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This seminar series, which is hosted by the academic members of staff who are involved with the MSc in Financial Mathematics, presents applied research in financial mathematics and related topics.
Seminars (unless otherwise stated) will take place online on Wednesdays at 4pm in the Benthham Room LG11. If you require any more information on the Financial Mathematics Practitioners seminars please contact Dr Camilo Garcia Trillos (e-mail: camilo.garcia AT ucl.ac.uk or tel: 020-3108-1577).
23 February 2022
Speaker: Chris Kenyon (MUFG)
Title: Transparency principle for carbon emissions drives sustainable finance
To register to attend in person: https://www.eventbrite.com/e/271953840257
Place: UCL, Bentham House, Room LG11
To register to attend online: https://www.eventbrite.com/e/271963729837
Abstract:
Sustainability, focusing on climate change, is a key issue for financial market participants. WWF International , among many other global organisations, emphasise the crucial role financial organisations and systems play in decarbonising human life and in enabling drastic reduction of adverse impact to our planet. Alignment of financial market incentives and carbon emissions disincentives is key to limiting global warming. Regulators and standards bodies have made a start by requiring some carbon-related disclosures and proposing others. In our paper we go further and propose a Carbon Equivalence Principle: all financial products shall contain a description of the equivalent carbon flows from greenhouse gases that the products enable, as well as their existing description in terms of cash flows. This description of the carbon flows enabled by the project shall be compatible with existing bank systems that track cashflows so that carbon flows have equal standing to cash flows. We demonstrate that this transparency alone can align incentives by applying it to project finance examples for power generation and by following through the financial analysis. The financial requirements to offset costs of carbon flows enabled in the future radically change project costs, and risk that assets become stranded, thus further increasing costs. This observation holds whichever partner in the project bears the enabled-carbon costs. Mitigating these risks requires project re-structuring to include negative emissions technologies. We also consider that sequestered carbon needs to remain sequestered permanently, e.g., for at least one hundred years. We introduce mixed financial-physical solutions to minimise this permanence cost, and price to them. This complements previous insurance-based proposals with lesser scope. For financial viability we introduce project designs that are financially net-zero, and as a consequence are carbon negative. Thus we see that adoption of the Carbon Equivalence Principle for financial products aligns incentives, requires product redesign, and is simply good financial management driving sustainability.
Biography
Chris Kenyon is global head of quant innovation at MUFG, and also global head of XVA quant modelling for MUFG. Previously Chris was head of XVA quant research at Lloyds Banking Group, worked at Credit Suisse, and at Depfa Bank plc he was the post-crisis head of structured credit valuation after working on inflation-rates hybrids introducing new smile models. Chris formalized KVA and MVA with Andrew Green, as well as PFL as the replacement for PFE, and a short-rate multi-curve model, all in Risk Cutting Edge papers. More recently he introduced a climate change valuation adjustment (CCVA), and the Carbon Equivalence Principle (CEP) with Mourad Berrahoui and Andrea Macrina. Chris has a PhD from Cambridge University, published 17 papers in the Cutting Edge section of Risk magazine - twice joint top-cited author, and holds 10 US patents.
16 March 2022
To register to attend online: https://www.eventbrite.co.uk/e/ucl-financial-mathematics-practitioner-seminar-alexandre-antonov-online-tickets-288565034787
Speaker: Alexandre Antonov (Danske Bank)
Title: Alternatives to Deep Neural Networks in Finance
Abstract:
We develop two neo-classical methods for function approximations, the generalized stochastic sampling (gSS) and the functional tensor train (fTT) methods, that are high-performing alternatives to generic deep neural networks (DNNs) currently routinely proposed for function approximations in derivatives pricing and other quantitative finance applications. The new methods not only outperform DNNs for typical financial problems but also, unlike DNNs, satisfy stringent requirements that financial applications place on function approximations such as predictability and explainability.
Biography
Alexandre Antonov received his PhD degree from the Landau Institute for Theoretical Physics in 1997. He worked for Numerix during 1998-2017, then in Standard Chartered bank in London as a director. Currently, AA is a chief analyst at Danske Bank in Copenhagen. His activity is concentrated on modelling and numerical methods for interest rates, cross currency, credit and XVA, as well as Machine Learning and its applications. AA is an author for multiple publications in mathematical finance and a frequent speaker at financial conferences. He has received a Quant of Year Award of Risk magazine in 2016.