Zachary Feinstein
Assistant Professor and Director of the Fintech Certificate Program
School of Business
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
Decentralized finance and automated market makers
Financial technology
Machine learning
Game theory and fixed point analysis
Set-valued analysis
Decentralized finance and automated market makers
Financial technology
Machine learning
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.
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
- Feinstein, Z.; Rudloff, B. (2024). Deep Learning the Efficient Frontier of Convex Vector Optimization Problems. Journal of Global Optimization.
- Feinstein, Z.; Halaj, G. (2023). Interbank asset-liability networks with fire sale management. Journal of Economic Dynamics and Control (vol. 155, pp. 104734).
- Amini, H.; Bichuch, M.; Feinstein, Z. (2023). Decentralized payment clearing using blockchain and optimal bidding. European Journal of Operational Research (1 ed., vol. 309, pp. 409-420).
- Feinstein, Z.; Sojmark, A. (2023). Contagious McKean-Vlasov systems with heterogeneous impact and exposure. Finance and Stochastics (vol. 27, pp. 663-711).
- Amini, H.; Feinstein, Z. (2023). Optimal network compression. European Journal of Operational Research (3 ed., vol. 306, pp. 1439-1455).
- Feinstein, Z.; Rudloff, B. (2023). Characterizing and Computing the Set of Nash Equilibria via Vector Optimization. Operations Research.
- Feinstein, Z.; Hurd, T. (2023). Contingent convertible obligations and financial stability. SIAM Journal on Financial Mathematics (1 ed., vol. 14, pp. 158-187).
- Feinstein, Z. (2022). Clearing prices under margin calls and the short squeeze. SIAM Journal on Financial Mathematics (4 ed., vol. 13, pp. SC113-SC122).
- Bichuch, M.; Feinstein, Z. (2022). Endogenous inverse demand functions. Operations Research (5 ed., vol. 70, pp. 2702-2714).
https://doi.org/10.1287/opre.2022.2325. - Chen, Y.; Feinstein, Z. (2022). Set-valued dynamic risk measures for processes and vectors. Finance and Stochastics (vol. 26, pp. 505-533).
- Banerjee, T.; Feinstein, Z. (2022). Pricing of debt and equity in a financial network with comonotonic endowments. Operations Research (4 ed., vol. 70, pp. 2085-2100).
https://pubsonline.informs.org/doi/10.1287/opre.2022.2275. - 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. - 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. - Feinstein, Z.; Sojmark, A. (2021). Dynamic default contagion in heterogeneous interbank systems. SIAM Journal on Financial Mathematics (4 ed., vol. 12, pp. SC83-SC97).
https://epubs.siam.org/doi/abs/10.1137/20M1376765. - Feinstein, Z.; Rudloff, B.; Zhang, J. (2021). Dynamic set values for nonzero sum games with multiple equilibriums. Mathematics of Operations Research (1 ed., vol. 47, pp. 616-642).
- Ararat, C.; Feinstein, Z. (2020). Set-valued risk measures as backward stochastic difference inclusions and equations. Finance and Stochastics (vol. 25, pp. 43–76).
- Clark, B.; Feinstein, Z.; Simaan, M. (2020). A machine learning efficient frontier. Operations Research Letters (5 ed., vol. 48, pp. 630-634).
- 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. - 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. - 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. - 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).
- 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. - 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. - 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
QF 301 Advanced Time Series Analytics and Machine Learning
FA 542 Time Series with Applications to Finance
FA 590 Statistical Learning in Finance
FE 620 Pricing and Hedging
FA 690 Machine Learning in Finance
FA 691 Deep Learning for Finance
FA 692 Natural Language Processing for Financial Applications
BIA 610 Applied Analytics
FA 542 Time Series with Applications to Finance
FA 590 Statistical Learning in Finance
FE 620 Pricing and Hedging
FA 690 Machine Learning in Finance
FA 691 Deep Learning for Finance
FA 692 Natural Language Processing for Financial Applications
BIA 610 Applied Analytics