Rate My Professor Duy-Minh Dang

Dang's research specializes in computational finance, particularly the development of reliable numerical methods for solving stochastic control problems, such as those arising in portfolio optimization, option pricing under jump-diffusion and stochastic volatility models, mean-variance optimization, and valuation adjustments. His work addresses practical challenges in defined contribution superannuation and other financial instruments influenced by governance and societal needs. Notable publications include "Multi-period mean-buffered probability of exceedance in Defined Contribution portfolio optimization" (SIAM Journal on Financial Mathematics, 2026), "Numerical analysis of American option pricing in a two-asset jump-diffusion model" with Hao Zhou (Applied Numerical Mathematics, 2025), "Fourier neural network approximation of transition densities in finance" with Rong Du (SIAM Journal on Scientific Computing, 2024), "Practical investment consequences of the scalarization parameter formulation in dynamic mean-variance portfolio optimization" with Pieter M. van Staden and Peter Forsyth (International Journal of Theoretical and Applied Finance, 2021), "The surprising robustness of dynamic Mean-Variance portfolio optimization to model misspecification errors" (European Journal of Operational Research, 2021), and "Time-consistent mean-variance portfolio allocation: a numerical impulse control approach" (Insurance: Mathematics and Economics, 2018). In 2015, he received a UQ Early Career Researcher grant for his project on models, calibration, pricing, and risk-management of long-dated foreign exchange interest rate financial derivatives. Dang has supervised more than 100 MFinMath graduates and several PhD candidates, many of whom now hold prominent positions in global corporations. He actively collaborates with industries in FinTech, superannuation, energy, investment, banking, finance, IT, and commercial sectors, and has served on editorial boards of international journals.