Fri, 10 May 2024

12:00 - 13:00
Quillen Room

The orbit method for the Witt algebra

Tuan Pham
(University of Edinburgh)
Abstract

The orbit method is a fundamental tool to study a finite dimensional solvable Lie algebra g. It relates the annihilators of simple U(g)-module to the coadjoint orbits of the adjoint group on g^* . In my talk, I will extend this story to the Witt algebra – a simple (non-solvable) infinite dimensional Lie algebra which is important in physics and representation theory. I will construct an induced module from an element of W^* and show that its annihilator is a primitive ideal. I will also construct an algebra homomorphism that allows one to relate the orbit method for W to that of a finite dimensional solvable algebra.

Mon, 03 Jun 2024
16:00
L2

TBC

Nathan Creighton
(University of Oxford)
Abstract

TBC

Wed, 24 Apr 2024
16:00
L6

Harmonic maps and virtual properties of mapping class groups

Ognjen Tošić
(University of Oxford)
Abstract

It is a standard result that mapping class groups of high genus do not surject the integers. This is easily shown by computing the abelianization of the mapping class group using a presentation. Once we pass to finite index subgroups, this becomes a conjecture of Ivanov. More generally, we can ask which groups admit epimorphisms from finite index subgroups of the mapping class group. In this talk, I will present a geometric approach to this question, using harmonic maps, and explain some recent results.

Thu, 16 May 2024
18:00
Stirling Square, London, SW1Y 5AD

Frontiers in Quantitative Finance Seminar: Turning tail risks into tail winds: using information geometry for portfolio optimisation

Julien Turc
(BNP Paribas)
Further Information

Registration for the talk is free but required.

Register here.

Abstract

A wide variety of solutions have been proposed in order to cope with the deficiencies of Modern Portfolio Theory. The ideal portfolio should optimise the investor’s expected utility. Robustness can be achieved by ensuring that the optimal portfolio does not diverge too much from a predetermined allocation. Information geometry proposes interesting and relatively simple ways to model divergence. These techniques can be applied to the risk budgeting framework in order to extend risk budgeting and to unify various classical approaches in a single, parametric framework. By switching from entropy to divergence functions, the entropy-based techniques that are useful for risk budgeting can be applied to more traditional, constrained portfolio allocation. Using these divergence functions opens new opportunities for portfolio risk managers. This presentation is based on two papers published by the BNP Paribas QIS Lab, `The properties of alpha risk parity’ (2022, Entropy) and `Turning tail risks into tailwinds’ (2020, The Journal of Portfolio Management).

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