette Geman
Followed by Keynote address: “Imputing the Price of Options in the Absence of a Market”
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.
Helyette Geman:
Ralph O’Connors Sustainable Energy Institute, Johns Hopkins University
Helyette Geman:
Helyette Geman: PhD, PhD: Ralph O’Connors Sustainable Energy Institute, Johns Hopkins University, Visiting Professor, Inland Norway University of Applied Sciences
Director, Commodity Finance Centre, Birkbeck-University of London
Ralph O’Connors Sustainable Energy Institute, Johns Hopkins University
Hélyette Geman is a Graduate of Ecole Normale Superieure in Mathematics and holds PhDs in Probability and Finance and a Masters’ degree in Theoretical Physics.
She has published more than 100 papers in Quantitative Finance; her book ‘Commodities and Commodity Derivatives’ is the reference in the field.
Hélyette Geman has taught in a number of prestigious Institutions worldwide and consulted for trading entities such as Louis Dreyfus, EDF Trading or Total Gas & Power.
Named ‘Financial Engineer of the Year 2022’ by the International Association for Quantitative Finance.
Volatility / Options / Monte Carlo Stream
09.45 – 10.30: Panel: Topic to be confirmed
10.30 – 11.00: Morning Break and Networking Opportunities
Morning Stream Chair:
To be confirmed
Volatility / Options / Monte Carlo Stream
11.00 – 11.45: Unsmooth: R-Functions in Option Pricing
We introduce an R-function–based framework for smoothing non-smooth option payoffs and stabilising Greek estimation. Standard numerical methods struggle with discontinuities arising in digital, barrier and path-dependent derivatives, leading to unstable sensitivities and degraded Quasi Monte Carlo (QMC) performance. Our approach reformulates payoff conditions as systems of inequalities and encodes them using R-functions, producing smooth, arbitrarily differentiable representations that preserve the original payoff logic and domain constraints. Numerical experiments show that the method significantly reduces variance and improves the robustness of Delta and Gamma estimates, particularly in QMC settings. Beyond option pricing, the framework naturally extends to portfolio risk aggregation, constraint modelling, XVA exposure profiles and optimisation problems involving complex logical conditions, offering a unified analytical tool for structured financial modelling.
Julien Hok:
Head of Quantitative Analysts, Investec Bank
Julien Hok:
Julien Hok: Head Quantitative Analyst, Investec Bank
Julien Hok holds a PhD in Financial Mathematics from École Polytechnique, France. He began his career as a quantitative analyst in equity derivatives at Santander in London, where he spent six years. He then joined Citi in London, focusing on interest rate products for two years.
Julien later moved to Crédit Agricole CIB, working as a quantitative analyst on the hybrid derivatives desk for four years. He subsequently joined Investec Bank in London as an equity quantitative analyst, before being promoted to manager with responsibilities across both Equity and FX Derivatives, a role he held for three years. He is currently Head of Quantitative Analyst at Investec Bank, leading the quant team and supporting model development and trading across multiple asset classes.
Sergei Kucherenko
Senior Research Fellow, Imperial College
Sergei Kucherenko
Sergei Kucherenko: Senior Research Fellow, Imperial College
Sergei Kucherenko earned his MSc and PhD in applied mathematical physics from the Moscow Engineering Physics Institute in Russia. He has held several research and academic positions at universities across Russia, the United States, the UK, and Italy. Additionally, he has experience working in investment banking. Currently, he is a Senior Research Fellow at Imperial College London. He is also affiliated with BRODA Ltd., specialising in the application of Monte Carlo and Quasi-Monte Carlo methods, along with other advanced numerical techniques, in quantitative finance.
We discuss learning the dynamics of option markets using of our smooth arbitrage-free non-parametric option surfaces (SANOS) under both the statistical and risk-neutral measure.
Hans Buehler:
Co-CEO XTX, Visiting Researcher, University of Oxford
Hans Buehler:
Hans Buehler: Co-CEO XTX, Visiting Researcher, University of Oxford
12.30 – 13.45: Lunch
Afternoon Stream Chair:
Nikolai Nowaczyk:
Quantitative Analytics, Director, NatWest Group
Nikolai Nowaczyk:
Nikolai Nowaczyk: Quantitative Analytics, Director, NatWest Group
Volatility / Options / Monte Carlo Stream
13.45 – 14.30: General Stochastic Local Volatility Models
New methologies for Monte Carlo calibration of local volatility overlay of general stochastic volatility models.
This includes multi-factor, path dependent, rough and tough variations.
Why risk reports in stochadtic local volatility models can be noisy and what to do about it.
Application to exotic option pricing: autocalls, barriers, cliquets, var/vol products.
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.
