World Business StrategiesServing the Global Financial Community since 2000

Main Conference Day 2: Friday 21st October

08.30 – 09.00: Morning Welcome Coffee

Volatility, Pricing & Modelling Stream

09.00 – 09.45: Topic to be confirmed

Milena Imamovic-Tomasovic:

Global Head of Product Valuation Methodologies and VCG Digital, Citi

Milena Imamovic-Tomasovic: Global Head of Product Valuation Methodologies and VCG Digital, Citi

Milena Imamovic-Tomasovic is a quantitative finance professional with over fifteen years of experience in banking. Her current role is Global Head of product valuation Methodologies and VCG Digital in Citi. Prior to that, she was Head of Business-Aligned Valuation Methodology within Global Valuation Group team and Head of CVA and Funding Methodology within GVG Methodology in Deutsche Bank. Before that Head of Analytics, EMEA at HSBC where she headed a cross-asset Valuation Control quant team. Before joining HSBC, Milena worked at TD Securities as a model validation and subsequently front office equity quant. She holds a Ph.D in theoretical physics from the University of Toronto.

Volatility, Pricing & Modelling Stream

09.45 – 10.30: Topic & Presenter to be confirmed

10.30 – 11.00: Morning Break and Networking Opportunities

Volatility, Pricing & Modelling Stream

11.00 – 11.45:Fast Pricing using Tensor Network Methods

Abstract: Tensor network methods are generally useful for high-dimensional problems, can outperform Monte Carlo and (partially) break the quantum advantage associated with amplitude estimation. A framework of interpolation-based tensor networks will be presented and practical performance gains demonstrated for pricing.

Sebastian Cassel:

Head of Valuation Model Risk, BNP Paribas

Sebastian Cassel: Head of Valuation Model Risk, BNP Paribas

Sebastian Cassel leads the Valuation Model Risk team at BNP Paribas covering model validation for trading book valuations including xVA. Previously, he worked in the Quantitative Research Centre at Royal Bank of Scotland Group developing market & counterparty risk models. Sebastian holds a D.Phil. in theoretical physics from Oxford University and M.Sci. from Cambridge University.

Volatility, Pricing & Modelling Stream

11.45 – 12.30: Chebyshev Tensors and Machine Learning in the computation of dynamic sensitivities

  • The computational cost of pricing in risk calculations
  • Mathematical properties of Chebyshev Tensors
    • Convergence properties and its implications for pricing function approximation
  • How to use Chebyshev Tensors in risk calculations
    • The problem of dimension
    • Different techniques to address the curse of dimensionality
  • Chebyshev Tensors and the computation of dynamic sensitivities
    • The composition technique and Chebyshev Tensors in the computation of dynamic sensitivities
    • Numerical results for dynamic sensitivities and dynamic initial

Mariano Zeron:

Head of Research and Development: MoCaX Intelligence

Mariano Zeron: Head of Research and Development: MoCaX Intelligence

Mariano leads our Research & Development work. He has vast experience in Chebyshev Spectral Decomposition, machine-learning and related disciplines, and their application to quantitative problems in the financial markets. Mariano holds a Ph.D. in Mathematics from Cambridge University.

12.30 – 13.30: Lunch

Volatility, Pricing & Modelling Stream

13.30 – 14.15: Conditional expectations: Model free, data driven, fast (with applications to pricing and hedging)

Jörg Kienitz:

Finciraptor, AcadiaSoft, University of Wuppertal and Cape Town

Jörg Kienitz: Finciraptor, AcadiaSoft, University of Wuppertal and Cape Town

Jörg Kienitz works in Quantitative Finance and Machine Learning  at Acadiasoft and the owner of the Finciraptor website (finciraptor.de). He is primarily involved in consulting on the development, implementation and validation of models. Jörg lectures at the University of Wuppertal as an Assistant Professor and is an Adjunct Associate Professor at UCT. He has addressed major conferences including Quant Minds and WBS Quant Conference. Jörg has authored four books “Monte Carlo Object Oriented Frameworks in C++” (with Daniel J. Duffy), “Financial Modelling” (with Daniel Wetterau), “Interest Rate Derivatives Explained I” and “Interest Rate Derivatives Explained II” (with Peter Caspers).

