Majeed Simaan (msimaan)

Majeed Simaan

Assistant Professor

School of Business

Research

Research interests revolve around Financial Risk Management (FRM), primarily focusing on asset allocation and pricing. Applications cover quantitative and computational finance-related tools, such as financial networks (interconnectedness), machine learning, and textual analysis.

General Information

I joined Stevens as a tenure-track assistant professor of Finance and Financial Engineering at the School of Business after completing my Ph.D. at Rensselaer Polytechnic Institute (RPI) in 2018. A native of Galilee, I hold a BA and MA in Statistics from the University of Haifa, specializing in actuarial science. In Aug 2023, I became a certified Financial Risk Manager (FRM) via GARP.

Experience

Before Stevens, I worked as a part-time data scientist for Financial Network Analytics (FNA) during the summer of 2018. In 2012/13, I pursued graduate training in Mathematical Finance at the London School of Economics (LSE) for one year, during which I worked as a part-time Quantitative Analyst for Pantheon Ventures.

Institutional Service

  • Undergraduate Studies Committee Member
  • School of Business Research Committee Member
  • Financial Engineering Research Committee Member
  • Finance PhD Committee Member
  • Financial Engineering Research Committee Member
  • Finance PhD Committee Member
  • Brownbag Member
  • Committee for Teaching Effectiveness Evaluations Member
  • Finance search committee Member

Professional Service

  • Global Association for Risk Professionals Member

Professional Societies

  • AFA – American Finance Association Member
  • EFA – European Finance Association Member
  • FMA – Financial Management Association Member
  • NFA – Northern Finance Association Member
  • GARP – Global Association of Risk Professionals Member
  • EFA – European Finance Association Member
  • EFA – Eastern Finance Association Member

Selected Publications

Publications
11. 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 96, 103572.
10. Cai, Z., Cui, Z., &Simaan, M. (2024). Partial index tracking enhanced mean-variance portfolio. International Journal of Finance & Economics, 1–19
9. Lassance, N., Martin-Utrera, A. & Simaan, M. (2024) The Risk of Expected Utility under Parameter Uncertainty Management Science
8. Bonini, S., Shohfi, T. & Simaan, M. (2023) Buy the Dip? European Financial Management
Featured on Bloomberg Markets
7. Khashanah, K., Simaan, M. & Simaan, Y. (2022) Do We Need Higher-Order Comoments to Enhance Mean-Variance Portfolios? Evidence from a Simplified Jump Process. International Review of Financial Analysis,102068.
6. Clark, B., Edirisinghe, C., & Simaan, M. (2022). Estimation risk and the implicit value of index-tracking. Quantitative Finance, 22(2), 303-319.
5. Cui, Z., & Simaan, M. (2021) The opportunity cost of hedging under incomplete information: Evidence from ETF/Ns. Journal of Futures Markets, 41(11), 1775-1796.
4. Clark, B., Feinstein, Z. & Simaan, M. (2020) A Machine Learning Efficient Frontier. Operations Research Letters, 48(5), 630-634.
3. Simaan, M., Gupta, A., & Kar, K. (2020) Filtering for Risk Assessment of Interbank Network. European Journal of Operational Research, 280(1), 279-294.
2. Simaan, M., & Simaan, Y. (2019) Rational Explanation for Rule-of-Thumb Practices in Asset Allocation. Quantitative Finance, 19(12), 2095-2109.
1. Simaan, M., Simaan, Y., & Tang, Y. (2018) Estimation error in mean returns and the mean-variance efficient frontier. International Review of Economics & Finance, 56, 109-124.

Book Chapters
2. Clark, B., Siddique, A. & Simaan, M. (2023) Pricing Model Complexity: The Case for Volatility Managed Portfolios. book chapter in Machine Learning and Data Sciences for Financial Markets: A Guide to Contemporary Practices. Edited by A. Capponi and C.A. Lehalle. Cambridge University Press. (link to SSRN)
Presented the R/Finance 2022 Annual Meeting at the University of Illinois at Chicago (slides)
Presented the Fin&Tech Conference at St. John’s University (slides)
1. Boudt, K., Cela, M., & Simaan, M. (2020) In search of return predictability: Application of machine learning algorithms in tactical allocation. Machine Learning for Asset Management: New Developments and Financial Applications, 35-73.


Other Publications
3. Clark, B., Siddique, A. & Simaan, M. (2024) Use and Misuse of Interpretability in Machine Learning. Journal of Financial Transformation (The Capco Institute).
2. Simaan, M. (2021) Working with CRSP/COMPUSTAT in R: Reproducible Empirical Asset Pricing. The R Journal (featured on CRSP)
1. Gupta, A., Simaan, M., & Zaki, M. J. (2016) Investigating Bank Failures Using Text Mining. Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence.

Courses

Financial Risk Management
QF-435: Risk Management for Capital Markets
FE-535: Introduction to Financial Risk Management
FA-636: Advanced Financial Risk Analytics

Financial Engineering
FE-530: Introduction to Financial Engineering

Money and Banking
BT-440: Introduction to Banking and Credit

Ph.D. Level
FE 960 - Research in Financial Engineering
MGT 960 - Research in Finance