Volatility / Options / Monte Carlo Stream
14.30 – 15.15: My Hot Shot Maverick Copula
Andrey Chirikhin:
Senior Credit Quant, Schonfeld
Andrey Chirikhin:
Andrey Chirikhin: Senior Credit Quant, Senior Credit Quant at SchonfeldSchonfeld
During the 30-year career in Finance, including 25 years as a quant, Andrey Chirikhin held a variety of front office QA positions in flow and structured credit, credit hybrid and XVA QA at Dresdner Kleinwort (now Commerzbank), HSBC, Goldman Sachs, Royal Bank of Scotland and Barclays. He also spent 4.5 years on the buyside, as Head of Risk/Head of QA at LetterOne Treasury Services, a $18bn private investment vehicle, and 1.5 years as a financial risk consultant for PwC and Deloitte.
15.15 – 15.45: Afternoon Break and Networking Opportunities
Volatility / Options / Monte Carlo Stream
15.45 – 16.30: Autoencoder Manifolds and Mean Reversion Skew
Alexander Sokol:
Head of Quant Research, CompatibL
Alexander Sokol:
Alexander Sokol: 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 a co-founder of Numerix, where he served as CTO from 1996 to 2003.
Alexander won the 2018 Quant of the Year Award together with Leif Andersen and Michael Pykhtin for their joint work revealing the true scale of the settlement gap risk that remains in the presence of initial margin. Alexander’s other notable research contributions include systemic wrong-way risk (with Michael Pykhtin), joint measure models and the local price of risk (with John Hull and Alan White), the use of autoencoder manifolds for interest rate modelling (with Andrei Lyashenko and Fabio Mercurio), and the mean reversion skew.
Alexander graduated from high school at the age of 14 and earned 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.
Volatility / Options / Monte Carlo Stream
16.30 – 17.15: Accurate Greeks for Non-smooth Payoffs through Smoothing Techniques Combined with AAD
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.
Volatility / Options / Monte Carlo Stream
17.15 – 18.00: Decomposing Hedge Backtesting Results: Insights for Model Validation & Model Optimization
Hedge backtesting is widely used in assessing models for pricing and hedging
The combination of cloud computing and coding assistants can support more rapid iteration
The literature on hedge backtesting as a formal tool for model validation is a little sparse
Though the material there suggests a route to formalizing the analysis and bolstering heuristics
We’ll pick up there and try to systematize things with the aid of some representative use cases
We’ll also touch on tangential issues of model under-specification and historical calibration
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.
Gala Dinner: Thursday 1st October, 20.00 til late.
Palazzo Preca Restaurant – The Gala Dinner is complimentary for all conference delegates.
At Palazzo Preca, we’re more than just a restaurant – we’re a celebration of the Preca family’s love of food and a tribute to their culinary legacy. Founded by sisters Ramona and Roberta Preca, our restaurant is the culmination of years of hard work, dedication, and a deep appreciation for the power of food to bring people together.
08.00 – 09.00: Registration and Morning Welcome Coffee
All Streams
09.00 – 09.45: Legends in Quants Finance – Bruno Dupire introduced by Helyette Geman
Followed by Keynote address: “Imputing the Price of Options in the Absence of a Market”
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.
Helyette Geman:
Ralph O’Connors Sustainable Energy Institute, Johns Hopkins University
Helyette Geman:
Helyette Geman: PhD, PhD: Ralph O’Connors Sustainable Energy Institute, Johns Hopkins University, Visiting Professor, Inland Norway University of Applied Sciences
Director, Commodity Finance Centre, Birkbeck-University of London
Ralph O’Connors Sustainable Energy Institute, Johns Hopkins University
Hélyette Geman is a Graduate of Ecole Normale Superieure in Mathematics and holds PhDs in Probability and Finance and a Masters’ degree in Theoretical Physics.
She has published more than 100 papers in Quantitative Finance; her book ‘Commodities and Commodity Derivatives’ is the reference in the field.
Hélyette Geman has taught in a number of prestigious Institutions worldwide and consulted for trading entities such as Louis Dreyfus, EDF Trading or Total Gas & Power.
Named ‘Financial Engineer of the Year 2022’ by the International Association for Quantitative Finance.
All Streams
09.45 – 10.30: Panel: Topic to be confirmed
10.30 – 11.00: Morning Break and Networking Opportunities
Morning Stream Chair:
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.
Trading & Interest Rate Modelling Stream
11.00 – 11.45: ‘Betting Platforms and Arbitrage Trading ‘
Helyette Geman:
Ralph O’Connors Sustainable Energy Institute, Johns Hopkins University
Helyette Geman:
Helyette Geman: PhD, PhD: Ralph O’Connors Sustainable Energy Institute, Johns Hopkins University, Visiting Professor, Inland Norway University of Applied Sciences
Director, Commodity Finance Centre, Birkbeck-University of London
Ralph O’Connors Sustainable Energy Institute, Johns Hopkins University
Hélyette Geman is a Graduate of Ecole Normale Superieure in Mathematics and holds PhDs in Probability and Finance and a Masters’ degree in Theoretical Physics.
She has published more than 100 papers in Quantitative Finance; her book ‘Commodities and Commodity Derivatives’ is the reference in the field.
Hélyette Geman has taught in a number of prestigious Institutions worldwide and consulted for trading entities such as Louis Dreyfus, EDF Trading or Total Gas & Power.
Named ‘Financial Engineer of the Year 2022’ by the International Association for Quantitative Finance.
