Quantitative Risk Solutions Lab
Prof. Gareth W. Peters
RESEARCH Expertise
Actuarial Mathematics & Statistics:
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Demographic Statistics: population dynamics, environment and population spatial-temporal models, climate change and population, pollution and health, deprivation indexes
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General insurance: claims reserving methods, claims processes and loss process modelling, risk measures
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Investment Decision Making: dynamic portfolio decision making, price process modelling, wealth management and pension, Environmental Social Governance and Divestment Practices.
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Life insurance and Longevity: stochastic mortality modelling, morbidity modelling, population modelling.
Econometrics and Computational Finance:
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Time series methods: time series regressions, panel regressions, isotonic regressions, functional time series regressions, causality testing, VARMAX models, dynamic copula models, state-space models, spatial-temporal models, cointegration methods, univariate and multivariate stochastic volatility models, Hawkes process, counting processes, Natural Language Processing time series for sentiment
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Application Domains: commodities, equity portfolios, Exchange Traded Funds, fixed income
and bonds, environmental finance
Risk Management:
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Operational Risk: loss modelling, capital calculations and approximation, Loss Distributional Approach, Key Risk Indicators, dependence and copula modelling, cyber risk, natural disaster risk analysis
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Portfolio Risk Analysis: optimal risk adjusted investment decision making, allocation principles, risk measure approximations, dynamic risk models.
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Stress Testing Models: analysis of portofolio stress testing, fixed income interest rate stress testing.
Statistics:
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Time Series: meth
odology and application, forecasting models, Bayesian time series methods,
panel, term structure, state-space, non-linear, non-stationary methods, decomposition methods,
machine learning methods in time series
• Multivariate Analysis: Copula methods, Feature Extraction Kernel Methods, multiple out-
put Gaussian Process Models, extreme value theory and heavy tailed processes
• Monte Carlo Methods and Sampling: SMC Samplers, MCMC, RJ-MCMC, Cross Entropy,
Variational approximation
• Spatial Temporal Modelling
Statistical Signal Processing:
• Communications Engineering and Channel Modelling
• Detection and Receiver Design
• Optimal Network Routing
• Participatory Sensing and privacy
• Location verification methods
• multi-modal spatial process field reconstruction
• Sensor networks
OUR VISION
The agenda of this laboratory is to produce innovative and cutting edge statistical solutions to modelling in applied Financial risk and Insurance.
We focus on innovative and emerging areas of high impact to research, regulators, industry and practitioners that require research level academic developments both of a fundamental nature and a practical quantitative nature.
This laboratory is specifically interested in modelling applied numerical and methodological financial risk problems of signficance in the financial industry and regulators - as such it aims to develop strategic partnership of a research nature with industry.
Big data analytics in risk and insurance is an emerging field that is covered in many reserach themes in this laboratory
The QRSLab is a collective of many different research skills and expertise in multidisciplinary working group.
IF YOU ARE INTERESTED IN COLLABORATION OPPORTUNITIES WITH THE QRSLab ON RESEARCH PROJECTS or honours, MSc., Ph.D. or Post doctoral opportunities - see contact information .
The axioms of Frederico Ardila (Todo Cuentan) nicely capture some axiomatic principles which we subscribe to in QRSLab.
Axiom 1. Mathematical potential is distributed equally among different groups, irrespective of geographic, demographic, and economic boundaries.
Axiom 2. Everyone can have joyful, meaningful, and empowering mathematical experiences.
Axiom 3. Mathematics is a powerful, malleable tool that can be shaped and used differently by various communities to serve their needs.
Axiom 4. Every student deserves to be treated with dignity and respect.