MathFinance Digital Conference 2020
MathFinance Digital Conference
1 October 2020
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The MathFinance conference provides an excellent environment to learn about recent developments and networking with leading experts from both industry and academia
Enjoyable atmosphere, lots of networking, expert speakers, way to learn developments in the industry
The conference is a great opportunity to meet interesting people and develop new ideas on recent market trends. Special thanks to the organizers, they did a very good job
Dr. Bruno Dupire
Head of Quantitative Research
Bruno Dupire is head of Quantitative Research at Bloomberg L.P., 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.
Dr. Antoine Jacquier
Senior Lecturer in Mathematics / Director MSc Mathematics and Finance
Imperial College London
Searching for lambda: consistent roughness under P and Q
Antoine (Jack) Jacquier is a Senior Lecturer in Mathematics in Imperial College London and a visiting researcher at the Alan Turing Institute. His research focuses on volatility modelling, with a special emphasis on rough volatility, on applications of asymptotic methods in finance, and on machine learning techniques. He holds a PhD in Mathematics from Imperial College London, has co-edited a book on Asymptotic Methods in Finance, and has published about 40 papers in Mathematical Finance and Applied Probability.
Dr. Adil Reghai
Head of Quantitative Research, Equity and Commodity Markets
Adil Reghaï joined Natixis since 2008 where he is Head of Quantitative Research for Equities and Commodities. Graduated from Ecole Polytechnique (X92) and Ecole des Mines (P94), Paris, Adil was Head of Quantitative Research at Merrill Lynch, BNP Paribas and Calyon. He attended conferences on mathematical finance and has written numerous papers and articles.
He is the author of many scientific publications and a book Quantitative finance: back to basic principles http://www.palgrave.com/page/detail/quantitative-finance-/?isb=9781137414496
He is a lecturer at the mathematical master in Nice (SKEMA – France).
Dr. Nils Detering
Assistant Professor, Department of Statistics & Applied Probability
University of California, Santa Barbara
We price European-style options written on forward contracts in a commodity market, which we model with a state-dependent infinite-dimensional Heath-Jarrow-Morton (HJM) approach. We introduce a new class of volatility operators which map the square integrable noise into the Filipović space of forward curves, and we specify a deterministic parametrized version of it. For calibration purposes, we train a neural network to approximate the option price as a function of the model parameters. We then use it to calibrate the HJM parameters starting from (simulated) option market data. Finally we introduce a new loss function that takes into account bid and ask prices and offers a solution to calibration in illiquid markets. A key issue discovered is that the trained neural network might be non-injective, which could potentially lead to poor accuracy in calibrating the forward curve parameters, even when showing a high degree of accuracy in recovering the prices. This reveals that the original meaning of the parameters gets somehow lost in the approximation.
Dr. Jan Vecer
Professor of Quantitative Finance
Charles University, Prague
Prof. Jan Vecer works at the Charles University in Prague since September 2015 where he teaches courses in mathematical finance and stochastic analysis. From 2010 to 2015 he was a Professor of Finance at the Frankfurt School of Finance and Management. Professor Jan Vecer received his PhD in Mathematical Finance from Carnegie Mellon University. He held academic jobs at the University of Michigan and Kyoto University and at Columbia University where he was promoted to the rank of the Associate Professor in 2006. He works in various areas within the fields of Financial Statistics, Financial Engineering and Applied Probability. These areas include Option Pricing, Optimal Trading Strategies, Stochastic Optimal Control, and Stochastic Processes. The method he developed for pricing Asian Options is widely used both in academia and in the finance industry as a benchmark. He is an author of a monograph “Stochastic Finance: A Numeraire Approach” published by CRC Press. He has given about 100 invited talks in the conferences and in the world class universities, such as Harvard, Princeton, Stanford, University of Chicago, Cornell, Oxford, Cambridge, Humboldt, or Tsukuba.
Dr. Kay Pilz
Automated position management: practical aspects in modelling, implementation and interpretation
In this talk a generic analytical framework is presented, that allows to use Machine Learning techniques for risk and position management, trade analytics and autonomous hedging applications.
Firstly, the concept of the Python based framework is introduced. It is shown how it interfaces with a custom C++ Quant library, and how it utilizes Machine Learning modules such as TensorFlow. It is further demonstrated how use cases can be implemented with low effort and applied to arbitrary portfolios.
In the second part examples of risk and position management solutions using real world data and realistic market conditions are discussed. This includes the generation of sample data for the training of neural networks, the autonomous hedging of exotic option portfolios and the analysis of hedge adjustments under imperfect market conditions.
Kay Frederik Pilz is founder and managing partner of kinetic mind GmbH, a company located in Germany, providing services and solutions in Predictive Analytics and Quantitative Finance. Prior to his current position, he worked as a Senior Quantitative Analyst for the energy provider STEAG and E.ON Energy Trading, as well as for Sal. Oppenheim, an Investment Bank in Frankfurt, Germany. Kay develops and implements pricing and hedging functionalities for exotic derivatives on equities, precious metals and energy commodities. As a Senior Research Associate at the University of Technology in Sydney, Australia, he worked on a project on hybrid commodity and interest rate modelling, as well as on exotic option pricing in stochastic volatility models. Kay graduated in Mathematics from the University of Frankfurt and holds a PhD in Mathematical Statistics from the University of Bochum.
Dr. Jesper Andreasen
Head, Quant Research Development
Arbitrage Free Evolution of the Volatility Surface
Jesper Andreasen, aka the Kwant Daddy, is universal head of the SupaPhly Analytics team at Saxo Bank. Jesper’s career spans over 20 years in the derivatives industry including senior roles at General Re Financial Products, Bank of America, Nordea and Danske Bank. Jesper has twice received Risk Magazine’s quant of year award. He is an honorary professor of mathematical finance at the HC Ørsted Institute of Copenhagen University and holds a PhD in the subject from Aarhus University.
