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51 - 60 of 155 results for: MS&E

MS&E 237: Networks, Markets, and Crowds (CME 237)

The course explores the underlying network structure of our social, economic, and technological worlds and uses techniques from graph theory and economics to examine the structure & evolution of information networks, social contagion, the spread of social power and popularity, and information cascades. Prerequisites: basic graph and probability theory.
Terms: not given this year | Units: 3 | Grading: Letter or Credit/No Credit

MS&E 238: Leading Trends in Information Technology

Focuses on new trends and disruptive technologies in IT. Emphasis on the way technologies create a competitive edge and generate business value. Broad range of views presented by guest speakers, including top level executives of technology companies, and IT executives (e.g. CIOs) of Fortune 1000 companies. Special emphasis in technologies such as Cloud Computing, Artificial Intelligence, Security, Mobility, and Big Data.
Terms: Sum | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: Barreto, D. (PI)

MS&E 238A: Leading Trends in Information Technology

Focuses on new trends and disruptive technologies in IT. Emphasis on the way technologies create a competitive edge and generate business value. Broad range of views presented by guest speakers, including top level executives of technology companies, and IT executives (e.g. CIOs) of Fortune 1000 companies. Special emphasis in technologies such as Cloud Computing, Artificial Intelligence, Security, Mobility, and Big Data.
Terms: Sum | Units: 1 | Grading: Satisfactory/No Credit
Instructors: Barreto, D. (PI)

MS&E 240: Accounting for Managers and Entrepreneurs (MS&E 140)

Non-majors and minors who have taken or are taking elementary accounting should not enroll. Introduction to accounting concepts and the operating characteristics of accounting systems. The principles of financial and cost accounting, design of accounting systems, techniques of analysis, and cost control. Interpretation and use of accounting information for decision making. Designed for the user of accounting information and not as an introduction to a professional accounting career. Enrollment limited. Admission by order of enrollment.
Terms: Win, Sum | Units: 3-4 | Grading: Letter or Credit/No Credit
Instructors: Stanton, F. (PI)

MS&E 241: Economic Analysis

Principal methods of economic analysis of the production activities of firms, including production technologies, cost and profit, and perfect and imperfect competition; individual choice, including preferences and demand; and the market-based system, including price formation, efficiency, and welfare. Practical applications of the methods presented. Recommended: 211, ECON 50.
Terms: Win | Units: 3-4 | Grading: Letter or Credit/No Credit
Instructors: Sweeney, J. (PI)

MS&E 243: Energy and Environmental Policy Analysis

Concepts, methods, and applications. Energy/environmental policy issues such as automobile fuel economy regulation, global climate change, research and development policy, and environmental benefit assessment. Group project. Prerequisite: MS&E 241 or ECON 50, 51.
Terms: Spr | Units: 3 | Grading: Letter or Credit/No Credit

MS&E 244: Economic Growth and Development

Formerly 249. What generates economic growth. Emphasis is on theory accompanied by intuition, illustrated with country cases. Topics: the equation of motion of an economy; optimal growth theory; calculus of variations and optimal control approaches; deriving the Euler and Pontriaguine equations from economic reasoning. Applications: former planned economies in Russia and E. Europe; the present global crisis: causes and consequences; a comparative study of India and China. The links between economic growth and civilization; the causes of the rise and decline of civilizations; lessons for the future. Intended for graduate students. Prerequisite: multivariate calculus and permission of instructor. To receive permission, submit an application at http://web.stanford.edu/~lcottle/forms/244app.fb
Terms: Sum | Units: 3 | Grading: Letter or Credit/No Credit

MS&E 245A: Investment Science

Basic concepts of modern quantitative finance and investments. Focus is on the financial theory and empirical evidence that are useful for investment decisions. Topics: basic interest rates; evaluating investments: present value and internal rate of return; fixed-income markets: bonds, yield, duration, portfolio immunization; term structure of interest rats; measuring risk: volatility and value at risk; designing optimal portfolios; risk-return tradeoff: capital asset pricing model and extensions. No prior knowledge of finance is required. Concepts are applied in a stock market simulation with real data. Prerequisite: basic preparation in probability, statistics, and optimization.
Terms: Aut | Units: 3-4 | Grading: Letter or Credit/No Credit
Instructors: Pelger, M. (PI)

MS&E 245B: Advanced Investment Science

Formerly MS&E 342. Topics: forwards and futures contracts, continuous and discrete time models of stock price behavior, geometric Brownian motion, Ito's lemma, basic options theory, Black-Scholes equation, advanced options techniques, models and applications of stochastic interest rate processes, and optimal portfolio growth. Computational issues and general theory. Teams work on independent projects. Prerequisite: 245A.
Terms: Win | Units: 3 | Grading: Letter or Credit/No Credit

MS&E 246: Financial Risk Analytics

Practical introduction to financial risk analytics. The focus is on data-driven modeling, computation, and statistical estimation of credit and market risks. Case studies based on real data will be emphasized throughout the course. Topics include mortgage risk, asset-backed securities, commercial lending, consumer delinquencies, online lending, derivatives risk. Tools from machine learning and statistics will be developed. Data sources will be discussed. The course is intended to enable students to design and implement risk analytics tools in practice. Prerequisites: MS&E 245A or similar, some background in probability and statistics, working knowledge of R, Matlab, or similar computational/statistical package.
Terms: Win | Units: 3 | Grading: Letter (ABCD/NP)
Instructors: Giesecke, K. (PI)
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