Khaldoun Khashanah (kkhashan)

Khaldoun Khashanah


School of Business

Babbio Center 543
(201) 216-5541


Active Research & Funding:

1. Algorithmic Contract Type Unified Standards, ACTUS project. Funded by: The Alfred P. Sloan Foundation 2012-current.

2. Modeling systemic risk in an international financial system of systems using clustering techniques and minimum spanning tree methodology, copula CoVaR.

3. Predictive analytics for large complex networks. Funded by the Stevens Accenture alliance.

4. Hawkes processes in finance

5. HFT - "On the Impact and Future of High Frequency Trading - Practitioners Version", download. Funded by IRRCi & NSF.

6. Principles versus rules in complex adaptive systems.

7. Bubbles and rare events: early warning financial systems.

8. Systems Taxonomy and Epistemology of Systems. Funded by NASA.


Director of Financial Engineering Division, 2002-present.

Initiated the Financial Engineering (FE) program at Stevens in 2002. The program offers a Graduate Certificate, a Master’s degree and a PhD in FE in FE with three tracks: Quantitative FE, Software Engineering in FE and Financial Systems Engineering, Financial Risk Engineering and Financial Software Engineering.
The FE division is one of the largest in the U.S. The FE Division introduced the first PhD in FE in the country in 2009 and currently has 37 PhD students in FE.
Co-Director of the MBA in Financial Engineering Program 2004-2012.

Initiated the program jointly with the Howe School of Management at Stevens in 2004.

Co-Project Director for the Hanlon Financial Systems Laboratory.

Institutional Service

  • Corporate Advisory Council Member
  • PhD in FE Committee Member

Professional Societies

  • IEEE – IEEE Member
  • IAQF – International Association of Quantitative Finance Member
  • SEM – Society of Economic Measurement Member

Selected Publications

Book Chapter

  1. Bozdog, D.; Florescu, I.; Khashanah, K.; Wang, J. (2011). A study of persistence of price movement using High Frequency Financial Data. Handbook of Modeling High-Frequency Data in Finance (pp. 27-46). Wiley.
  2. Bozdog, D.; Florescu, I.; Khashanah, K.; Qiu, H. (2011). Construction of Volatility Indices using a Multinomial Tree Approximation Method.. Handbook of Modeling High-Frequency Data in Finance (pp. 97-116).

Conference Proceeding

  1. Bundi, N.; Khashanah, K. (2019). Complex interbank network estimation: sparsity-clustering threshold. Studies in Computational Intelligence (vol. 813, pp. 487-498).
  2. Bundi, N.; Khashanah, K. (2018). Complex Interbank Network Estimation: Sparsity-Clustering Threshold. International Conference on Complex Networks and their Applications, Studies in Computational Intelligence book series (SCI, volume 813). Springer.

Journal Article

  1. 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.
  2. Khashanah, K.; Shao, C. (2021). Short-term volatility forecasting with kernel support vector regression. Quantitative Finance. Taylor Francis.
  3. Harsha, S.; Khashanah, K. (2020). HFT Technology for Retail Investors. International Journal of Industrial Electronics and Electrical Engineering.
  4. Harsha, S.; Khashanah, K. (2020). Compute-Communicate Continuum for Interconnectivity of Multiple Stock Exchanges. Int. J. of Advanced Computational Engineering and Networking (8 ed., vol. 8).
  5. Yang, H.; Shao, C.; Khashanah, K. (2019). Multi-scale Economic Dynamics: The Micro–Macro Wealth Dynamics and the Two-Level Imbalances of the Euro Crisis. Computational Economics (2 ed., vol. 53, pp. 587-616).
  6. Bozdog, D.; Florescu, I.; Khashanah, K.; Wang, J. (2011). Rare Events Analysis of High-Frequency Equity Data. Wilmott Journal (54 ed., vol. 2011, pp. 74-81).