Prof. Rolf Poulsen
University of Copenhagen
A tour de force of finance-related poor maths; from social media over financial institutions to public administration. Names will be named; is one of them yours?
Dr. Jos Gheerardyn
CEO & Co-founder
Model risk and AI
Yields.io Co-Founder and CEO Jos Gheerardyn has built the first FinTech platform that uses AI for real-time model testing and validation on an enterprise-wide scale. A zealous proponent of model risk governance & strategy, Jos is on a mission to empower quants, risk managers and model validators with smarter tools to turn model risk into a business driver. Prior to his current role he has been active in quantitative finance both as a manager and as an analyst. Over the past 15 years he has been working with leading international investment banks as well as with award-winning start-up companies. He is the author of multiple patents applying quantitative risk management techniques to imbalance markets. Jos holds a PhD in superstring theory from the University of Leuven, Belgium.
Dr. Martin Keller-Ressel
Professor Stochastic Analysis
Technical University Dresden
Semi-Static and Sparse Variance-Optimal Hedging“ – Among theoretical results, we show that a variance swap can be reasonably hedged by three static option positions and dynamic hedging in the underlying
Martin Keller-Ressel received his Diploma in Computational Mathematics from TU Wien in 2005, followed by his PhD in 2009.
After positions at ETH Zurich and TU Berlin he was appointed professor at TU Dresden in 2013 and has received funding from the Excellence Initiative of the German Research Foundation to establish a new research group in stochastic calculus and financial mathematics.
Martin Keller-Ressel’s research interests are stochastic volatility, interest rate models, financial networks and dependency modelling. His research has been published in leading scientific journals such as Mathematical Finance, Quantitative Finance and Annals of Statistics
Dr. Frédéric Bossens
An introduction to MLV, benefits and comparison with SLV
Frédéric has worked in the field of financial modelling for more than 13 years, in Brussels (Fortis), London (Bnp-Paribas) and Singapore (Standard Chartered Bank). As a seasoned professional, Frédéric’s expertise is widely recognized by is pairs and co-workers. He used to teach an introductory course on financial modelling at University of Toulouse and co-authored several journal papers in the fields of financial derivatives pricing and control theory. His paper “Vanna-Volga Methods Applied to FX Derivatives: From Theory to Market Practice” became a flagship publication in the world of FX quantitative finance. He holds a Garp-FRM certification (Financial Risk Manager). Frédéric earned his PhD in mechanical and electrical engineering from University of Brussels (ULB).
Prof. Antonis Papapantoleon
National Technical University Athens
Model-free bounds for multi-asset options using option-implied information
Antonis Papapantoleon is an Assistant Professor of Mathematics at the
National Technical University of Athens and an Affiliated Researcher at
the Foundation for Research and Technology Hellas. Before moving to
Athens, he was a Juniorprofessor at TU Berlin, while his practical
experience includes nine months at Commerzbank and two years at the
Quantitative Products Laboratory, a joint venture between Deutsche Bank,
HU Berlin and TU Berlin. He received his PhD in Mathematics from the
University of Freiburg. His research interests include applications of
Lévy process in finance, term structure modeling, and model-free methods
in finance. His research has been published in leading journals such as
Mathematical Finance, Mathematics of Operations Research, and the
Transactions of the AMS, while he has co-edited a book on “Advanced
Modelling in Mathematical Finance” (Springer, 2016).
Dr. Katia Amrit Babbar
Visiting Research Fellow
Katia is currently a Visiting Research Fellow at Oxford University where she works alongside the Mathematical and Computational Finance Group as an Industry Connector. Her latest work focuses on applications of Machine Learning to Finance, in particular as a means to increase efficiency of Risk Management and Quant Analytics systems, a challenge she also explores through her start-up, AI Wealth Technologies. Katia’s career spans 18 years in the City, in multiple senior leadership roles, from Managing Director of the Electronic Foreign Exchange (FX) Trading desk and Head of FX Derivatives Research at Lloyds Bank, where she worked for 11 years. She has also worked as Senior FX Quant at Citi and UBS. Katia holds a BSc in Mathematics from UCL and a PhD in Stochastic Analysis applied to finance from Imperial College.
Prof.Dr. Thorsten Schmidt
Senior Financial Engineer
Thorsten Schmidt is Professor for Mathematical Stochastics at University Freiburg (successor of Ernst Eberlein) and Senior Financial Engineer at MathFinance AG. From 2017-2019 he was fellow of the Freiburg institute of Advanced Studies (FRIAS). Prior to this he was professor for Mathematical Finance at Chemnitz University of Technology since 2008, held a replacement Professorship from Technical University Munich in 2008 and was Associate Professor at University of Leipzig from 2004 onwards.
He is currently editor of a volume of Risks on the topic „Machine Learning in Finance, Insurance and Risk Management
Professor of Mathematics and Statistics
Berlin School of Economics and Law
Natalie Packham is Professor of Mathematics and Statistics at Berlin School of Economics and Law. Natalie has several years of industry experience as a front office software engineer at an investment bank, and is frequently involved in industry-related research and consulting projects. Her research expertise includes Mathematical Finance, Financial Risk Management and Computational Finance, and her academic work has been published in Mathematical Finance, Finance & Stochastics, Quantitative Finance, Journal of Applied Probability and many other academic journals. She is associate editor of “Methodology and Computing in Applied Probability” and co-chair of the GARP Research Fellowship Advisory Board. Natalie holds an M.Sc. in Computer Science from the University of Bonn, a Master’s degree in Banking & Finance from Frankfurt School, and a Ph.D. in Quantitative Finance from Frankfurt School.