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MathFinance Conference 2018

MathFinance hosts the annual Conference in Frankfurt which is tailored to the European finance community. Providing cutting-edge research and brand new practical applications, the conference is intended for practitioners in the areas of trading, quantitative or derivative research, risk and asset management, insurance as well as for academics studying or researching in the field of financial mathematics.

As always, we expect around 100 delegates both from the academia and the industry. This ensures a unique networking opportunity which should not be missed. A blend of world renowned speakers ensure that a variety of topics and issues of immediate importance are covered.

This event is a must for everyone in the quantitative financial industry.


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MathFinance Conference 2017

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Poster Session of the MathFinance Conference 2018:

Poster Session at the MathFinance Conference 2018:

We are pleased to once again host a poster session at the Conference. This is an excellent opportunity, particularly for doctoral and post-doctoral students to present their research results to a broader community of academics and professionals.

  Registration from December 1, 2017 until January 15, 2018
  Submission of posters latest by February 23, 2018
  Winner Award on March 12, 2018

Our independant jury consisting of Prof. Dr. Natalie Packham, Professor of Mathematics and Statistics, Berlin School of Economics and Law, Dr. Michael Einemann, Risk Methodology Specialist, Deutsche Bank AG and Prof. Dr. Andrija Mihoci, Professor of Statistics and Econometrics, Technical University Cottbus will nominate the best five posters to be presented at the conference. Participation in the Conference is mandatory for exhibiting the posters. The winner will receive free admittance to the whole conference.

Poster size should be A1 (841 x 594 mm /33.1 x 23.4 in). Please submit your ideas as a pdf document to




Dr. Tomasz Bielecki

Illinois Institute of Technology

Dr. Jürgen Hakala


Prof. Jessica James

Prof. Jessica James

Managing Director Senior Quantitative Researcher


Cross Currency Basis – what drives it?

The cross currency basis is a market dislocation in a fundamental sense, breaking some of the fundamental arbitrage conditions many of us grew up with.  Where does it come from, and how does it persist?  We drill down to show exactly what it is and why it is not traded away, revealing some really opportunities and dispelling some often-repeated myths.




Jessica James is the Senior Quantitative Researcher in the Rates Research team at Commerzbank, where she covers foreign exchange and fixed income. She joined Commerzbank from Citigroup where she was Global Head of the Quantitative Investor Solutions Group. Previously, she lectured in physics at Trinity College, Oxford.
Significant publications include ‘FX Option Performance’, ‘Handbook of Foreign Exchange’ (Wiley), ‘Interest Rate Modelling’ (Wiley), and ‘Currency Management’ (Risk books).
She is on the Board of the Journal of Quantitative Finance, a Fellow of the Institute of Physics, and is a Visiting Professor at UCL and Cass Business School.

Dr. Christian Kappen

Dr. Christian Kappen

Manager Financial Engineering


Approximating MVA along Low-Dimensional State Spaces

The Initial Margin Valuation Adjustment (MVA) is the present value of the opportunity and funding costs generated by future initial margin amounts. Computing MVA requires long-term risk neutral simulations of future initial margin requirements. In this talk, I present a novel method for approximating ISDA SIMM based MVA. It consists in projecting the SIMM measures from high-dimensional risk factor spaces to lower-dimensional subspaces parametrized by model state variables, calibrated model parameters or explanatory variables. ISDA SIMM based MVA can thus be approximated in terms of future sensitivities with respect to this more accessible and lower-dimensional vector of model-specific risk vectors. This projection method uses principal components analysis, and it fits in naturally with American Monte Carlo techniques.


Christian Kappen is Manager in the Financial Engineering unit at d-fine, a leading consultancy company in risk and finance. In this role he manages and delivers client projects on current valuation and risk management topics. He is specialized in the validation and the development of counterparty credit risk models. Christian previously worked as a researcher in pure mathematics at the University of Duisburg-Essen. He holds a Ph.D. and a Diploma from the University of Münster.

Bryan Liang


Dr. Jacopo Mancin

Dr. Jacopo Mancin


Barclays Capital

Volatility Swaps: PDE pricing improvements for LSV frameworks

The hedging of Volatility Swaps is model-dependent and highly exposed to volatility oscillations and the concavity effect. This, together with the increasing volume of traded Volatility Swaps, demanded for a fast and reliable PDE pricer. We present a development of the 1 Factor PDE pricer that is able to closely replicate LSV Montecarlo prices also in the context of fairly oscillating volatility term structure, while sensibly improving the computational performance. Furthermore, we developed some insights on the hedging of Volatility Swaps, showing a rather different behavior between short and long expiries.

Our analysis is based on FX Volatility Swaps, but can be equivalently applied to other asset classes.

Jacopo is a quant at Barclays, which he joined originally as intern in March 2017. His main focus is FX Volatility products PDE pricing. Prior to that he earned a PhD in Financial Mathematics at the LMU University in Munich, working on Model Uncertainty under the supervision of Prof. Dr. Francesca Biagini.

