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This archived information is dated to the 2011-12 academic year only and may no longer be current.
For currently applicable policies and information, see the current Stanford Bulletin.
This archived information is dated to the 2011-12 academic year only and may no longer be current.
For currently applicable policies and information, see the current Stanford Bulletin.
AdmissionTo be eligible for admission, students are expected to have excelled in the following courses or their equivalent:
Some of these courses (e.g. STATS 116) are usually offered during the Summer Quarter so candidates lacking the required background may take them then.
Candidates for admission must take the general Graduate Record Examination and may take the subject test in Mathematics as well. Information about these exams can be found at http://www.gre.org.
RequirementsThe program requires completion of 45 units of course work. Ordinarily, four quarters are needed to complete all requirements. Students who do not complete all requirements within three years of admission are terminated from the program.
Of these 45 units, six courses must be taken from the list of required courses and six must be taken from the list of elective courses, available below and on the program web site at http://finmath.stanford.edu/academics/required.html and http://finmath.stanford.edu/academics/electives.html. These courses must be taken for letter grades, but students may elect to take one of the 12 courses CR/NC. An overall grade point average (GPA) of 2.75 is required. There is no thesis requirement.
Any remaining units required to complete the 45 total must be taken from the following options, and may be taken for letter grades or CR/NC:
Required CoursesIn partial fulfillment of the M.S. degree in Financial Mathematics, students must fulfill six required courses, with two from each of the following three core areas:
The selection of these courses is to be done in consultation with the Program Director. The following courses can be counted toward the six required courses:
Mathematics:
MATH 227. Partial Differential Equations and Diffusion Processes
MATH 236. Introduction to Stochastic Differential Equations
MATH 238. Mathematical Finance (same as STATS 250)
MATH 239. Computation and Simulation in Finance
Statistics:
STATS 240. Statistical Methods in Finance
STATS 241. Financial Modeling Methodology and Applications
STATS 242. Algorithmic Trading and Quantitative Strategies
STATS 243. Statistical Methods and Models for Risk Management and Surveillance
STATS 315B. Modern Applied Statistics: Data Mining
STATS 362. Monte Carlo
Management Science & Engineering:
MS&E 347. Credit Risk: Modeling and Management
Graduate School of Business:
FINANCE 622. Dynamic Asset Pricing Theory
At the Program Director's discretion, courses taken previously that are equivalent to the above may be waived; in which case they must be replaced by elective courses in the same subject area.
Elective CoursesEach candidate must take at least six approved elective courses from the list below, with two from each of the three core areas:
Other elective courses may be authorized by the Program Director if they provide skills relevant to financial mathematics and do not overlap with courses in the candidate's program.
Mathematics:
MATH 136. Stochastic Processes (same as STATS 219)
MATH 180. Introduction to Financial Mathematics
MATH 205A/B. Real Analysis
MATH 220. PDE of Applied Mathematics
MATH 222A. Computational Methods for Fronts, Interfaces, and Waves
MATH 227. Partial Differential Equations and Diffusion Processes
MATH 237. Stochastic Equations and Random Media
MATH 256A/B. Partial Differential Equations
MATH 261A/B. Functional Analysis
MATH 266. Time Frequency Analysis and Wavelets
Statistics:
STATS 202. Data Mining and Analysis
STATS 206. Applied Multivariate Analysis
STATS 207. Introduction to Time Series Analysis
STATS 212. Applied Statistics with SAS
STATS 219. Stochastic Processes (same as MATH 136)
STATS 220. Continuous Time Stochastic Control
STATS 227. Statistical Computing
STATS 235. Decision Making in Financial Services
STATS 237. Time Series Modeling and Forecasting
STATS 252. Data Mining and Electronic Business
STATS 254. Correspondence Analysis and Related Methods (one time offering Aut 08-09)
STATS 305. Introduction to Statistical Modeling
STATS 306A. Methods for Applied Statistics
STATS 310A/B/C. Theory of Probability
STATS 315A/B/C. Modern Applied Statistics
STATS 317. Stochastic Processes
STATS 318. Modern Markov Chains
STATS 322. Function Estimation in White Noise
STATS 324. Multivariate and Random Matrix Theory
STATS 343. Time Series Analysis
STATS 376A. Information Theory
Computer Science:
CS 106B. Programming Abstractions
CS 106X. Programming Abstractions (Accelerated)
CS 193D. C++
CS 224M. Multi-Agent Systems
CS 295. Software Engineering
CS 229. Machine Learning
CS 249A. Object-Oriented Programming: A Modeling and Simulation Perspective
CS 261. Optimization and Algorithmic Paradigms
CS 339. Topics in Numerical Analysis
CS 365. Randomized Algorithms
Economics:
ECON 190. Introduction to Financial Accounting
ECON 202N-203N. Core Economics: Modules 1 and 2, 5 and 6 - For Non-Economics Ph.D. Students
ECON 210. Core Economics: Modules 3 and 7
ECON 211. Core Economics: Modules 11 and 12
ECON 269. International Financial Markets and Monetary Institutions
ECON 275. Time Series Econometrics
ECON 281. Economics of Uncertainty
ECON 284. Topics in Dynamic Economics
Management Science & Engineering:
MS&E 242H. Investment Science Honors
MS&E 247G. International Financial Management (same as GSB F323)*
MS&G 247S. International Investments
MS&G 272. Entrepreneurial Finance
MS&E 310 . Linear Programming
MS&E 311. Optimization
MS&E 312. Advanced Methods in Numerical Optimization
MS&E 313. Vector Space Optimization
MS&E 322. Stochastic Calculus and Control
MS&E 323. Stochastic Simulation
MS&E 339. Approximate Dynamic Programming
MS&E 341. Advanced Economic Analysis
MS&E 342. Advanced Investment Science
MS&E 345. Advanced Topics in Financial Engineering
MS&E 348. Optimization of Uncertainty and Applications in Finance
MS&E 349. Capital Deployment
MS&E 351. Dynamic Programming and Stochastic Control
MS&E 444. Investment Practice
MS&E445. Projects in Wealth Management
Computational & Mathematical Engineering:
CME 340. Computational Methods in Data Mining
Graduate School of Business (GSB), Finance:
FINANCE 320*. Debt Markets
FINANCE 326*. Derivative Securities
FINANCE 328* Portfolio Management
FINANCE 620*. Financial Markets I
FINANCE 621*. Financial Markets II
FINANCE 622*. Dynamic Asset Pricing Theory
FINANCE 629*. Tax and Finance Seminar
Graduate School of Business (GSB), Economic Analysis and Policy:
MGTECON 600. Microeconomic Analysis I*
MGTECON 604. Econometric Methods II*
MGTECON 609. Applied Econometric and Economics Research*
Graduate School of Business (GSB), Operations, Information, and Technology:
OIT 667. Revenue Management*
*Indicates courses of limited enrollment and/or that instructor consent is required for registration.
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