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RESEARCH Expertise

Actuarial Mathematics & Statistics:
  • Demographic Statistics: population dynamics, environment and population spatial-temporal models, climate change and population, pollution and health, deprivation indexes
  • General insurance: claims reserving methods, claims processes and loss process modelling, risk measures​
  • Investment Decision Making: dynamic portfolio decision-making, price process modelling, wealth management and pension, Environmental Social Governance (ESG) and Divestment Practices.
  • Life insurance and Longevity: stochastic mortality, morbidity & population modelling.
Econometrics and Computational Finance:
  • 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
  • Application Domains: commodities, equity portfolios, Exchange Traded Funds, fixed income
    and bonds, environmental finance, digital finance - blockchain and crypto 
Risk Management:
  • Operational Risk: loss modelling, capital calculations and approximation, Loss Distributional Approach, Key Risk Indicators, dependence and copula modelling, cyber risk, natural disaster risk analysis
  • Portfolio Risk Analysis: optimal risk-adjusted investment decision-making, allocation principles, risk measure approximations, dynamic risk models.
  • Stress Testing Models: analysis of portfolio stress testing, fixed income interest rate stress testing.
  • Time Series: methodology and application, forecasting models, Bayesian time series methods, panel, term structure, state-space, non-linear, non-stationary methods, decomposition methodsmachine learning methods in time series
  • Multivariate Analysis: Copula methods, Feature Extraction Kernel Methods, multiple output Gaussian Process Models, extreme value theory and heavy-tailed processes
  • Monte Carlo Methods and Sampling: SMC Samplers, MCMC, RJ-MCMC, Cross EntropyVariational approximation
  • Spatial-Temporal Modelling: Gaussian process models, warped Gaussian processes, extreme value processes, quantile processes, graph regressions, tensor processes in space and time
  • Statistical Signal Processing:  multi-modal spatial process field reconstruction, sensor networks, participatory sensing and privacy, location verification methods, optimal network routing, communications engineering and channel modelling, detection and receiver design.
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