Majeed Simaan

• 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

• Global Association for Risk Professionals Member

• AFA – American 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

Book Chapter

1. Clark, B.; Siddique, A.; Simaan, M. (2023). Pricing Model Complexity: The Case for Volatility Managed Portfolios. Machine Learning and Data Sciences for Financial Markets: A Guide to Contemporary Practices. . Cambridge University Press.
   https://www.cambridge.org/ae/universitypress/subjects/mathematics/mathematical-finance/machine-learning-and-data-sciences-financial-markets-guide-contemporary-practices?format=HB.
2. Simaan, M.; Boudt, K.; Cela, M. (2020). In Search of Return Predictability: Application of Machine Learning Algorithms in Tactical Allocation. Machine LearninMachine Learning for Asset Management: New Developments and Financial Applicationsg and Asset Management. Hoboken: ISTE Ltd 2020. Published by ISTE Ltd and John Wiley & Sons, Inc..

Conference Proceeding

1. Simaan, M. (2016). Investigating bank failures using text mining. IEEE Symposium Series on Computational Intelligence (SSCI).
   https://ieeexplore.ieee.org/abstract/document/7850006.

Journal Article

1. Bonini, S.; Shohfi, T.; Simaan, M. (2023). Buy the Dip?. European Financial Management.
   https://onlinelibrary.wiley.com/doi/10.1111/eufm.12465.
2. Khashanah, K.; Simaan, M.; Simaan (2022). Do we need higher-order comoments to enhance mean-variance portfolios? Evidence from a simplified jump process. International Review of Financial Analysis. Hoboken.
   https://www.sciencedirect.com/science/article/pii/S1057521922000412?via%3Dihub.
3. Cui, Z.; Simaan, M. (2021). The opportunity cost of hedging under incomplete information: Evidence from ETF/Ns. Journal of Futures Markets (11 ed., vol. 41, pp. 1775-1796). Wiley.
   http://dx.doi.org/10.1002/fut.22252.
4. Clark, B.; Edirisinghe, C.; Simaan, M. (2021). Estimation Risk and Implicit Value of Index-Tracking. Quantitative Finance.
5. Simaan, M. (2021). Working with CRSP/COMPUSTAT in R: Reproducible Empirical Asset Pricing. The R Journal.
6. Clark, B.; Feinstein, Z.; Simaan, M. (2020). A machine learning efficient frontier. Operations Research Letters (5 ed., vol. 48, pp. 630-634).
7. Simaan, M.; Gupta, A.; Kar, K. (2020). Filtering for risk assessment of interbank network. European Journal of Operational Research.
   https://doi.org/10.1016/j.ejor.2019.06.049.
8. Simaan, M.; Simaan, Y. (2019). Rational explanation for rule-of-thumb practices in asset allocation. Quantitative Finance.
9. Simaan, M.; Simaan, Y.; Tang, Y. (2018). Estimation error in mean returns and the mean-variance efficient frontier. International Review of Economics & Finance.