Trading & Interest Rate Modelling Stream
11.45 – 12.30: Inflation, where will it be in 2027?
In this talk, we examine which CPI components are most important for driving headline inflation in the US. We discuss how we can approach forecasting inflation using machine learning models, and the types of data we can use for this. We also present some systematic trading strategies across macro markets using inflation forecasts as an input. We shall also be presenting some of forecasts for inflation going into 2027 for the major economies.
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:
To be confirmed
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.
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.
Trading & Interest Rate Modelling Stream
14.30 – 15.15: Robust Lower Bound for a Bermudan Option
We derive a sharp model-independent lower bound for any twice-exercisable Bermudan
We characterise it as a dual to the optimal sub-hedge of a generalized spread type
We show that there exists a common model (measure) under which all Bermudans with the same exercise dates are priced at their individual lower bounds
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
15.15 – 15.45: Afternoon Break and Networking Opportunities
Trading & Interest Rate Modelling Stream
15.45 – 16.30: Role of Central Banks: Implications for Rates Modelling and Pricing
Maria Makarova:
Vice President Quantitative Analyst, BNP Paribas
Maria Makarova:
Maria Makarova: 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:
Vladimir Chorniy: Managing Director, Head of Risk Model Fundamentals and Research Lab, Senior Technical Lead, BNP Paribas
Vladimir Chorniy started his career in finance as a founding member and later led Credit Risk Analytics team in Barclays Capital. Later he headed Risk Methodology and Analytics team in BNP Paribas responsible for methodologies covering counterparty risk (EE/PFE models), market risk (VAR, IRC, CRM), credit value adjustment, capital calculations and exotic derivative treatment. Later Vladimir has assumed a new role to determine long term strategy of risk modelling in BNP Paribas as Head of Risk Modelling Strategy and Senior Technical Lead. In 2022 whilst retaining his lead role in model development Vladimir founded and became the head of Risk Model Fundamentals and Research Lab to reflect evolving role and understanding of model risk. Vladimir holds a Ph.D. in Physics from Cambridge University.
Trading & Interest Rate Modelling Stream
16.30 – 17.15: Learning the Exact SABR Model
The pricing model calibration bottleneck
Theoretical framework: why SABR ?
Learning SABR with DNNs
Conclusions and perspectives
The SABR model is a cornerstone of interest rate volatility modeling, but its practical application relies heavily on the analytical approximation by Hagan et al., whose accuracy deteriorates for high volatility, long maturities, and out-of-the-money options, admitting arbitrage. While machine learning approaches have been proposed to overcome these limitations, they have often been limited by simplified SABR dynamics or a lack of systematic validation against the full spectrum of market conditions.
We develop a DNN SABR, a specialized Deep Neural Network (DNN) architecture that learns the true SABR stochastic dynamics using an very large training dataset (more than 200 million points) of interest rate Cap/Floor volatility surfaces, including very long maturities (30Y) and extreme strikes consistently with market quotations. Our dataset is obtained via high-precision unbiased Monte Carlo simulation of a special scaled shifted-SABR stochastic dynamics, which allows dimensional reduction without any loss of generality. Our SABR DNN provides arbitrage-free calibration of real market volatility surfaces and Cap/Floor prices for any maturity and strike with negligible computational effort and without retraining across business dates. Our results fully address the gaps in the previous machine learning SABR literature in a systematic and self-consistent way, and can be extended to cover any interest rate European options in different rate tenors and currencies, thus establishing a comprehensive functional SABR framework that can be adopted for daily trading and risk management activities.
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.
Managing Director, Global Head of Rates Quant Analytics, Barclays
Antoine Savine:
Antoine Savine: Managing Director, Global Head of Rates Quant Analytics, Barclays
Antoine Savine has worked for various Investment Banks since 1995, along Bruno Dupire, Leif Andersen and Marek Musiela. He was Global Head of Quantitative Research for Fixed Income, Currency and Credit Derivatives for BNP-Paribas 1999-2009, and currently works in Copenhagen for Danske Bank, where his work with Jesper Andreasen earned the In-House System of the Year 2015 Risk Award. His upcoming publications in Wiley’s Computational Finance series are dedicated to teaching the technologies implemented in those award-winning systems.
Antoine also teaches Volatility Modeling and Numerical Finance in the University of Copenhagen’s Masters of Science in Mathematics-Economics. The curriculum for his Numerical Finance lectures is being published by Wiley under the name “AAD and Parallel Simulations”.
Antoine holds a Masters from the University of Paris (Jussieu) and a PhD from the University of Copenhagen, both in Mathematics.
Gala Dinner: Thursday 1st October, 20.00 til late.
Palazzo Preca Restaurant – The Gala Dinner is complimentary for all conference delegates.
At Palazzo Preca, we’re more than just a restaurant – we’re a celebration of the Preca family’s love of food and a tribute to their culinary legacy. Founded by sisters Ramona and Roberta Preca, our restaurant is the culmination of years of hard work, dedication, and a deep appreciation for the power of food to bring people together.
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