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151 - 160 of 204 results for: MS

MS&E 348: Optimization of Uncertainty and Applications in Finance

How to make optimal decisions in the presence of uncertainty, solution techniques for large-scale systems resulting from decision problems under uncertainty, and applications in finance. Decision trees, utility, two-stage and multi-stage decision problems, approaches to stochastic programming, model formulation; large-scale systems, Benders and Dantzig-Wolfe decomposition, Monte Carlo sampling and variance reduction techniques, risk management, portfolio optimization, asset-liability management, mortgage finance. Projects involving the practical application of optimization under uncertainty to financial planning.
Last offered: Winter 2020

MS&E 349: Financial Statistics

Topics in financial statistics with focus on current research: Time-series modeling, volatility modeling, high-frequency statistics, large-dimensional factor modeling and estimation of continuous-time processes. Prerequisites: 220, 226 or STATS 200, 221 or STATS 217, 245A, or equivalents.
Terms: Win | Units: 3

MS&E 350: Fundamental and Current Topics in Engineering Risk Analysis

Limited to doctoral students and advanced master students. Literature in the fields of engineering risk assessment and management. New methods and topics, emphasizing probabilistic methods and decision analysis. Applications to risk management problems involving the technical, economic, and organizational aspects of engineering system safety. Possible topics: treatment of uncertainties, learning from near misses, and use of expert opinions.
Last offered: Spring 2020 | Repeatable for credit

MS&E 351: Dynamic Programming and Stochastic Control

Markov population decision chains in discrete and continuous time. Risk posture. Present value and Cesaro overtaking optimality. Optimal stopping. Successive approximation, policy improvement, and linear programming methods. Team decisions and stochastic programs; quadratic costs and certainty equivalents. Maximum principle. Controlled diffusions. Examples from inventory, overbooking, options, investment, queues, reliability, quality, capacity, transportation. MATLAB. Prerequisites: MATH 113, 115; Markov chains; linear programming.
Last offered: Winter 2019

MS&E 352: Decision Analysis II: Professional Decision Analysis

How to organize the decision conversation, the role of the decision analysis cycle and the model sequence, assessing the quality of decisions, framing decisions, the decision hierarchy, strategy tables for alternative development, creating spare and effective decision diagrams, biases in assessment, knowledge maps, uncertainty about probability. Sensitivity analysis, approximations, value of revelation, joint information, options, flexibility, bidding, assessing and using corporate risk attitude, risk sharing and scaling, and decisions involving health and safety. See 353 for continuation. Prerequisite: 252.
Last offered: Winter 2018

MS&E 353: Decision Analysis III: Frontiers of Decision Analysis

The concept of decision composite; probabilistic insurance and other challenges to the normative approach; the relationship of decision analysis to classical inference and data analysis procedures; the likelihood and exchangeability principles; inference, decision, and experimentation using conjugate distributions; developing a risk attitude based on general properties; alternative decision aiding practices such as analytic hierarchy and fuzzy approaches. Student presentations on current research. Goal is to prepare doctoral students for research. Prerequisite: 352.
Last offered: Spring 2018

MS&E 355: Influence Diagrams and Probabilistics Networks

Network representations for reasoning under uncertainty: influence diagrams, belief networks, and Markov networks. Structuring and assessment of decision problems under uncertainty. Learning from evidence. Conditional independence and requisite information. Node reductions. Belief propagation and revision. Simulation. Linear-quadratic-Gaussian decision models and Kalman filters. Dynamic processes. Bayesian meta-analysis. Prerequisites: 220, 252, or equivalents, or consent of instructor.
Last offered: Winter 2020

MS&E 365: Mechanism and Market Design (ECON 287)

Primarily for doctoral students. Focus on quantitative models dealing with sustainability and related to operations management. Prerequisite: consent of instructor. May be repeated for credit.
Terms: Win | Units: 3 | Repeatable for credit
Instructors: Ashlagi, I. (PI)

MS&E 366: Market Design and Resource Allocation in Non-Profit Settings

Survey of recent research on market design and resource allocation with a focus on under-explored domains in non-profit settings. Will start with classic results in allocation, matching and social choice, and discuss them in the context of relevant objectives such as social welfare and equity. Will then draw on techniques from operations research and economics to explore the design of resource allocation platforms in emerging applications including housing, humanitarian logistics, volunteer coordination, food allocation, conservation and sustainability, and informal markets in the developing world. Prerequisite: consent of instructor; background material will be covered throughout the course as necessary. May be repeated for credit.
Terms: Aut | Units: 3 | Repeatable 7 times (up to 21 units total)
Instructors: Lo, I. (PI)

MS&E 370: Current Topics in Strategy, Innovation and Entrepreneurship

This course will cover focused exploration of contemporary readings and classics as relevant in strategy, innovation and entrepreneurship such as platforms, ecosystems, institutional logics, and strategic "games" in nascent markets. The course will include both content and methods discussions, including theory-building from multiple cases. PhD students only. Prerequisite: Consent of instructor.
Terms: Aut, Win, Spr | Units: 1 | Repeatable 21 times (up to 21 units total)
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