Head of Quantitative Modelling & Research

Roles & Responsibilities

Options Market Making, Calibration & Smile Modeling 

• Develop and own the quantitative infrastructure for quoting and risk managing vanilla and exotic options, including: 

• Real-time volatility surfaces 

• Greeks engines 

• Market-making and execution algorithms 

• Lead implementation of arbitrage-free volatility smile and skew models, including: 

• Smile parameterisation techniques: e.g. SVI, SABR, and Fengler’s arbitrage-free smoothing approaches 

• Local volatility models: Dupire local volatility for smile-consistent pricing and delta-hedging 

• Mixed local/stochastic volatility models: for capturing dynamic skew behaviour under stressed conditions 

• Build robust model calibration pipelines to liquid market instruments (e.g. vanilla options, forwards, futures) ensuring: 

• Fast convergence 

• Numerical stability 

• No calendar, butterfly, or vertical spread arbitrage 

• Extend volatility modelling to handle long-dated exotic derivatives: 

• American barriers, Asian accumulators, spread options, TARFs 

• Currency-denominated option structures with quanto and correlation features 

Term Structure & Correlation Modelling 

• Develop multi-factor forward curve models for commodities and currencies: 

• Gabillon Two-Factor Model for capturing commodity forward curve dynamics 

• Schwartz-Smith or CIR++ extensions for interest rate and inflation-linked exposure 

• Model and estimate cross-asset correlations, particularly between: 

• Commodities (oil, palm, soy, energy, etc.) 

• Currencies (USD, CNY, MYR, INR, etc.) 

• Freight and storage costs 

• Integrate correlation modeling into: 

• Structured products 

• Portfolio VaR / CVaR frameworks 

• Basis risk hedging strategies 

Real Assets & Physical Optionality 

• Build stochastic optimization and valuation frameworks for: 

• Crushing/refining spreads (e.g. soybean crush, palm kernel crush) 

• Storage and logistics assets as American swing options 

• Real-time asset monetization tools using Monte Carlo simulation, real options valuation, and basis path modeling 

• Incorporate physical constraints (capacity, delivery time, transport) into derivatives-driven optimization