Close
Autumn 2017
22 November 2017
Venue: D103, 25 Gordon Street
Speaker: Dr Marc Henrard
Title: Game of Benchmarks: LIBOR and IRON thrones
Abstract:
Over the last couple of years, interest rate benchmarks have appeared more in the news than in the previous 30 years. This is a combination of fundamental changes in the interest rate market, bad behaviour, including manipulation, and regulatory evolution. At this stage LIBOR is still sitting on the throne of benchmarks but this is expected to change soon. A game of power has started to establish its successors.
In the seminar we will review the origin of benchmarks and their fundamental importance for the financial market. We will also describe what LIBOR is and why its importance is decreasing. Different jurisdictions have proposed different types of potential successors. In particular the importance of overnight (ON) and secured rates is expected to increase. The benchmarks impacts are far reaching in term of practical financial impacts and theoretical financial mathematics. In the last part of the seminar, we will discuss open questions related to the mathematical finance aspects of benchmarks.
Please download the presentation slides here.
Bio:
Marc Henrard is an Advisory Partner at OpenGamma and visiting professor at University College London.
Over the last 20 years, Marc has worked in various areas of quantitative finance. His experience includes management positions in risk management, trading, software development, and quantitative research. In particular he has been Global Head of Interest Rate Modeling for Dexia Group, Deputy Head of Treasury Risk at the Bank for International Settlements (BIS) and Head of Quantitative Research and Deputy Head of Interest Rate Trading also at BIS.
Marc's research focuses on interest rate modeling, risk management and their efficient implementation. More recently he focused his attention to market infrastructure (CCP and bilateral margin, new products design, regulatory costs). He publishes on a regular basis in international finance journals, and is a frequent speaker at academic and practitioner conferences. He authored two recent books: The multi-curve framework: foundation, evolution, implementation and Algorithmic Differentiation in Finance Explained.
Marc holds a PhD in Mathematics from the University of Louvain, Belgium. He has been research scientist and university lecturer in Belgium, Italy, Chile and the United Kingdom.
6 December 2017
Venue: D103, 25 Gordon Street
Speaker: Dr Levent Menguturk
Title: Markov-Modulated Information Flows
Abstract:
We model information flows in continuous time that are generated by a number of information sources that are switched on and off at random times. In a novel approach, we explicitly relate the discovery of relevant new information sources to jumps in the conditional expectation process of a partially observed signal. We derive the resulting endogenous jump-diffusion dynamics, and show that it is a solution to the stochastic filtering problem associated with the Markov-modulated multivariate information process. We give a Feynman-Kac representation for the endogenous jump-diffusion, and produce an explicit expression for the size of the jumps. The jump-size distribution is a function of a weighted sum of those information processes that are activated at the jump time. The proposed approach can be applied broadly in signal processing, and an example in mathematical finance is provided. We consider a vanilla option and find that its Merton-type price can be expressed by a weighted sum of vanilla prices based on the possible combinations of active information processes at option maturity. The constructed information-flow models also lend themselves to the quantification of informational advantage in a competition where agents have diverse access to information sources.
Bio:
Levent Ali Menguturk holds an honorary lecturer position in the Department of Mathematics at University College London, and is an algorithmic quant at J.P. Morgan working on projects involving data analytics and machine learning for credit derivatives. Prior to his current position, he has spent around 5 years at Citi working in various front-office roles within the credit quant, algorithmic quant and strategic solutions teams. Prior to his career in the financial sector, Levent completed his PhD in Mathematics from Imperial College London. His research interests can be found broadly within stochastic processes, probability theory, mathematical finance and quantum mechanics.
13 December 2017 - cancelled
Venue: D103, 25 Gordon Street
Speaker: Dr Paul McCloud
Title: From Quadratic Gaussian to Quantum Groups: Dual *-Hopf Algebras in Financial Derivatives Pricing
Abstract:
Mathematical finance explores the consistency relationships between the prices of securities imposed by replicability and the absence of arbitrage. These economic principles, essentially algebraic in nature, can be applied in the context of quantum probability as well as the more familiar classical setting.
In this talk, mathematical finance is developed from the perspective of quantum groups. This naturally leads to the study of models based on restrictions of the quantum group, such as the Quadratic Gauss model, that retain much of the phenomenology of their parents within a more tractable domain, and extensions of the quantum group, such as the Linear Dirac model, with novel features unattainable in the classical case.
Reference: "Quantum Duality in Mathematical Finance"
Bio:
Paul began his career in finance in 2000 and has been at Nomura since 2008, working on exotic rates modelling, business resource management, and flow rates etrading. Highlights include the development of the CMS Triangle Arbitrage trade in 2010, founding the flow rates etrading quant team, and more recently managing the global fixed income quant team. Prior to working in finance Paul was a theoretical physicist, and in 2015 he returned to academia as an industry researcher in the Mathematics department at UCL, with research interests in applying quantum group methods to IR-FX hybrid derivative pricing.