Machine learning and tactical asset allocation: Majeed Simaan

This will be an interactive session touching upon several topics:
1- Reproducibility of results in finance
2- Return Predictability
3- Pitfalls in Quant Finance
4- Tactical Asset Allocation using ML

Note: Some light reading materials and code snippets will be shared by the speaker one week before the meetup. Attendees are strongly encouraged to peruse those to benefit the most from this session.

Speaker Bio:
Majeed Simaan is a tenure-track assistant professor at the Department of Finance at Stevens Institute of Technology (SIT).

He holds a Ph.D. in Finance from RPI (2018). His research interests revolve around Banking and Risk Management, with emphasis on asset allocation and pricing.

He covers quantitative and computational finance-related research areas, such as financial networks (interconnectedness), machine learning, and textual analysis. His research has been presented globally and published in the International Review of Economics and Finance and the Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence.

At SIT, Majeed is currently teaching Financial Risk Management via the Financial Engineering graduate program.

Majeed's Homepage: http://personal.stevens.edu/~msimaan/
LinkedIn Profile: https://www.linkedin.com/in/majeed-simaan-85383045/
GitHub Link: https://github.com/simaan84