What is he best known for?
The fields of study he is best known for:
- Statistics
- Mathematical analysis
- Finance
His primary areas of investigation include Mathematical optimization, Mathematical finance, Mathematical economics, Stochastic control and Dynamic programming.
Huyên Pham has included themes like Isoelastic utility, Expected utility hypothesis and Stochastic volatility in his Mathematical optimization study.
His Mathematical finance study integrates concerns from other disciplines, such as Optimization problem, Incomplete markets and Portfolio.
His Mathematical economics research incorporates themes from Closed-form expression, Representation, Infimum and supremum and Asian option.
His Stochastic control research integrates issues from Markov process, Quantization, Optimal stopping, Markov chain and Monte Carlo method.
His biological study spans a wide range of topics, including Optimal control, Bounded function, Applied mathematics and Bellman equation.
His most cited work include:
- Mean‐Variance Hedging and Numéraire (165 citations)
- Optimal stopping, free boundary, and American option in a jump-diffusion model (148 citations)
- Dynamic programming and mean-variance hedging (141 citations)
What are the main themes of his work throughout his whole career to date?
Huyên Pham mainly focuses on Mathematical optimization, Stochastic control, Dynamic programming, Applied mathematics and Bellman equation.
His Mathematical optimization research is multidisciplinary, incorporating perspectives in Portfolio optimization, Portfolio and Selection.
His work deals with themes such as High-frequency trading, Hamilton–Jacobi–Bellman equation, Nonlinear system and Markov chain, which intersect with Stochastic control.
His Dynamic programming research also works with subjects such as
- Viscosity solution which intersects with area such as Variational inequality,
- Mathematical economics together with Semimartingale.
In the subject of general Applied mathematics, his work in Stochastic differential equation is often linked to Backward induction and Rate of convergence, thereby combining diverse domains of study.
Huyên Pham interconnects Expected utility hypothesis, Discrete time and continuous time and Trading strategy in the investigation of issues within Bellman equation.
He most often published in these fields:
- Mathematical optimization (46.04%)
- Stochastic control (40.00%)
- Dynamic programming (34.34%)
What were the highlights of his more recent work (between 2018-2021)?
- Applied mathematics (32.45%)
- Mathematical optimization (46.04%)
- Stochastic differential equation (22.26%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Applied mathematics, Mathematical optimization, Stochastic differential equation, Partial differential equation and Bellman equation.
His study in Applied mathematics is interdisciplinary in nature, drawing from both Numerical analysis, Uniqueness, Stochastic game and Optimal control.
Huyên Pham combines subjects such as Bayesian inference, Portfolio optimization, Portfolio and Probability measure with his study of Mathematical optimization.
His work in Partial differential equation addresses subjects such as Nonlinear system, which are connected to disciplines such as Artificial neural network, Deep learning, Artificial intelligence and Algorithm.
His research in Bellman equation intersects with topics in Dynamic programming, Stochastic control and Constraint.
Within one scientific family, he focuses on topics pertaining to Viscosity solution under Dynamic programming, and may sometimes address concerns connected to First-order partial differential equation.
Between 2018 and 2021, his most popular works were:
- Deep backward schemes for high-dimensional nonlinear PDEs (27 citations)
- Neural networks-based backward scheme for fully nonlinear PDEs (25 citations)
- Robust Markowitz mean‐variance portfolio selection under ambiguous covariance matrix (25 citations)
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