Monday 14th June: Day 1 WQF
Keynote: 'Why Storage Matters: the Case of WTI prices in Covid Times'
Professor of Mathematical Finance, Birkbeck – University of London & Johns Hopkins
Helyette Geman, PhD, PhD: Professor of Mathematical Finance, Birkbeck – University of London & Johns Hopkins
Helyette GEMAN is a Professor of Mathematical Finance at Birkbeck – University of London and at Johns Hopkins University. She is a Graduate of Ecole Normale Supérieure in Mathematics, holds a Masters degree in Theoretical Physics, a PhD in Probability from the University Pierre et Marie Curie and a PhD in Finance from the University Pantheon Sorbonne.
She has been a scientific advisor to a number of major energy and mining companies for the last 20 years, covering the trading of crude oil, natural gas, electricity as well as metals in companies such as EDF Trading, Louis Dreyfus or BHP Billiton and was named in 2004 in the Hall of Fame of Energy Risk.
Prof Geman was previously the head of Research and Development at Caisse des Depots. She has published more than 140 papers in major finance journals including the Journal of Finance, Mathematical Finance, Journal of Financial Economics, Journal of Banking and Finance and Journal of Business. She has also written the book entitled Insurance and Weather Derivatives and is a Member of Honor of the French Society of Actuaries.
Her research includes exotic option pricing for which she got the first prize of the Merrill Lynch awards, asset price modeling through the introduction of transaction time (JOF, 2000); she is one of the authors of the CGMY pure jump Levy model (2002). Prof Geman had organized in 2000 at College de France the first meeting of the Bachelier Finance Society, with Paul Samuelson, Robert Merton and Henry McKean as keynote speakers.
Her book, ‘Commodities and Commodity Derivatives’ is the reference in the field. She was a Scientific Expert on Agriculture for the European Commission and is on the Board of the Bloomberg Commodity Index.
She counts among her numerous PhD students Nassim Taleb, author of the Black Swan
Deep Hedging under Rough Volatility
We investigate the performance of the Deep Hedging framework under training paths beyond the (finite dimensional) Markovian setup. In particular we analyse the hedging performance of the original architecture under rough volatility models with view to existing theoretical results for those. Furthermore, we suggest parsimonious but suitable network architectures capable of capturing the non-Markoviantity of time-series. Secondly, we analyse the hedging behaviour in these models in terms of P&L distributions and draw comparisons to jump diffusion models if the the rebalancing frequency is realistically small.
Lecturer, King’s College London and Researcher, The Alan Turing Institute
Blanka Horvath: Lecturer, King’s College London and Researcher, The Alan Turing Institute
Blanka is a Honorary Lecturer in the Department of Mathematics at Imperial College London and a Lecturer at King’s College London. Her research interests are in the area of Stochastic Analysis and Mathematical Finance.
Her interests include 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.
"Using Neural Networks to speed up SABR consistent Cross-Smiles"
- Assuming EURUSD and USDJPY each follow a SABR process, under some mild assumption on correlations, a EURJPY consistent cross-smile can be inferred.
- Such models require a 4-factor Monte Carlo simulation and are too slow for calibration
- Here a NN is trained on a set of data in order to speed up Calibration of range of Cross-Smiles.
University of Oxford”, Academic Visitor & “QuantBright” Consultant
Katia Babbar: University of Oxford”, Academic Visitor & “QuantBright” Consultant
Climate Scenario Analysis and Stress Testing
- Introduction to climate risk stress testing and scenario analysis
- Incorporating climate change risk into stress testing, for example, the 2021 Bank of England stress test
- Challenges of scenario analysis
- Examples of climate change screening analysis and deep dives
Director of Sustainable Finance, South Pole
Rebecca Self: Director of Sustainable Finance, South Pole
Rebecca leads South Pole’s work with financial institutions globally, focusing on climate regulations and disclosures, the UN’s Sustainable Development Goal (SDG) environmental impact analysis for financial products and Net Zero. Formerly Chief Financial Officer of Sustainable Finance at HSBC Holdings plc, Rebecca has approximately two decades of holding senior leadership roles in the financial industry. In her previous role, Rebecca oversaw group-wide financial services relating to sustainable finance products, such as sustainability/green bonds, ESG (environmental, social, governance) asset management/private bank funds and commercial lending related to sustainability. In addition, Rebecca was responsible for HSBC’s external ESG reporting and investor relations – including the Task Force on Climate-related Financial Disclosures and corporate reporting on the UN SDGs. Rebecca has chaired the European Banking Federation industry SDG working group and has been a member of other advisory groups to progress non-financial reporting, for example, the Sustainability Accounting Standards Board and CDP. She holds a BSc in Economics and Politics, a Masters from the University of Cambridge (Centre of Sustainability Leadership), and is a Chartered Global Management Accountant.