D
Duy-Minh Dang
Researcher at University of Queensland
Publications - 56
Citations - 731
Duy-Minh Dang is an academic researcher from University of Queensland. The author has contributed to research in topics: Partial differential equation & Interest rate derivative. The author has an hindex of 15, co-authored 52 publications receiving 613 citations. Previous affiliations of Duy-Minh Dang include University of Toronto & University of Waterloo.
Papers
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Better than pre-commitment mean-variance portfolio allocation strategies: A semi-self-financing Hamilton–Jacobi–Bellman equation approach
Duy-Minh Dang,Peter Forsyth +1 more
TL;DR: It is shown that if the portfolio wealth exceeds a threshold, an MV optimal strategy is to withdraw cash, and tests based on estimation of parameters from historical time series show that the semi-self-financing strategy is robust to estimation ambiguities.
Journal ArticleDOI
Better than Pre-Commitment Mean-Variance Portfolio Allocation Strategies: A Semi-Self-Financing Hamilton-Jacobi-Bellman Equation Approach
Duy-Minh Dang,Peter Forsyth +1 more
TL;DR: In this article, semi-self-financing strategies are built upon a numerical solution framework for Hamilton-Jacobi-Bellman equations, and can be readily employed in a very general setting, namely continuous or discrete rebalancing, jump-diffusions with finite activity, and realistic portfolio constraints.
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Continuous time mean‐variance optimal portfolio allocation under jump diffusion: An numerical impulse control approach
Duy-Minh Dang,Peter Forsyth +1 more
TL;DR: In this paper, the authors present an efficient partial differential equation method for continuous time mean-variance portfolio allocation problems when the underlying risky asset follows a jump-diffusion, and formulate the asset allocation problem as a 2D impulse control problem for each asset in the portfolio.
Journal ArticleDOI
Continuous Time Mean-Variance Optimal Portfolio Allocation Under Jump Diffusion: An Numerical Impulse Control Approach
Duy-Minh Dang,Peter Forsyth +1 more
TL;DR: In this article, the authors present an efficient partial differential equation (PDE) method for continuous time mean-variance portfolio allocation problems when the underlying risky asset follows a jump-diffusion.
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An efficient graphics processing unit-based parallel algorithm for pricing multi-asset American options
TL;DR: This work develops highly efficient parallel PDE‐based pricing methods on graphics processing units (GPUs) for multi‐asset American options by pricing American options written on three assets using a combination of a discrete penalty approach and a GPU‐based parallel alternating direction implicit approximate factorization technique.