The mathematical sciences play an increasingly important role in the measurement, monitoring and management of risk in today’s increasingly complex financial markets and institutions. The realm of quantitative risk management has come to encompass a range of topics: market volatility, interest rate risk, credit risk, default risk, counterparty risk, high frequency trading, systemic risk, liquidity risk, which are challenging to model.
The recent turmoil in financial markets has highlighted the need for a better and more sophisticated approach to quantitative risk management and has stimulated the interest of industry for exploring new research approaches for facing current challenges.
This event will bring together academic researchers and industry experts in quantitative risk management and mathematical modelling in finance, to discuss and explore new challenges in quantitative risk management and emerging research directions, and mentor early career researchers.
The meeting will be open to graduate students and academics in mathematical sciences interested in the topics of the workshop. Participation of early career researchers, especially PhD students, is encouraged.
Aims and Objectives
- To present a panorama of current modelling challenges and recent research advances in quantitative risk management
- To raise awareness in the research community of the exciting and challenging research problems found in this field
- To expose PhD students and participants to current challenges in risk management, and provide examples of interactions between mathematical research and industry practice