Publications

12. Gupta, A., Lu, C., Simaan, M., & Zaki, M. J. When Positive Sentiment is Not so Positive: Textual Analytics and Bank Failures. Computational Economics (forthcoming). 

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 (link to interview)

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. (2021). 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) Generative 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 (link)

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.

Working Papers

• Cai, Z., Cui, Z., Lassance, N. & Simaan, M. The Economic Value of Mean Squared Error:  Evidence from Portfolio Selection 

  • Minor revision at Operations Research

  • Presented at the 2024 FMA Annual Meeting

• Bonini, S., Shohfi, T., Zhou, G. & Simaan, M. The Value of Data: Analyst Vs. Machine 

  • Reject and resubmit to JFQA

  • Presented at the 34th Conference on Financial Economics and Accounting (CFEA)

  • Presented at the 2024 China International Conference in Finance (CICF) - link to presentation/slides

  • Presented at the 2022 FMA Annual Meeting

  • Presented at the European FMA 2022 Conference

  • Presented at the Applied FMA 2022 (slides)

  • An earlier/different version was presented at FMA 2020 and Eastern Finance Association 2019

• Simaan, M. & Simaan, Y. Revisiting the CAPM: Pricing Ambiguity and the Size Factor

  • Revise and resubmit to the European Journal of Finance

• Bonini, S., Huang, S., & Simaan, M. Watching the FedWatch

• Lu, C & Simaan, M. Valuing Non-Myopic Views in Equity Premium Forecasting

  • Presented at the 2024 FMA Annual Meeting

• Huang, S., Simaan, M. & Tang, Y. Measuring Bank Complexity Using XAI

• Makridis, C. & Simaan, M. Balancing Returns and Responsibility: Evidence from Shrinkage-based Portfolios

  • Presented at the 2024 FMA Annual Meeting

  • Presented at the 2024 FMA European Conference 

  • Presented at the 2024 European Financial Management Association Annual Meeting

• Clark, B., Francis, B., & Simaan, M. Pricing Banks: Risk and Return in an Opaque Industry

  • Presented at the Diversity Emerging Scholar Initiative (DESI) via the FMA Program 2020 

  • An earlier version was presented at Eastern Finance Association 2018, FMA Annual Meeting 2017 

Work in Progress

• Simaan, M & Simaan, Y. Revisiting the CAPM: Pricing Ambiguity and the Size Factor

• Bhat, M., Clark, B., Siddique, A. & Simaan, M. Appraising Explanations: Explainable AI for Mortgage Lending

• Huang, S., Luvishis, E., Maksymenko, L., & Simaan, M. Hedging Linear Risk via Non-Linear Machine Learning