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Joint Risk & Stochastics and Financial Mathematics Seminar Series

PLEASE NOTE THAT THESE SEMINARS ARE POSTPONED UNTIL FURTHER NOTICE

One should really think of Statistics as a discipline which can be used to support other disciplines

The series aims to promote communication and discussion of research in the mathematics of insurance and finance and their interface, to encourage interaction between practice and theory in these areas, and to support academic students in related programmes at postgraduate level. 

This Seminar Series will be held in room 32L.LG.03, LSE. 

LSE maps and directions

All are welcome to attend these seminars. If you are attending from outside LSE please notify statistics@lse.ac.uk, so that we can ensure you have access to the seminar room.  


Current seminars in Lent Term 2020

Thursday 30th January, 12pm - Blanka Horvath 

Title: Data Anonymisation, Outliers Detection and Fighting Overfitting with Restricted Boltzmann Machines. 

Abstract: We propose a novel approach to the anonymisation of datasets through non-parametric learning of the underlying multivariate distribution of dataset features and generation of the new synthetic samples from the learned distribution. The main objective is to ensure equal (or better) performance of the classifiers and regressors trained on synthetic datasets in comparison with the same classifiers and regressors trained on the original data. The ability to generate unlimited number of synthetic data samples from the learned distribution can be a remedy in fighting overfitting when dealing with small original datasets. When the synthetic data generator is trained as an autoencoder with the bottleneck information compression structure we can also expect to see a reduced number of outliers in the generated datasets, thus further improving thegeneralization capabilities of the classifiers trained on synthetic data. We achieve these objectives with the help of the Restricted

Boltzmann Machine, a special type of generative neural network that possesses all the required properties of a powerful data anonymiser.

Based on joint work with Alexei Kondratyev and Christian Schwarz.

Thursday 13th February, 12pm - Soren Christensen

Title: Nonparametric learning in stochastic control - exploration vs. exploitation

Abstract: One of the fundamental assumptions in stochastic control of continuous time processes is that the dynamics of the underlying (diffusion) process is known. This is, however, usually obviously not fulfilled in practice. On the other hand, over the last decades, a rich theory for nonparametric estimation of the drift (and volatility) for continuous time processes has been developed. The aim of this talk is to make a first (small) step to bringing together techniques from stochastic control with methods from statistics for stochastic processes to find a way to both learn the dynamics of the underlying process and control good at the same time. To this end, we study a toy example motivated from optimal harvesting, mathematically described as an impulse control problem. One of the problems that immediately arises is an Exploration vs. Exploitation behavior as is well known in Machine Learning. We propose a way to deal with this issue and analyse the proposed strategy asymptotically.

Thursday 27th February, 12pm - Andreas Sojmark

Title: Dynamic default contagion: From Eisenberg--Noe to the Mean-field.

Abstract: In this talk, we will start by constructing a simple dynamic network model for interbank default contagion in the vein of the seminal clearing payment frameworks of Eisenberg & Noe (2001) and Rogers & Veraart (2013). The key feature, and main novelty, is a combination of stochastic dynamics for the banks’ external assets together with a realistic balance sheet methodology for determining early defaults (on interbank obligations). This then leads to the study of random default contagion events in continuous time. After first developing the model for a finite number of banks, we display a law of large numbers effect, which allow us to pass to the mean field limit of the interbank model. Thus, we can study default contagion via a conditional McKean–Vlasov type problem that respects the original network topology. 

Thursday 12th March, 12pm - Eduardo Ebi Jaber

Title: Reconciling rough volatility with jumps.

Starting from hyper-rough Volterra Heston models, for which we provide new existence uniqueness and stability results for any Hurst index in (-1/2,1/2], we construct a Markovian approximating class of one dimensional Heston-type models parametrized by a fast mean reversion speed and an unconstrained Hurst index. This class does not only enjoy closed form solutions for its Fourier-Laplace transform but is also able to mimick hyper-rough implied-volatility surfaces for any Hurst index in (-1/2,1/2]. More remarkably, for H smaller -1/2, sending the mean reversion to infinity, we obtain convergence of the reversionary model towards Lévy processes such as the IG-NIG.Joint work with Ryan McCrickerd.

Monday 23rd March, 12pm - Pamela Saliba

NOTE: This seminar will be held on a Monday, not a Thursday. The seminar will also be held in Columbia House, COL 6.15.

 

Past seminars in Michaelmas Term 2019/20

For all Michealmas Term seminars, please click here