All projects delivered in PythonCurrent areas of focus• Fixed income risk driver research - key rate tenors / Nelson-Siegel / PCA etc.• Ex-ante multi-curve simulations via parametric / non-parametric Monte-Carlo• Scenario conditioning through (analytical) conditional multivariate normal (point forecast)Future areas of focus:• Scenario conditioning through (analytical) minimum relative entropy (distributional forecast)• Adopt flexible probabilities approach for bootstrapped Monte-Carlo• Use copulas for fitting joint distributions - parametric and non-parametric• Research on other time series for multi-curve / risk driver modelling e.g. VAR, MVOU, MV-GARCH• Coherent risk measures for stress analysis e.g. use CDF distortions to weigh negative scenarios

Projects delivered in R where required• Total portfolio (multi-asset) risk• Conditional multivariate normal for stress testing - conditional expectation• Deterministic proprietary multi-period stress scenario

Projects generally delivered in R; some in PythonMulti-Asset • Research and back test investment ideas e.g. analyze effect of adding a new asset class to portfolio• Portfolio construction using MVO, ERC and volatility targeting• Back test static and dynamic asset allocation strategies with control over covariance matrix computation, rebalance frequency and delay of entry to market• Automated portfolio performance analysis• Developed proprietary risk signal and dashboardFixed Income• Construct sector- and rating-specific yield curves for specific fixed income universes• Fixed income portfolio construction through linear optimization methods

• RM to institutional clients such as Endowments, FIs and SWFs• Total AUM under care ~ SGD3 Billion• Experienced with Institutional mandate lifecycle including lead generation, RFP and tender, proposals, documentation, onboarding and client servicing