Majeed Simaan
Assistant Professor
School of Business
Research
Research interests revolve around Risk Management, with a focus on Asset allocation and Pricing. Applications cover quantitative and computational finance-related tools, such as financial networks (interconnectedness), machine learning, and textual analysis.
Experience
Prior to joining SIT, I worked as a part-time data scientist for Financial Network Analytics (FNA) during the of summer 2018. While in London, I worked as a part-time Quantitative Analyst for Pantheon Ventures. I am also an active member of the R programming community, promoting a free software environment for statistical computing and data science.
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
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
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.
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
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
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