His SSRN author page is https://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=744396″

Volatility, Pricing & Modelling Stream

14.15 – 15.00: Using matrix pricing/collaborative filtering approaches to illiquid instrument pricing / use of ML in illiquid instrument pricing

Arun Verma:

Quantitative Research Solutions, Bloomberg, LP

Arun Verma: Quantitative Research Solutions, Bloomberg, LP

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.

15.00 – 15.20: Afternoon Break and Networking Opportunities

All Streams

15.20 – 16.00: Closing Presentation:

Machine Learning in Finance

Paul Bilokon:

Founder, CEO, Thalesians & Senior Quantitative Consultant, BNP Paribas

Paul Bilokon: Founder, CEO, Thalesians & Senior Quantitative Consultant, BNP Paribas

Dr. Paul Bilokon is CEO and Founder of Thalesians Ltd and an expert in electronic and algorithmic trading across multiple asset classes, having helped build such businesses at Deutsche Bank and Citigroup. Before focussing on electronic trading, Paul worked on derivatives and has served in quantitative roles at Nomura, Lehman Brothers, and Morgan Stanley. Paul has been educated at Christ Church College, Oxford, and Imperial College. Apart from mathematical and computational finance, his academic interests include machine learning and mathematical logic.

08.30 – 09.00: Morning Welcome Coffee

Machine Learning Stream

09.00 – 09.45: “Explainability of Learning Models”

Harsh Prasad:

Vice President, Morgan Stanley

Harsh Prasad: Vice President, Morgan Stanley 

Harsh currently works with Morgan Stanley in Quant Analytics Group. He started his career as a programmer focussed on developing data driven algos in the areas of speech recognition, image processing and bioinformatics. He then moved to financial risk management and over the last 12 years has worked in various roles through the life cycle of models. In these roles, he has been continuously enthusiastic to applying machine learning in problems related to behavioural assumptions, data quality, recommender systems,  model benchmarking and text analytics. His current role requires him reviewing all Machine Learning models used by the firm and providing direction to shaping AIML governance framework and strategy. He is also a visiting lecturer with universities and training institutions.

Machine Learning Stream

09.45 – 10.30: Topic & Presenter to be confirmed

10.30 – 11.00: Morning Break and Networking Opportunities

Machine Learning Stream

11.00 – 11.45: Deep Order Flow Imbalance: Extracting Alpha at Multiple Horizons from the Limit Order Book

Petter Kolm:

Clinical Full Professor and Director, Courant Institute of Mathematical Sciences, NYU

Petter Kolm: Clinical Full Professor and Director of the M.S. in Mathematics in Finance Program, Courant Institute of Mathematical Sciences, New York University & Partner, CorePoint-Partners.com

Petter Kolm is Clinical Full Professor and Director of the M.S. in Mathematics in Finance Program at the Courant Institute of Mathematical Sciences, New York University, since 2007. He is also Partner at CorePoint-Partners.com. Previously, Petter worked in the Quantitative Strategies group at Goldman Sachs Asset Management, developing proprietary investment strategies, portfolio and risk analytics in equities, fixed income and commodities.

Petter is the co-author of numerous academic journal articles and several well-known finance books including, ​Financial Modeling of the Equity Market: From CAPM to Cointegration​ (Wiley, 2006); ​Trends in Quantitative Finance (CFA Research Institute, 2006); Robust Portfolio Management and Optimization​ (Wiley, 2007); and ​Quantitative Equity Investing: Techniques and Strategies​ (Wiley, 2010).

