Nuclear dimension of extensions of commutative C*-algebras by Kirchberg
algebras
Evington, S Ng, A Sims, A White, S (19 Sep 2024) http://arxiv.org/abs/2409.12872v2
Addendum: Testing structural balance theories in heterogeneous signed networks
Gallo, A Garlaschelli, D Lambiotte, R Saracco, F Squartini, T Communications Physics volume 7 issue 1 312-312 (20 Sep 2024)
A GCN-LSTM Approach For ES-Mini And VX Futures Forecasting
Michael, N Cucuringu, M Howison, S (01 Aug 2024)
Morpho-mechanics of pressurized cellular sheets
Chandler, T Ferria, J Shorthose, O Allain, J Maiolino, P Boudaoud, A Vella, D (19 Sep 2024)
Tue, 15 Oct 2024
14:30
L6

Undergraduate Summer Project Presentations: Computational experiments in the restricted universal enveloping algebra of sl 2

Joel Thacker
(University of Oxford)
Abstract

The problem of finding an explicit description of the centre of the restricted universal enveloping algebra of sl2 for a general prime characteristic p is still open. We use a computational approach to find a basis for the centre for small p. Building on this, we used a special central element t to construct a complete set of (p+1)/2 orthogonal primitive idempotents e_i, which decompose Z into one 1-dimensional and (p-1)/2 3-dimensional subspaces e_i Z. These allow us to compute e_i N as subspaces of the e_i Z, where N is the largest nilpotent ideal of Z. Looking forward, the results perhaps suggest N is a free k[T] / (T^{(p-1)/2}-1)-module of rank 2.

Log Neural Controlled Differential Equations: The Lie Brackets Make a Difference
Walker, B McLeod, A Qin, T Cheng, Y Li, H Lyons, T Proceedings of Machine Learning Research volume 235 49822-49844 (01 Jan 2024)
Thu, 24 Oct 2024
18:00
Citi Stirling Square, London, SW1Y 5AD

Backtesting with correlated data

Nikolai Nowaczyk
(NatWest Group)
Abstract

The important problem of backtesting financial models over long horizons inevitably leads to overlapping returns, giving rise to correlated samples. We propose a new method of dealing with this problem by decorrelation and show how this increases the discriminatory power of the resulting tests.


About the speaker
Nikolai Nowaczyk is a Risk Management & AI consultant who has advised multiple institutional clients in  projects around counterparty credit risk and xVA as well as data science and machine learning. 
Nikolai holds a PhD in mathematics from the University of Regensburg and has been an Academic Visitor at Imperial College London.
 

Registration for in-person attendance is required in advance.

Register here.

Subscribe to