Dr William A. McGhee

Dr William A. McGhee

Global Head of Quantitative Analytics

NatWest Markets

Machine Learning in Quantitative Finance

  • History of Machine Learning : from MENACE to Alpha Go Zero
  • Machine Learning Algorithms
  • The changing role of Quants
  • Applications within Quantitative Finance
  • Practical considerations : from technology to governance.



William started his quant career in 1994 with J.P. Morgan in the Currency Options business. In 1998 he joined Deutsche Bank where he became Global Head of FX Quantitative Analytics. He worked between 2003 and 2009 at Citi in a number of roles encompassing structuring, exotics trading and heading up the FX Quantitative Strategy Group.
He joined RBS in 2009 to run the multi-asset Hybrid Quantitative Analytics team. In his current position as Global Head of Quantitative Analytics he is responsible for all modelling within the investment bank – from electronic trading to vanilla and complex derivatives.
William holds a PhD in Mathematical Physics, is a Fellow of the Institute of Mathematics and It’s Applications and serves on the UK Parliamentary and Scientific Committee.


Bereshad Nonas

Director Structured Finance Ratings

Scope Ratings AG

Prof. Rolf Poulsen

Prof. Rolf Poulsen

Professor of Mathematical Finance

 University of Copenhagen

How Accurately Did Markets Predict the GBP/USD Exchange Rate Around the Brexit Referendum?

We develop a model for the British pound/US dollar exchange rate around the Brexit referendum in June 2016. Applying the model to a combination of betting market odds and financial option prices, we show that while Leave was the least likely outcome (more unlikely, in fact, than betting odds would immediately suggest), predictions of the exchange rate conditional on the outcome of the referendum were accurate and the market was able to separate its views on the likelihood and the impact of Brexit.

Rolf Poulsen is a professor of Mathematical Finance at the Dept. of Math. Sciences at the University of Copenhagen. His main research interest is quantitative methods for pricing and hedging of derivatives. He will talk about exchange rate markets at length to all who will listen – and some who won’t.
Adil Reghaï

Adil Reghaï



The fair pricing under local stochastic volatility

Choosing the right mixture between local volatility and stochastic volatility has an important impact on valuation. We propose to link this blending factor with the dynamic of the volatility introducing new formulae linking the mixing weight and the skew stickiness ratio.


Adil Reghaï
Head of Quantitative Research for Equities and Commodities, Natixis

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 fiancé: back to basic principles
He is a lecturer at the mathematical master in Nice (SKEMA – France).

Artur Sepp

Artur Sepp

Quantitative Strategist

Julius Bär

Applications of machine learning for volatility trading and asset allocation

Most applications of quantitative trading and investing require the forecast of the future realized volatility as a key input. While there are many models for volatility measurement and forecast, the key decision is how to select the best models with the highest predicative power for a given application. I apply the methods of supervised machine learning and learning to rank for the machine-based selection of volatility models. I demonstrate applications of this framework to trading strategies in implied vs realized volatilities, to designing volatility-targeting products, and to implementing risk-based and risk-parity allocations.



Artur Sepp works as a Quantitative Strategist at the Swiss wealth management company Julius Baer in Zurich. His focus is on quantitative models for systematic trading strategies, risk-based asset allocation, and volatility trading. Prior to that, Artur worked as a front office quant in equity and credit at Bank of America, Merrill Lynch and Bear Stearns in New York and London with emphasis on volatility modelling and multi- and cross-asset derivatives valuation, trading and risk-managing. His research area and expertise are on econometric data analysis, machine learning, and computational methods with their applications for quantitative trading strategies, asset allocation and wealth management. Artur has a PhD in Statistics focused on stopping time problems of jump-diffusion processes, an MSc in Industrial Engineering from Northwestern University in Chicago, and a BA in Mathematical Economics. Artur has published several research articles on quantitative finance in leading journals and he is known for his contributions to stochastic volatility and credit risk modelling. He is a member of the editorial board of the Journal of Computational Finance. Artur keeps a regular blog on quant finance and trading at

Prof. Dr. Uwe Wystup

Prof. Dr. Uwe Wystup

Managing Director



FX Volatility 101 Exam

Uwe Wystup is managing director of MathFinance AG. Before, he has actively worked in FX derivatives trading as Financial Engineer, Global Structured Risk Manager and Advisor since 1992, including Citibank, UBS, Sal. Oppenheim and Commerzbank. He is one of the few hybrids in the world working in the intersection of the derivates market and academic research.
Uwe earned his PhD in mathematical finance from Carnegie Mellon University, is currently Professor of Financial Option Price Modeling and Foreign Exchange Derivatives at University of Antwerp and Honorary Professor of Quantitative Finance at Frankfurt School of Finance & Management.
Together with his team at MathFinance he provides independent (re-)structuring, valuation, model validation and expert witness services.
His first book Foreign Exchange Risk was published in 2002, quickly became the market standard and has also been translated into Mandarin. His second book FX and Structured Products appeared in 2006 with a fully updated and expanded second edition in 2017. Many of his papers appeared in scientific journals.