LIU Peng
Assistant Professor of Quantitative Finance (Practice)
LKCSBFull-time Faculty
Email
liupeng@smu.edu.sg
liupeng@smu.edu.sg
Phone
68264917
68264917
Research Areas
▸
- Lee Kong Chian School of Business
- Operations Management
- Business Analytics
- Quantitative Finance
- Risk Management and Quantitative Trading
- Mathematical Finance
- Computational Methods and Simulations
- High-Frequency Data Analysis and Trading Strategies
- Asset Allocation and Portfolio Optimisation
Strategic Priorities
▸
- Digital Transformation
Education
| 2021 | Ph.D. in Statistics and Data Science (Part-time) National University of Singapore |
| 2015 | M.S in Business analytics (Full-time) National University of Singapore |
| 2012 | B. Eng. in Electronic Science and Technology (Full-time) Beijing Technology and Business University |
Current Position (s) Held
| 2022 - Now | Assistant Professor of Quantitative Finance (Practice) Lee Kong Chian School of Business, Singapore Management University |
| Apr 2019 - Jun 2022 | Manager, Advanced Analytics Singapore Chartered Bank, Singapore |
| Aug 2015 - Apr 2019 | Analytics Manager Marina Bay Sands, Singapore |
| Jan 2013 - Jul 2014 | Technical Support IBM, China |
Research Interests
Generalization in deep learning, sparse estimation, portfolio optimization using reinforcement learning, financial text mining, risk management, Bayesian optimization
Awards and Certificates
| Best Ph.D. Graduate Research Award, Department of Statistics and Data Science, NUS, 2020 |
| National Scholarship of China, School of Computer and Information Engineering, BTBU, 2009 |
| Google TensorFlow Developer Certificate, 2020 - 2023 |
| Project Management Professional, 2013 - 2017 |
Publications
- Peng Liu, Hailong Sun, Chung-Piaw Teo, and Mabel Chou. " Generalizing Bayesian Human-AI Collaboration: Theory and Application in Data-Scarce Environments." In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2026.
- Antoine Ledent, Peng Liu. Explainable Neural Networks with Guarantees: A Sparse Estimation Approach, Association for the Advancement of Artificial intelligence (AAAI), 2025
- Peng Liu. Seeking Better Sharpe Ratio via Bayesian Optimization. Journal of Portfolio Management (JPM), 2023
- Peng Liu, Haowei Wang, Qiyu Wei. Bayesian Optimization with Switching Cost: Regret Analysis and Lookahead Variants. International Joint Conference on Artificial Intelligence (IJCAI), 2023
- Peng Liu. An Integrated Framework on Human-in-the-Loop Risk Analytics. The Journal of Financial Data Science (JFDS) 5 (1): 58-64, 2023
- Peng Liu. A Review on Derivative Hedging using Reinforcement Learning, The Journal of Financial Data Science (JFDS) 5 (2): 136-145, 2023
- Chen Zichuan,Peng Liu. Towards Better Data Augmentation using Wasserstein Distance in Variational Auto-encoder, IEEE International Conference in Image Processing (ICIP), pp. 81-85, 2022
- Peng Liu, Ying Chen, Chung-Piaw Teo. Limousine Service Management: Capacity Planning with Predictive Analytics and Optimization, INFORMS Journal on Applied Analytics (IJAA), Vol. 51. No. 4, 2021
Books
- Peng Liu, Practical Bayesian Optimization, Apress, Springer Nature, 2023
- Peng Liu, The Statistics and Machine Learning with R Workshop, Packt, 2023
- Peng Liu, Quantitative Trading Strategies with Python, Apress, Springer Nature, 2023
- Peng Liu, Deep Learning Generalization, CRC Press, Taylor & Francis, 2025
- Peng Liu, Quantitative Risk Management with Python, Apress, Springer Nature, 2025
- Peng Liu, Deep Reinforcement Learning for Portfolio Optimization, CRC Press, Taylor & Francis (to appear in 2026)
- Peng Liu, Practical Asset Pricing with Python, Apress, Springer Nature (to appear in 2026)
- Peng Liu, Deep Learning Generalization II, CRC Press, Taylor & Francis (to appear in 2026)
Courses taught
- UG: COR1201 (Calculus), QF206 (Quantitative Trading Strategies), QF209 (Machine Learning in Quantitative Finance), QF210 (Reinforcement Learning in Quantitative Finance)
- PG: QF624/FNCE6065 (Machine Learning and Financial Applications, MQF & MAF), FNCE685 (Financial Risk Management, MBA), QF632/FNCE6066 (Financial Data Science, MQF & MAF)
Grants Received
- MOE Tier 1, 2025-2026
- Research Capability Building Fund (RCBF), 2023-2025
- ASEAN Business Research Initiative, 2024
