Our research

The Institute for Financial and Actuarial Mathematics aims to conduct research in financial and actuarial mathematics, stochastic analysis and applications at an internationally recognised level. We seek interdisciplinary research within our university and collaborate with professionals in the financial services industry and other academics both in the UK and internationally.

Some of our main areas of research are:

Machine Learning in Finance

In recent years, machine learning (ML) has permeated the financial sector and reshaped quantitative finance methodologies. This research area harnesses ML technologies to both calibrate traditional financial stochastic models and to transition towards data-centric approaches. Using these techniques, we aim to tackle classically complex financial decision-making challenges such as analysing large financial datasets, pricing, and hedging complex financial instruments, mitigating operational risk, and forecasting price trends.

Financial inclusion

This area focuses on microinsurance and microfinance in low income countries with the aim of using the mathematical model developed to help alleviate poverty.

Extreme events

The insurance of extreme events such as pandemics is new area of research for the Institute. We are working with the Pandemic Institute on designing insurance contracts for pandemics. Research focusses on how society can protect and recover from these events and specifically how financial services can aid faster recovery.

Mortality and longevity modelling

The institute focuses research in this area towards informing policy details for insurance companies and pensions.

Financial mathematics

This area focuses on financial derivatives (financial contract on an underlying asset, group of assets, or benchmark, set between two or more parties). It also looks at pricing and hedging, interest rate modelling, optimal investment and consumption plans.

Stochastic control theory and stochastic processes

This is the most common area of expertise within the team. There is further expertise in stochastic analysis and applications, stochastic optimal control and applications, functional analysis, stochastic differential equations, data analysis and machine learning.

 

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