2018年密歇根大学安娜堡分校QFRM录取两枚

金融工程专业是属于最热门的留学专业之一，总体申请难度很高的专业。全美前100院校中，开设金融工程硕士项目的仅30个左右，其中，超过50%的项目开设在名校中。总体来说，美国金融工程的录取率在10%以下，国际应届毕业生还要面临美国以及有工作经验的申请者的挑战。下面给大家汇报两枚密歇根大学安娜堡分校数量金融与风险管理硕士（QFRM）的录取！

毕达学子：H同学

本科学校与专业：北京师范大学，数学与应用数学

申请背景：GPA 3.0+，TOEFL 100+，GRE 320；2个实习，2个项目

录取：University of Michigan-Ann Arbor，MS in Quantitative Finance and Risk Management

毕达学子：S同学

本科学校与专业：西交利物浦大学，数学与应用数学

申请背景：GPA 2.9，IELTS 7.0，GRE 321；4个实习

录取：University of Michigan-Ann Arbor，MS in Quantitative Finance and Risk Management

UM的数量金融与风险管由数学系、统计系联合开设。培养学生掌握复杂的量化技能，并运用到现实的金融问题。适合职业目标为定量分析师、风险经理、交易员等。

往届学生就业去向：

• Quantitative Analyst, ACSI Funds (Ann Arbor)

• Senior Quantitative Analyst, Capital One (McLean, VA)

• Mergers and Acquisitions Intern, China Merchants Securities

• Senior Analyst, Mergers and Acquisitions, CITIC Securities (Beijing)

• Data Analyst, Discover Shanghai Analytics Center of Excellence (Shanghai)

• Analyst, Global Banking and Markets, HSBC (New York)

• Assistant Analyst, Huatai-PineBridge Investments (Shanghai)

• Quant Intern, ICBC Credit Suisse (Beijing)

• Data Assurance Analyst, Mistubishi UFJ Financial Group (New York)

• Data Scientist, Mint Servicing, Inc. (Washington, D.C.)

• Market Risk Analyst, Huarong Securities

项目属于STEM，为期一年，包括24个学分必修课和12个学分选修课：

必修课：

• Math 573 (3 cr): Advanced Financial Mathematics I.

• Math 574 (3 cr): Advanced Financial Mathematics II.

• Math 526 (3 cr): Discrete State Stochastic Processes.

• Math 506 (3 cr): Stochastic Analysis for Finance.

• Math 472 (3 cr): Numerical Methods with Financial Applications.

• Math 623 (3 cr): Computational Finance.

• Stats 500 (3 cr): Applied Statistics I.

• Stats 509 (3 cr): Statistical Analysis of Financial Data.

选修课：

Math Courses

• MATH 507: Mathematical Methods of Algorithmic Trading (3 cr)

• MATH 561/IOE 510: Linear Programming (3 cr)

• MATH 562/IOE 511: Continuous Optimization Methods (3 cr)

• MATH 663/IOE 611: Nonlinear Programming (3 cr)

Statistics Courses

• STATS 503: Applied Multivariate Analysis (3 cr)

• STATS 531/Econ 677: Analysis of Time Series (3 cr)

• STATS 535/IOE 562: Reliability (3 cr)

Computer Science Courses

• EECS 484: Database Management (4 cr)

• EECS 492: Introduction to Artificial Intelligence (4 cr)

• EECS 545: Machine Learning (3 cr)

• EECS 547: Electronic Commerce (3 cr)

• EECS 597: Language and Information (3 cr)

Economics Courses

• ECON 411: Monetary and Financial Theory (3 cr)

• ECON 441: International Trade Theory (3 cr)

• ECON 442: International Finance (3 cr)

• ECON 501: Microeconomics (3 cr)

• ECON 502: Macroeconomics (3 cr)

Finance Courses

• FIN 608: Capital Markets & Investment Strategies (2.25 cr)

• FIN 609: Fixed Income Securities and Markets (2.25 cr)

• FIN 640: Financial Trading (1.5 cr)

• FIN 645: Real Options in Valuation (2.25 cr)

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