Zachary Feinstein

Assistant Professor

School: School of Business

Building: Babbio Center

Room: 628

Phone: (201) 216-5414

Email: zfeinste@stevens.edu

Education
  • PhD (2014) Princeton University (Operations Research and Financial Engineering)
  • MA (2011) Princeton University (Operations Research and Financial Engineering)
  • BS (2009) Washington University in St. Louis (Systems Science and Engineering)
Research

Financial contagion and systemic risk
Risk measurement
Game theory and fixed point analysis
Set-valued analysis

General Information

Assistant Professor, Financial Engineering, Stevens Institute of Technology. August 2019 - Present.
Assistant Professor, Electrical & Systems Engineering, Washington University in St. Louis. August 2014 - August 2019.

Institutional Service
  • Stevens Society of Financial Engineers Chair
Professional Service
  • INFORMS Finance Section Secretary and Treasurer
Selected Publications
Journal Article
  1. Bichuch, M.; Feinstein, Z. (2022). A repo model of fire sales with VWAP and LOB pricing mechanisms. European Journal of Operational Research (1 ed., vol. 296, pp. 353-367).
    https://www.sciencedirect.com/science/article/pii/S037722172100374X.
  2. Feinstein, Z.; Rudloff, B.; Zhang, J. (2021). Dynamic set values for nonzero sum games with multiple equilibriums. Mathematics of Operations Research.
  3. Banerjee, T.; Feinstein, Z. (2021). Price mediated contagion through capital ratio requirements with VWAP liquidation prices. European Journal of Operational Research (3 ed., vol. 295, pp. 1147-1160).
    https://www.sciencedirect.com/science/article/pii/S0377221721002794.
  4. Ararat, C.; Feinstein, Z. (2020). Set-valued risk measures as backward stochastic difference inclusions and equations. Finance and Stochastics (vol. 25, pp. 43–76).
  5. Clark, B.; Feinstein, Z.; Simaan, M. (2020). A machine learning efficient frontier. Operations Research Letters (5 ed., vol. 48, pp. 630-634).
  6. Feinstein, Z. (2020). Capital regulation under price impacts and dynamic financial contagion. European Journal of Operational Research (2 ed., vol. 281, pp. 449-463). Elsevier BV.
    http://dx.doi.org/10.1016/j.ejor.2019.08.044.
  7. Feinstein, Z. (2019). Obligations with Physical Delivery in a Multilayered Financial Network. SIAM Journal on Financial Mathematics (4 ed., vol. 10, pp. 877-906). Society for Industrial & Applied Mathematics (SIAM).
    http://dx.doi.org/10.1137/18m1194729.
  8. Banerjee, T.; Feinstein, Z. (2019). Impact of contingent payments on systemic risk in financial networks. Mathematics and Financial Economics (4 ed., vol. 13, pp. 617-636). Springer Science and Business Media LLC.
    http://dx.doi.org/10.1007/s11579-019-00239-9.
  9. Feinstein, Z.; Pang, W.; Rudloff, B.; Schaanning, E.; Sturm, S.; Wildman, M. (2018). Sensitivity of the Eisenberg–Noe clearing vector to individual interbank liabilities. SIAM Journal on Financial Mathematics (4 ed., vol. 9, pp. 1286-1325).
  10. Feinstein, Z. (2017). Financial contagion and asset liquidation strategies. Operations Research Letters (2 ed., vol. 45, pp. 109-114). Elsevier BV.
    http://dx.doi.org/10.1016/j.orl.2017.01.004.
  11. Feinstein, Z.; Rudloff, B.; Weber, S. (2017). Measures of Systemic Risk. SIAM Journal on Financial Mathematics (1 ed., vol. 8, pp. 672-708). Society for Industrial & Applied Mathematics (SIAM).
    http://dx.doi.org/10.1137/16m1066087.
  12. Cassidy, A.; Feinstein, Z.; Nehorai, A. (2016). Risk measures for power failures in transmission systems. Chaos: An Interdisciplinary Journal of Nonlinear Science (11 ed., vol. 26, pp. 113110). AIP Publishing.
    http://dx.doi.org/10.1063/1.4967230.
Courses

FE 542 Time Series with Applications to Finance
FE 590 Statistical Learning in Finance
FE 620 Pricing and Hedging
FE 690 Machine Learning in Finance
BIA 610 Applied Analytics