This project will consider the effects of social influence on financial market behaviour. We will look at how social networks – both at the individual and societal level – influence investment decisions, and investigate whether social influence can lead to market instability. We will further consider whether it is possible to detect social influence and incipient instability from market data in real time.
We will model the markets and social networks using a mixture of agent-based modelling, network dynamics and stochastic differential equations, using data assimilation to update models on the fly, with the ultimate aim of automating the detection of market instability and its causes. The stochastic models developed will be based on research in the sociology of crowd behaviour, thus linking qualitative and quantitative theories of crowd dynamics.
Applicants should have a first class degree in mathematics or a related discipline with a large quantitative component such as physics or statistics.