David Mordecai Taught Financing the Grid University Chicago Booth
David K.A. Mordecai, Adjunct Professor of Econometrics and Statistics at the University of Chicago Booth School of Business, taught Financing the Grid: Valuing Transmission & Storage Capacity course in Spring 2024. His co-faculty were:
- John R. Birge, Hobart W. Williams Distinguished Service Professor of Operations Management
- Kevin M. Murphy, George J. Stigler Distinguished Service Professor of Economics Emeritus
The course provided a general introductory overview to fundamental instruments, and foundational concepts and practice principles from industrial economics, statistics and engineering applicable to financing and valuation of grid-scale electricity storage and transmission capacity.
Throughout the quarter, the course content addressed key principles underlying the engineering and economics of the grid. and introduced fundamental themes from applicable financial derivatives, as well as natural resource and environmental economics, foundational to the application of Cournot models and real options analysis, as well as statistical and econometric specification of spatial models from industrial economics for storage and transmission in the context of binding technical constraints. Beginning with foundational principles for fundamental pricing instruments applicable to electricity generation, consumption, storage and transmission, lecture and discussion addressed corresponding established and prospective industry practice related to spatial organization and colocation of industrial electricity supply and demand with additional implications for environmental and infrastructure regulation and finance, electricity trading and asset pricing (e.g., metals and ancillary commodity derivatives markets). Classroom discourse further extended technical fundamentals and foundational principles to broader implications and impacts for political economy, energy policy and applied management science.
The course concluded with a panel discussion at which the three co-instructors were joined by colleague Mihai Anitescu, University of Chicago Department of Statistics Professor and Senior Computational Mathematician at Argonne National Laboratory.
Dr. Mordecai is Co-Managing Member of Numerati® Partners LLC, which coordinates a data analytics and technology development ecosystem, with the mission of advancing and fostering the next generation of scalable data-intensive risk and liability management enterprises. The firm provides resources fundamental to advancing the development of nascent leading-edge inferential surveillance, monitoring, and predictive analytics technologies for deployment within the RiskTech domain: risk technologies associated with adaptive distributed, networked and embedded systems such as remote sensing, agent-oriented data analytics, computing and control systems. Numerati® Partners curates integrated RiskTech solutions as well as forensic and use-case applications in RiskTech sub-domains such as LitTech, RegTech, FinTech and InsurTech (litigation technology, regulation technology, financial technology and insurance technology).
As an Adjunct Professor of Law at NYU Law School, he also co-teaches the course Quantitative Methods in Litigation with a focus on machine testimony and machine behavior. His contributions to this course as co-instructor include his extensive testifying experience, as well as four decades of industry experience and direct experience with technical review, evaluation, and testing of AI and machine learning applications across diverse institutional contexts, and industry and market settings.
Since 2013, Dr. Mordecai has also served as the first Scientist-in-Residence at FinTech Innovation Lab, an accelerator platform for early and growth stage technology firms, organized by The Partnership Fund for New York City in conjunction with Accenture and a consortium of venture capital firms and global financial institutions.
He earned a Ph.D. with concentrations in Econometrics/Mathematical Statistics and Economics/ Industrial Organization from the University of Chicago, and an M.B.A. in Finance from NYU Stern School of Business. His dissertation research applied principal components analysis to risk-based leverage estimation with a focus upon empirical tests of the limits of arbitrage, and how market shocks trigger contagion via the financing of highly leveraged financial institutions during periods of extreme market volatility. In addition to studying financial economics and market microstructure, as well as the economics of law, regulation and industry structure, his doctoral education included the study of Bayesian decision theory, social network analysis and behavioral economics.
