量化金融和风险管理专业排名暂无排名 ，US News 2018
As an interdisciplinary program, we draw upon the strengths of students from many different academic backgrounds. Competitive applicants will possess exceptional quantitative skills in fields such as mathematics, statistics, physics, engineering, and economics. Majors in related areas that provide background in probability and statistics at the level of Math/Statistics 425 (Introduction to Probability) are also acceptable. Students admitted will have a strong background in calculus, linear algebra, probability, and programming (Matlab and/or C/C++).
1.Statement of Purpose
The Statement of Purpose should be a concise, well-written essay about your mathematical background, your career goals, and how the Quantitative Finance and Risk Management program will help you meet your career and educational objectives.
This is different from the Statement of Purpose in that we ask that you write about things not captured by the application or the Statement of Purpose. Tell us about where you grew up, when you first decided you wanted to study mathematics, what challenges you faced and how you overcame them in your pursuit of mathematics.
3.Curriculum Vitae/Resume (4 page limit)
Upload your curriculum vitae or resume that describes your education, work experience, research and teaching experience, professional affiliations, volunteer activity and community engagement, honors and awards.
4.Three letters of recommendation
Register your recommenders for the electronic Letters of Recommendation system in the online application. This is the preferred method of submission. If your recommender would prefer a paper copy of the Recommendation form (PDF format), it may be downloaded here.
5.Official GRE General scores
Request ETS to send official scores directly to the Rackham Graduate School at the University of Michigan.
The ETS school code for the University of Michigan Rackham Graduate School is 1839.
NOTE: the Mathematics Subject GRE is very useful for the admissions committee so it is highly recommended, but it is not required for this program.
6.Official Transcripts from all post secondary institutions are submitted to the University of Michigan Rackham Graduate School.
Send one copy of all official transcripts to the Rackham Graduate School at the University of Michigan. Directions on what qualifies as an official transcript and how to submit official transcripts can be found here. **Applications without official transcripts are considered incomplete and will not be reviewed.**
7.Non-native English speakers have additional requirements
Official TOEFL or IELTS Scores are required for non-native English speakers. This requirement may be waived for some applicants depending on their educational background. Visit the Rackham School of Graduate Studies for more information on their TOEFL Requirement to determine whether you qualify for a waiver.
Minimum Requirements: TOEFL overall score must be 95 or higher. IELTS overall score must be 7 or higher. Applicants who do not meet the minimum requirements will not be considered. Applicants may submit multiple scores, but at least one score that meets the minimum must be received by the designated deadline in order for an applicant to be considered.
Request ETS to send an official copy to the University of Michigan Rackham Graduate School.
The Department of Mathematics and the Department of Statistics jointly oversee an interdisciplinary Master of Science degree program in Quantitative Finance and Risk Management.
The program focuses intensely on advanced mathematical and statistical methods. Graduates will have sophisticated quantitative skills that will prepare them to apply their knowledge to the solution of real world financial problems as quantitative analysts, risk managers, traders, developers, and other roles in the financial industry.
Advanced Financial Mathematics I and II
Discrete State Stochastic Processes and Stochastic Analysis for Finance
Numerical Analysis with Financial Applications and Computational Finance
Applied Statistics I and Statistical Analysis of Financial Data
Mathematical Methods of Algorithmic Trading
Continuous Optimization Methods
Applied Multivariate Analysis
Analysis of Time Series
Introduction to Artificial Intelligence
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