Papa Momar Ndiaye
Teaching Associate Professor
School of Business
Research
I am a Financial Engineer and Quantitative Strategist with extensive industry experience in developing innovative solutions for portfolio construction and risk management. My research area is at the intersection of robust optimization, modeling and control of dynamic systems, and machine learning with applications to risk modeling, signal generation, portfolio allocation and management.
My latest research explores the application of Convex and Semi-definite Optimization combined with Deep Learning (DL), Reinforcement Learning (RL) and cutting-edge technologies like Large Language Models (LLMs) to enhance signal generation for improved portfolio performance. That includes using RL to train an Agent for building robust covariance matrices that incorporate alternative data such modeling industry boundaries. Another example is using LLMs to extract information from Earning Conference Calls and Deep Learning to predict volatility signal for financial securities. To improve the robustness of optimally allocated portfolios, I am also currently exploring the joint use of Semidefinite Optimization techniques and clustering algorithms for construction and dynamic updating of factor portfolios and covariance matrices.
My latest research explores the application of Convex and Semi-definite Optimization combined with Deep Learning (DL), Reinforcement Learning (RL) and cutting-edge technologies like Large Language Models (LLMs) to enhance signal generation for improved portfolio performance. That includes using RL to train an Agent for building robust covariance matrices that incorporate alternative data such modeling industry boundaries. Another example is using LLMs to extract information from Earning Conference Calls and Deep Learning to predict volatility signal for financial securities. To improve the robustness of optimally allocated portfolios, I am also currently exploring the joint use of Semidefinite Optimization techniques and clustering algorithms for construction and dynamic updating of factor portfolios and covariance matrices.
General Information
EDUCATION:
University Paris-IX Dauphine - Ph.D. in Applied Math for Engineering
University Paris-IX Dauphine - M.A. in Applied Math for Engineering
University of Dakar - B.S. in Mathematics and Applications
University Paris-IX Dauphine - Ph.D. in Applied Math for Engineering
University Paris-IX Dauphine - M.A. in Applied Math for Engineering
University of Dakar - B.S. in Mathematics and Applications
Institutional Service
- Hanlon Center Member
- Faculty Core Curriculum Working Group. Member
- Hanlon Financial Center Operating Committee Member
- Hanlon Financial Center Operating Committee Member
Professional Service
- CEO of Aleph1 Portfolio
Professional Societies
- ACM – Association for Computing Machinery Member
Selected Publications
Conference Proceeding
- Cao, Y.; Chen, Z.; Pei, Q.; Lee, N.; Subbalakshmi, K.; Ndiaye, P. (2024). ECC Analyzer: Extracting Trading Signal from Earnings Conference Calls using Large Language Model for Stock Volatility Prediction. Proceedings of the 5th ACM International Conference on AI in Finance (pp. 257-265). ACM.
https://doi.org/10.1145/3677052.3698689. - Ndiaye, P.; Sorine, M. (2000). Delay sensitivity of quadratic controllers. A singular perturbation approach. Proceedings of the IEEE Conference on Decision and Control (vol. 3, pp. 2799-2804).
Journal Article
- Lu, C.; Ndiaye, P.; Simaan, M. (2024). Improved estimation of the correlation matrix using reinforcement learning and text-based networks. International Review of Financial Analysis. Elsevier.
https://www.sciencedirect.com/science/article/pii/S1057521924005040?dgcid=author. - Lu, C.; Ndiaye, P.; Simaan, M. (2024). Improved estimation of the correlation matrix using reinforcement learning and text-based networks. International Review of Financial Analysis (Part A ed., vol. 96, pp. 103572). Elsevier BV.
https://doi.org/10.1016/j.irfa.2024.103572. - Ndiaye, P. (2011). Non-Gaussian optimization model for systematic portfolio allocation: How to take advantage of market turbulence?. No. Risk and Decision Analysis (4 ed., vol. 2, pp. 237-244). SAGE Publications.
https://doi.org/10.3233/rda-2011-0048. - Guigues, V.; Aid, R.; Ndiaye, P.; Oustry, F.; Romanet, F. (2009). Robust mid-term power generation management. no. Optimization (3 ed., vol. 58, pp. 351-371). Taylor and Francis.
https://doi.org/10.1080/02331930902741788. - Ndiaye, P.; Oustry, F.; Piolle, V. (2006). Semidefinite optimisation for global risk modelling. No. Journal of Asset Management (2 ed., vol. 7, pp. 142-153). Springer Science and Business Media LLC.
https://doi.org/10.1057/palgrave.jam.2240209. - Ndiaye, P.; Sorine, M. (2000). Delay sensitivity of quadratic controllers: A singular perturbation approach. SIAM Journal on Control and Optimization (6 ed., vol. 38, pp. 1655-1682).
- Ndiaye, P.; Sorine, M. (2000). Regularity of solutions of retarded equations and application to sensitivity of linear quadratic controllers to small delays. Journal of Mathematical Analysis and Applications (1 ed., vol. 245, pp. 189-203).
Preprint submitted to arXiv
Courses
Graduate Courses
- FE 630 (Portfolio Theory and Applications)
- FE 543 (Introduction to Stochastic Calculus for Finance)
- FIN 678 (Asset Allocation Practicum)
Undergraduate Course: QF302 (Market Microstructure and Trading)
- FE 630 (Portfolio Theory and Applications)
- FE 543 (Introduction to Stochastic Calculus for Finance)
- FIN 678 (Asset Allocation Practicum)
Undergraduate Course: QF302 (Market Microstructure and Trading)