Modelling and Simulation with applications in Finance, Insurance and Economics

Interdisciplinary research has gained a lot of attention in recent years and this is also the case in finance and insurance as well as for topics at the interface of economics, physics and sociology (i.e., econophysics and sociophysics). Advanced mathematical modelling and new computational and statistical methods have already brought the research in these applied fields to a high level. Thanks to the increasing computing capacity of computers and the availability of large data sets, there is an upsurge of data analytic techniques, particularly machine learning and network science, that can be applied to complex economic and social systems, bringing novel methodologies and insights to traditional disciplines. Bayesian inference is also used to extract features from large data and has been shown as a promising approach for predictive analytics. Combined with computational and mathematical modelling, data science methods provide a full tool box to study the mechanisms driving economic and social phenomena, from descriptive patterns to forecasting system behaviour.

Our main scientific targets are:

  • To develop, analyse and implement numerical methods for dealing with highly sophisticated mathematical models in finance and insurance , e.g., jump-diffusion models, free boundary problems, swing contracts, and high-dimensional systems.
  • To develop, analyse and implement stochastic models to price securities and valuate liabilities at the interplay between finance and insurance, e.g., variable annuities and hybrid insurance liabilities.
  • To apply network modelling to study systemic risk in inter-bank networks, finding key players and means to improve the stability of such systems under perturbation and its robustness against failures.
  • To study the emergence of economic behaviour and opinions in local populations by using data-driven models of social networks, social influence, and opinion dynamics.
  • To estimate the controllability potential of particular financial and insurance institutions and businesses by using co-ownership networks and control theory, aiming to estimate the vulnerability and inter-dependence of institutions and firms.

To remain at the forefront of the international research community in the field of insurance studies, actuarial science, risk management for financial institutions, financial engineering, and behavioural economics and to be able to adapt to the continuously changing scientific challenges we want to join not only the expertise available in the Flemish research units but also broader in the Belgian and European research units with which there can be an active collaboration.

We not only aim at the interaction between different disciplines but also between fundamental and applied research. To stimulate scientific discussions and cooperative research projects, we will organise scientific meetings such as workshops and seminars or more informal meetings on a regular basis.

By organising conferences, we will give our researchers a platform on the one hand to communicate their results to a larger audience and on the other hand to interact with other experts or practitioners and to be updated about the state-of-the art in their domain. The planned winter/summer schools aim to engage the next-generation of PhD students in learning modern quantitative methods from data science, linking their background education to state-of-the-art data analytics and modelling methods of financial and insurance products and of economic phenomena.