Letter From the Chair
The Quantitative Advantage
The Decision, Risk, and Operations Division is a world leader in research and instruction in quantitative, data-driven decision-making through the use modeling, optimization and the management of uncertainty, and all aspects of the operations and analytics functions in firms.
Application areas in which the division has strong expertise include business analytics; e-commerce; revenue management; logistics, distribution and supply-chain management; resource networks and service systems; healthcare operations; market design; quantitative finance with emphasis on the valuation of derivative securities, modern market microstructure, and risk management; and econometrics.
An important aspect of the mission of the division is to foster collaboration with industry and impact society by solving important practical problems such as helping hospitals care for their patients in a more efficient and cost effective manner; coordination and risk mitigation in global supply chains; design of dynamic and responsive pricing algorithms in a variety of industries; creation of innovative securities trading algorithms; design of frameworks to measure systemic risk; and optimization of the operations of online marketplaces.
The division is actively involved in teaching in the MBA and PhD programs. In the MBA program, the division teaches the core courses on Managerial Statistics, Business Analytics, and Operations Management, and offers a suite of electives in various topics in Operations, Analytics, and Technology.
Awi Federgruen
Charles E. Exley Professor of Management;
Chair of Decision, Risk, and Operations Division
Affiliated Departments and Research Centers
The Computational Optimization Research Center
carries out advanced studies in the solution of difficult, large-scale optimization problems, with special focus on state-of-the-art implementation of modern algorithms.
Center for Applied Probability
provides an umbrella under which diverse research and educational activities in probability and its applications can be focused and supported.
Industrial Engineering and Operations Research
is the home to Financial Engineering, a multidisciplinary field that requests familiarity with financial theory, the methods of engineering, the tools of mathematics and the practice of programming.
The Center for Financial Engineering
is part of an interdisciplinary field of research where contributions from applied mathematics, economics, operations research, statistics and computer science have given birth to remarkable developments in market practice.
In the Media
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Decisions Over Decimals: Striking the Balance Between Intuition and Information
Research
The Macroeconomics of Stakeholder Equilibria*
We propose one route to a more inclusive society. Our context is the prevailing one of high wealth inequality where stockholders alone supply the stochastic discount factor governing the allocation of capital. A large and pervasive pecuniary externality is thus imposed on non-stockholder workers, something we view as antithetical to the notion of an inclusive society.
Presenting balanced geoengineering information has little effect on mitigation engagement
‘Moral hazard’ links geoengineering to mitigation via the fear that either solar geoengineering (solar radiation management, SRM) or carbon dioxide removal (CDR) might crowd out the desire to cut emissions. Fear of this crowding-out effect ranks among the most frequently cited risks of (solar) geoengineering. We here test moral hazard versus its inverse in a large-scale, revealed-preference experiment (n~340,000) on Facebook and find little to no support for either outcome. For the most part, talking about SRM or CDR does not motivate our study population to support a large U.S.
A Q Theory of Internal Capital Markets
We propose a tractable model of dynamic investment, spinoffs, financing, and risk management for a multi-division firm facing costly external finance. Our analysis formalizes
Dynamic Trading with Realization Utility
An investor receives utility bursts from realizing gains and losses at the individual-stock level (Barberis and Xiong, 2009, 2012; Ingersoll and Jin, 2013) and dynamically allocates his mental budget between risky and risk-free assets at the trading-account level. Using savings, he reduces his stockholdings and is more willing to realize losses. Using leverage, he increases his stockholdings beyond his mental budget and is more reluctant to realize losses. While leverage strengthens the disposition effect, introducing leverage constraints mitigates it.
Dynamic Banking and the Value of Deposits
We propose a theory of banking in which banks cannot perfectly control deposit flows. Facing uninsurable loan and deposit shocks, banks dynamically manage lending, wholesale funding, deposits, and equity. Deposits create value by lowering funding costs. However, when the bank is undercapitalized and at risk of breaching leverage requirements, the marginal value of deposits can turn negative as deposit inflows, by raising leverage, increase the likelihood of costly equity issuance. Banks’ inability to fully control leverage distinguishes them from non-depository intermediaries.