Petter is a frequent speaker, panelist and moderator at academic and industry conferences and events. He is a member of the editorial boards of the International Journal of Portfolio Analysis and Management (IJPAM), Journal of Financial Data Science (JFDS), Journal of Investment Strategies (JoIS), and Journal of Portfolio Management (JPM). Petter is an Advisory Board Member of Alternative Data Group (ADG), AISignals and Operations in Trading (Aisot), Betterment (one of the largest robo-advisors) and Volatility and Risk Institute at NYU Stern. He is also on the Board of Directors of the International Association for Quantitative Finance (IAQF) and Scientific Advisory Board Member of the Artificial Intelligence Finance Institute (AIFI).

As an advisory board member, consultant, and expert witness, Petter has provided services in areas including alternative data, data science, econometrics, forecasting models, high frequency trading, machine learning, portfolio optimization with transaction costs, quantitative and systematic trading, risk management, robo-advisory, smart beta strategies, trading strategies, transaction costs, and tax-aware investing.

He holds a Ph.D. in Mathematics from Yale University; an M.Phil. in Applied Mathematics from the Royal Institute of Technology, Stockholm, Sweden; and an M.S. in Mathematics from ETH Zurich, Switzerland

Machine Learning Stream

11.45 – 12.30: Shallow vs. Deep Learning

Ioana Boier:

Independent

Ioana Boier: Independent

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.

12.30 – 13.30: Lunch

Machine Learning Stream

13.30 – 14.15: Topic & Presenter to be confirmed

Machine Learning Stream

14.15 – 15.00: Topic to be confirmed

Katia Babbar:

University of Oxford, Academic Visitor & QuantBright Consultant

Katia Babbar: University of Oxford, Academic Visitor & QuantBright Consultant

15.00 – 15.20: Afternoon Break and Networking Opportunities

All Streams

15.20 – 16.00: Closing Presentation:

Machine Learning in Finance

Paul Bilokon:

Founder, CEO, Thalesians & Senior Quantitative Consultant, BNP Paribas

Paul Bilokon: Founder, CEO, Thalesians & Senior Quantitative Consultant, BNP Paribas

Dr. Paul Bilokon is CEO and Founder of Thalesians Ltd and an expert in electronic and algorithmic trading across multiple asset classes, having helped build such businesses at Deutsche Bank and Citigroup. Before focussing on electronic trading, Paul worked on derivatives and has served in quantitative roles at Nomura, Lehman Brothers, and Morgan Stanley. Paul has been educated at Christ Church College, Oxford, and Imperial College. Apart from mathematical and computational finance, his academic interests include machine learning and mathematical logic.

08.30 – 09.00: Morning Welcome Coffee

Alt Data Stream

09.00 – 09.45: AI, Alt Data and Macroeconomic Forecasting

Alexander Denev:

Co – Founder, TurnLeaf Analytics | Lecturer in AI, University of Oxford

Alexander Denev: Co – Founder, TurnLeaf Analytics | Lecturer in AI, University of Oxford

Alexander has more than 15 years of experience in finance, financial modelling and machine learning and was previously Head of AI – Financial Services Advisory in Deloitte. Prior to joining Deloitte, he led the Quantitative Research & Advanced Analytics at IHS Markit where he created and maintained a center of excellence.

He has written several papers and two books on topics ranging from stress testing and scenario analysis to asset allocation. He has provided thought leadership engagements for conferences, journals and global forums. He also worked as a senior advisor to Risk Dynamics, an arm of McKinsey & Company. Previously he was Director of Risk Models at the Royal Bank of Scotland, where his responsibilities included development of the stress testing methodologies and credit models, and a Fixed Income Structurer for a front office desk. He has also held roles at the European Investment Bank and the European Investment Fund and has participated in the engineering of both the European Financial Stability Facility and the European Stability Mechanism.

