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.

Mon, 14 Oct 2024
15:30
L3

A Mean Field Game approach for pollution regulation of competitive firms

Dr Giulia Livieri
(LSE)
Abstract

We develop a model based on mean-field games of competitive firms producing similar goods according to a standard AK model with a depreciation rate of capital generating pollution as a byproduct. Our analysis focuses on the widely-used cap-and-trade pollution regulation. Under this regulation, firms have the flexibility to respond by implementing pollution abatement, reducing output, and participating in emission trading, while a regulator dynamically allocates emission allowances to each firm. The resulting mean-field game is of linear quadratic type and equivalent to a mean-field type control problem, i.e., it is a potential game. We find explicit solutions to this problem through the solutions to differential equations of Riccati type. Further, we investigate the carbon emission equilibrium price that satisfies the market clearing condition and find a specific form of FBSDE of McKean-Vlasov type with common noise. The solution to this equation provides an approximate equilibrium price. Additionally, we demonstrate that the degree of competition is vital in determining the economic consequences of pollution regulation.

 

This is based on joint work with Gianmarco Del Sarto and Marta Leocata. 

https://arxiv.org/pdf/2407.12754

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