NEWS: The QRSLab is becomming a joint venture between members in UNSW and members in University College London effective August 1st 2012.
THIS URL LAST UPDATED
Aug. 1st 2012 - Please see new address at UCL Department of Statistics.
The QRSLab was founded by Dr. Gareth W. Peters (UNSW - UCL), Mark Young (formerly Deloitte) and Pavel Shevchenko (CSIRO) as a research laboratory in the Department of Mathematics and Statistics at the University of NSW in 2010. Since this time the laboratory has continued to grow, it will soon embark on a new international phase with a group in University College London, effective August 2012.
The agenda of this laboratory is to produce innovative and cutting edge statistical solutions to modelling in applied financial risk; hedge fund models and risk; time series models; traditional - market, credit and operational risk; and insurance statistical modelling. This laboratory is specifically interested in modelling applied numerical and methodological financial risk problems of signficance in the financial industry - as such it aims to develop strategic partnership of a research nature with industry.
QRSLab Research Interests and Expertise
- Model risk and insurance in Basel II / Basel III.
- Computations with copula models in finance and model risk (eg. Operational Risk, Insurance settings).
- Computations with meta distributions for risk modelling and associated model risk analysis.
- Risk sensitivity and stress testing frameworks under Basel II and Solvency II – properties, algorithms, methodology, impact on capital calculation and allocation.
- Dynamic latent factor models and copula for Operational Risk.
- Cointegration models, estimation, prediction and model risk.
- Risk metrics and analysis for the hedge fund and private equity sectors.
- Alpha stable heavy tailed models for financial risk.
- Claims reserving models for insurance - models and methodology.
- Project risk and pricing for mining/agriculture via multifactor sde commodity models online calibration and estimation via Sequential Monte Carlo and Adaptive MCMC.
- Tracking VaR and other risk measures dynamically through non-linear filtering techniques.
- Rare-Event modelling and simulation methodology.
IF YOU ARE INTERESTED IN COLLABORATION OPPORTUNITIES WITH THE QRSLab ON RESEARCH PROJECTS or honours, MSc., Ph.D. or Post doctoral opportunities - see contacts