Alexander Denev attained his Master of Science degree in Physics with a focus on Artificial Intelligence from the University of Rome, Italy, and he holds a degree in Mathematical Finance from the University of Oxford, UK, where he continues as a visiting lecturer.

Alt Data Stream

09.45 – 10.30: Machine Learning for Quant Strategies in Crypto Assets using On-Chain Data

    • On-chain fundamental and flows data for crypto assets
    • Features engineering
    • Generalized fused and group Lasso ML methods for feature selection and model training
    • Efficient solutions for high-dimensional estimation problem
    • Simulation of quant strategies using trained Lasso models

Artur Sepp:

Head Systematic Solutions and Portfolio Construction, Sygnum Bank

Artur Sepp: Head Systematic Solutions and Portfolio Construction, Sygnum Bank

Artur Sepp is Head Systematic Solutions and Portfolio Construction at Sygnum Bank’s Asset Management in Zurich, specializing in crypto assets and decentralized finance. Prior, Artur led quantitative research at a systematic hedge fund (Quantica Capital) focusing on data-driven investment strategies and asset allocation in global managed futures. In previous roles, Artur worked as front office Quant Strategist on the implementation of systematic solutions in private banking (Julius Baer), and on the full-cycle development of quantitative solutions and derivatives in investment banking (Merrill Lynch/BofA).

Artur is dedicated to connecting financial applications with science and technology. His expertise covers quantitative investing and asset allocation, modeling of financial markets and instruments, statistical and Machine Learning methods, modern computational and programming tools. His 14 years professional experience includes performing in leading roles at top quant teams in New-York, London, and Zurich.

Artur has a PhD in Mathematical Statistics from University of Tartu, an MSc in Industrial Engineering and Management Sciences from Northwestern University, and a BA cum laude in Mathematical Economics from Tallinn University of Technology. He is the author and co-author of several research articles on quantitative finance published in key journals. Artur is known for contributions to stochastic volatility and credit risk modelling with an H-index of 16. He is a member of the editorial board of the Journal of Computational Finance. Artur loves martial arts, water, and mountain sports.

10.30 – 11.00: Morning Break and Networking Opportunities

Alt Data Stream

11.00 – 11.45: The role of media sentiment in factor investing: Added value of alternative data

Svetlana Borovkova:

Head of Quantitative Modelling, Probability & Partners. Associate Prof, Vrije Universiteit Amsterdam

Svetlana Borovkova: Head of Quantitative Modelling, Probability & Partners and Associate Professor, Vrije Universiteit Amsterdam

Currently Head of Quantitative Modelling at Probability & Partners and Associate Professor at Vrije University Amsterdam, Dr Svetlana Borovkova has specialized in applying mathematical and statistical methods to problems within quantitative finance and risk management.

Dr Borovkova’s research extends in many areas, such as news analytics for finance, derivatives pricing, commodity markets and risk management in the face of new regulation. She is also a consultant for the Dutch Central Bank and the founder and principal consultant of DataDecisions: Financial Risk Consultancy.

Dr Borovkova is a frequent speaker on international conferences, such as Global Derivatives, Risk Minds, Bachelier Congress for Mathematical Finance, Sentiment Analysis and Behavioural Finance and others.

Previously she held an assistant professor position in Delft University of Technology and a trading analyst position in Shell Trading, London.

She got her PhD in 1998 from the University of Groningen, The Netherlands, and Oregon State University, USA and MSc degree in applied mathematics and computer science from Moscow and Utrecht.

Alt Data Stream

11.45 – 12.30: Topic & Presenter to be confirmed

12.30 – 13.30: Lunch

See ML & Vol Streams for Friday afternoon.

  • Discount Structure
  • Super early bird discount
    30% until 24th June 2022

  • Early bird discount
    25% until 29th July 2022

  • Early bird discount
    15% until 23rd September 2022

  • Special Offer
    When two colleagues attend the 3rd goes free!

  • 70% Academic Discount
    (FULL-TIME Students Only)

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