Finance
The Master of Science in Finance program at the Segal Graduate School equips students with the tools needed to manage investments and risk in a rapidly changing world. Designed to meet the increasing global demand for skilled risk management and investment management professionals, the program provides a unique blend of rigorous training and real-world experience. Visiting finance professionals contribute an invaluable practical component to the program. Students also have an unparalleled opportunity to gain hands-on experience by managing an investment portfolio with a market value in excess of $10 million.
Applicants should also refer to the program website .
丁香园AV Requirements
丁香园AV is based on the following:
- Students can apply online at 丁香园AV’s online Graduate Studies application for admission, found at http://www.sfu.ca/dean-radstudies/prosp_students/application_process/
- MSc in Finance program application essay, found at .
- Official undergraduate transcripts mailed directly from the granting institution. An undergraduate degree in business, commerce, economics, mathematics, physics or other suitable quantitatively oriented programs is required. Candidates holding a professional designation such as a PRM or FRM and evidence of strong mathematics competency would also be ideal candidates. Students with a strong mathematical aptitude who have completed the graduate diploma in business administration offered by the University would be qualified for admission consideration
- A resume
- Three confidential letters of reference mailed directly from the referees, preferably from supervisors or former professors
- Graduate management admission test (GMAT) results
- Applicants whose primary language is not English, or whose previous education was conducted in another language, must submit evidence of satisfactory completion of a standardized English test that is acceptable to the University (see )
- Interview (shortlisted candidates only)
Application
Students can apply online at 丁香园AV's online graduate studies application for admission, found at http://www.sfu.ca/dean-gradstudies/prosp-students/application_process.
Program Requirements
A minimum 3.0 grade point average (B grade) is required and completion of a minimum of 45 units from the following course list including BUS 870.
An introduction to elements of mathematics and computational techniques employed in finance and financial risk management. An introduction to programming tools, e.g. VBA, Matlab, and an object oriented programming language (e.g. C++).
An introductory course in the theory of finance and investor behavior, financial decision-making under uncertainty as well as capital market equilibrium.
A survey of asset pricing models including linear factor models, CAPM, and arbitrage models. Multi-period consumption, portfolio choice, and asset pricing models; continuous-time consumption and portfolio choice; behavioral finance and asset pricing; asset pricing with differential information.
An introduction to portfolio management, equity valuation, debt valuation, and performance and risk measurement.
The term structure of interest rates, fixed income returns, yield-spread analysis, sources of risk in fixed income securities, and embedded options.
An introductory course in derivative securities that includes pricing as well as the use of derivative securities in portfolio management and structured transactions.
Assumptions underlying the Capital Asset Pricing Model are relaxed to allow for specific views on asset returns, and to allow for the expected future consumption needs of a given investor to be considered at a strategic level.
The valuation of equity securities, including company and industry analysis, financial statement analysis and valuation models.
A review of securities law in Canada, US and the EU. Overview of how, and by whom, financial intermediaries are regulated, Canada: Bank Act, Bank of Canada, OSFI. US: Federal Reserve, SEC, OCC, FDIC, etc.
Provides an understanding of the linkages between financial statements such as annual reports and prospectuses including the three principal financial statements (balance sheet, income statement and cash flow statement) and how useful information about a company can be extracted from them.
Four main topics are covered: portfolio theory, asset pricing, market efficiency, and performance measurement. The first two are cornerstones of financial economics, as, for the most part, portfolio selection models form the basis of models of asset pricing. The third cornerstone is the efficient markets hypothesis, which asks whether prices reflect information. Finally, asset pricing models provide the basis for many risk-adjusted measures of the performance of mutual, pension, and hedge funds.
| Section | Instructor | Day/Time | Location |
|---|---|---|---|
| TBD |
Credit risk management with emphasis on portfolio models, including probability of default and loss given default models, credit capital allocation, active portfolio management, credit derivatives, and structured transactions.
An assessment of the risk management practices of financial institutions. A survey of best practices with respect to enterprise risk management, including risk architecture and risk communication and disclosure within the organization.
Provides a comprehensive definition of all types of financial instruments and develops a thorough understanding of operational accounting and auditing for a broad range of financial instruments.
A risk management research project, completed within the final academic term, based on ideas generated in previous terms, with in-class sessions on topic development, presentation, and reporting of findings as well as regular meetings with a designated supervisor. Project may be done individually or in pairs.
| Section | Instructor | Day/Time | Location |
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| TBD | |||
| TBD |
Comparative systems of accounting. Evolution of multinational business and accounting implications. Prerequisite: BUS 871 and 346, or permission of the instructor.
Other graduate courses may be substituted for the courses listed above at the discretion of the academic director.
