Chi Seng Pun

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Associate Professor

Nanyang Technological University (NTU)

Singapore

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About

Chi Seng Pun is an Associate Professor at Nanyang Technological University, Singapore. His research areas include stochastic differential games, robust equilibrium controls, and data-driven portfolio optimization. Recent publications explore topics such as risk measurement in stock markets, Bayesian estimation for sequential portfolio learning, and the integration of economic and public health considerations in the context of the COVID-19 pandemic.

Recent Grants

Grant: Close

New Directions in Constrained Sparse Learning Problems: Theory and Applications

Open Date: 2021-11-01

Close Date: 2024-11-01

Grant: Close

Robust Impulse Control with Ambiguity Aversion and Applications

Open Date: 2018-01-01

Close Date: 2021-01-01

Grant: Close

Sparse Learning: Direct Estimation with Self-Calibrated Regularization

Open Date: 2017-09-01

Close Date: 2019-09-01

Grant: Close

Portfolio Selection with Advanced Statistical Techniques

Open Date: 2016-06-01

Close Date: 2020-06-01

Articles (15)

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2025

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2022

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2022

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2022

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2022

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2022

Collaborators (1)

Zhenzhen Yan

Nanyang Technological University (NTU)

SINGAPORE

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Chi Seng Pun

Research Interests

Contact this professor

About

Recent Grants

Articles (15)

Stock market simulator using hidden Markov generative model and its application in risk measurement

A Subgame Perfect Equilibrium Reinforcement Learning Approach to Time-Inconsistent Problems

Nonlocality, nonlinearity, and time inconsistency in stochastic differential games

Bayesian Estimation and Optimization for Learning Sequential Regularized Portfolios

Efficient social distancing during the COVID-19 pandemic: Integrating economic and public health considerations

Nonlocal fully nonlinear parabolic differential equations arising in time-inconsistent problems

Optimal multi-period transaction-cost-aware long-only portfolios and time consistency in efficiency

Data-Driven Distributionally Robust CVaR Portfolio Optimization Under A Regime-Switching Ambiguity Set

An Extended McKean–Vlasov Dynamic Programming Approach to Robust Equilibrium Controls Under Ambiguous Covariance Matrix

Incorporating plasmonic featurization with machine learning to achieve accurate and bidirectional prediction of nanoparticle size and size distribution

Machine-Learning-enhanced systemic risk measure: A Two-Step supervised learning approach

Optimal dynamic mean–variance portfolio subject to proportional transaction costs and no-shorting constraint

Persistent-homology-based machine learning: a survey and a comparative study

Robust Time-Inconsistent Stochastic Linear-Quadratic Control with Drift Disturbance

Robust classical-impulse stochastic control problems in an infinite horizon

Collaborators (1)

Zhenzhen Yan

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