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151 - 160 of 168 results for: MS&E

MS&E 446A: Mathematical and Computational Finance Seminar (CME 242, STATS 239)

Terms: Aut, Spr | Units: 1 | Repeatable for credit | Grading: Satisfactory/No Credit
Instructors: Jain, K. (PI)

MS&E 447: Systemic and Market Risk : Notes on Recent History, Practice, and Policy

The global financial crisis of 2007-8 threw into sharp relief the ongoing challenges of understanding risk, the financial system, links with the global economy, and interactions with policy. We will explore elements of the crisis, a few other key events, and ongoing debates about systemic risk. Group projects will explore in more detail past events and current topics in systemic risk. Supplements a rigorous technical curriculum in modern finance with select aspects relevant to understanding the practice and broader context of modern financial activities such as derivatives, financial engineering, and risk management.
Terms: not given this year | Units: 3 | Grading: Letter (ABCD/NP)

MS&E 448: Big Financial Data and Algorithmic Trading

Project course emphasizing the connection between data, models, and reality. Vast amounts of high volume, high frequency observations of financial quotes, orders and transactions are now available, and poses a unique set of challenges. This type of data will be used as the empirical basis for modeling and testing various ideas within the umbrella of algorithmic trading and quantitative modeling related to the dynamics and micro-structure of financial markets. Due to the fact that it is near impossible to perform experiments in finance, there is a need for empirical inference and intuition, any model should also be justified in terms of plausibility that goes beyond pure econometric and data mining approaches. Introductory lectures, followed by real-world type projects to get a hands-on experience with realistic challenges and hone skills needed in the work place. Work in groups on selected projects that will entail obtaining and cleaning the raw data and becoming familiar with techniqu more »
Project course emphasizing the connection between data, models, and reality. Vast amounts of high volume, high frequency observations of financial quotes, orders and transactions are now available, and poses a unique set of challenges. This type of data will be used as the empirical basis for modeling and testing various ideas within the umbrella of algorithmic trading and quantitative modeling related to the dynamics and micro-structure of financial markets. Due to the fact that it is near impossible to perform experiments in finance, there is a need for empirical inference and intuition, any model should also be justified in terms of plausibility that goes beyond pure econometric and data mining approaches. Introductory lectures, followed by real-world type projects to get a hands-on experience with realistic challenges and hone skills needed in the work place. Work in groups on selected projects that will entail obtaining and cleaning the raw data and becoming familiar with techniques and challenges in handling big data sets. Develop a framework for modeling and testing (in computer languages such as Python, C++ , Matlab and R) and prepare presentations to present to the class. Example projects include optimal order execution, developing a market making algorithm, design of an intra-day trading strategy, and modeling the dynamics of the bid and ask. Prerequisites: MS&E 211, 242, 342, or equivalents, some exposure to statistics and programming. Enrollment limited. Admission by application; details at first class.
Terms: Spr | Units: 3 | Grading: Letter (ABCD/NP)

MS&E 449: Buy-Side Investing

In-class lectures and guest speakers who work in the Buy-Side to explore the synergies amongst the various players¿ roles, risk appetites, and investment time and return horizons. We aim to see the forest and the different species of trees growing in the forest known as the Buy-Side, so as to develop a perspective as financial engineers for how the ecosystem functions, what risks it digests, how it generates capital at what rate and amount for the Sell-Side, and how impacts in the real economy are reflected - or should be reflected - in the culture and risk models adopted by the Buy-Side participants.
Terms: Win | Units: 1-2 | Grading: Satisfactory/No Credit

MS&E 450: Lessons in Decision Making

Entrepreneurs, senior management consultants, and executives from Fortune 500 companies share real-world stories and insights from their experience in decision making.
Terms: not given this year | Units: 1 | Repeatable for credit | Grading: Satisfactory/No Credit

MS&E 453: Decision Analysis Applications

How to be effective and efficient when making important personal choices as well as organizational decisions about business strategies and public policies. Applications show the use of decision analysis techniques to frame, structure, assess, evaluate, analyze, and appraise complex decisions implemented in an uncertain future world. Experienced decision professionals lead discussions of case studies about venture capital, biotech acquisition, commodity options trading, R&D portfolios, tech manufacturing strategy, litigation risk, medical diagnosis, health care delivery, pharmaceutical drug development, real estate development, energy economics, and environmental risk analysis. Discussions include lessons learned about useful processes for effective interactions, clear communications, organizational renewal, decision quality, and collaborative decision making. Prerequisite: MS&E 152 or MS&E 252.
Terms: Spr | Units: 2 | Grading: Letter or Credit/No Credit
Instructors: Robinson, B. (PI)

MS&E 454: Decision Analysis Seminar

Current research and related topics presented by doctoral students and invited speakers. May be repeated for credit. Prerequisite: 252.
Terms: Aut, Win, Spr | Units: 1 | Repeatable for credit | Grading: Satisfactory/No Credit
Instructors: Howard, R. (PI)

MS&E 463: Healthcare Systems Design

Students work on projects to analyze and design various aspects of healthcare including hospital patient flow, physician networks, clinical outcomes, reimbursement incentives, and community health. Students work in small teams under the supervision of the course instructor and partners at the Lucille Packard Children's Hospital, the Stanford Hospital, and other regional healthcare providers. Prerequisite: 263.
Terms: Spr | Units: 3-4 | Grading: Letter (ABCD/NP)

MS&E 472: Entrepreneurial Thought Leaders' Seminar

Entrepreneurial leaders share lessons from real-world experiences across entrepreneurial settings. ETL speakers include entrepreneurs, leaders from global technology companies, venture capitalists, and best-selling authors. Half-hour talks followed by half hour of class interaction. Required web discussion. May be repeated for credit.
Terms: Aut, Win, Spr | Units: 1 | Repeatable for credit | Grading: Satisfactory/No Credit

MS&E 475A: Entrepreneurial Leadership

This seminar explores a wide range of topics related to entrepreneurial leadership through class discussions, case studies, field trips, and guest speakers. It is part of the DFJ Entrepreneurial Leaders Fellowship, which requires an application during Fall quarter. Details can be found at: http://stvp.stanford.edu/dfj/.
Terms: Win | Units: 1 | Grading: Satisfactory/No Credit
Instructors: Seelig, T. (PI)
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