Graduate Diploma in Financial Engineering
The Graduate Diploma in Financial Engineering is designed for graduate students in the Department of Statistics and Actuarial Science who would like to develop applied skills in the field of finance, and for students in the M.Sc. Finance program seeking to deepen their theoretical understanding of relevant statistical and mathematical concepts so as to prepare students for careers in quantitative finance.
Students must complete a total of 22 units of graduate coursework, including:
An introductory course in derivative securities that includes pricing as well as the use of derivative securities in portfolio management and structured transactions.
Minimally one (1) ofthe following courses:
An introduction to stochastic models for the rate of return. Time series. Stochastic differential equations. Covariance equivalence principle. Applications. Prerequisite: Permission of the Department. Students with credit for ACMA 820 may not take this course for further credit.
Life insurance models. Interest rate models for life insurance: time series, stochastic differential equations, estimation. Portfolios of identical policies. Diversified portfolios. Prerequisite: ACMA 320.
Minimally two (2) ofthe following courses:
Study the distribution of aggregate claims and introduce stochastic claims reserving methods in insurance. Individual versus collective models. Standard distribution-free methods. Other models. Prerequisite: Permission of the Department. Students with credit for ACMA 821 may not take this course for further credit.
The statistical theory that supports modern statistical methodologies. Distribution theory, methods for construction of tests, estimators, and confidence intervals with special attention to likelihood and Bayesian methods. Properties of the procedures including large sample theory will be considered. Consistency and asymptotic normality for maximum likelihood and related methods (e.g., estimating equations, quasi-likelihood), as well as hypothesis testing and p-values. Additional topics may include: nonparametric models, the bootstrap, causal inference, and simulation. Prerequisite: STAT 450 or permission of the instructor. Students with credit for STAT 801 may not take this course for further credit.
Advanced mathematical statistics for PhD students. Topics in probability theory including densities, expectation and random vectors and matrices are covered. The theory of point estimation including unbiased and Bayesian estimation, conditional distributions, variance bounds and information. The theoretical framework of hypothesis testing is covered. Additional topics that may be covered include modes of convergence, central limit theorems for averages and medians, large sample theory and empirical processes. Prerequisite: STAT 830 or permission from the instructor.
Application of stochastic processes: queues, inventories, counters, etc. Reliability and life testing. Point processes. Simulation. Students with credit for STAT 870 may not take this course for further credit.
An introduction to smoothing and modelling of functional data. Basis expansion methods, functional regression models and derivative estimation are covered. Prerequisite: STAT 830 or permission of the instructor.
An introduction to computational methods in applied statistics. Topics can include: the bootstrap, Markov Chain Monte Carlo, EM algorithm, as well as optimization and matrix decompositions. Statistical applications will include frequentist and Bayesian model estimation, as well as inference for complex models. The theoretical motivation and application of computational methods will be addressed. Prerequisite: STAT 830 or equivalent or permission of instructor.
| Section | Instructor | Day/Time | Location |
|---|---|---|---|
|
Jinko Graham |
Jan 6 鈥� Apr 13, 2015: Wed, 9:30鈥�11:20 a.m.
Jan 6 鈥� Apr 13, 2015: Fri, 10:30 a.m.鈥�12:20 p.m. |
Burnaby Burnaby |
Minimally one (1) of the following courses:
A survey of asset pricing models including linear factor models, CAPM, and arbitrage models. Multi-period consumption, portfolio choice, and asset pricing models; continuous-time consumption and portfolio choice; behavioral finance and asset pricing; asset pricing with differential information.
The term structure of interest rates, fixed income returns, yield-spread analysis, sources of risk in fixed income securities, and embedded options.
Credit risk management with emphasis on portfolio models, including probability of default and loss given default models, credit capital allocation, active portfolio management, credit derivatives, and structured transactions.
and one or more elective courses from the above lists to meet the overall minimum required units.
Students may apply some courses completed for one credential towards this credential as outlined in graduate regulation 1.7.6.Normally this would mean that students must complete minimally four (4) additional courses to be awarded this diploma beyond their MSc.
For those with limited background in finance/economics, preparatory courses offered by the Beedie School of Business may be required.
Optional Prep Courses
M.Sc. Prep Program - Economics Fundamentals (non-credit)
An introductory course in the theory of finance and investor behavior, financial decision-making under uncertainty as well as capital market equilibrium.
* students in the investment management stream complete BUS 826, 816 and 823
** students in the risk management stream complete BUS 864, 865, and 866
Academic Requirements within the Graduate General Regulations
All graduate students must satisfy the academic requirements that are specified in the (residence, course work, academic progress, supervision, research competence requirement, completion time, and degree completion), as well as the specific requirements for the program in which they are enrolled, as shown above.