密歇根大学安娜堡分校量化金融与风险管理硕士概况
量化金融和风险管理硕士是理学硕士，属于数学系和统计学系共同管理一个跨学科的理学硕士学位项目。
该课程重点关注高级数学和统计方法。毕业生将拥有复杂的量化技能，这将使他们能够将自己的知识应用于解决现实世界的金融问题，成为量化分析师、风险经理、交易员、开发人员和金融行业的其他角色。
量化金融和风险管理课程旨在培养优秀的数学家在金融行业工作。除了完成我们要求苛刻的课程外，Quant的学生还需要在第二和第三学期之间完成暑期实习，以获得实际的行业经验。为此，学生可以获得密歇根大学就业中心和Quant项目工作人员提供的丰富的职业准备资源和就业服务，包括个人咨询、简历准备研讨会、雇主信息会议和招聘会，以及校园面试。
密歇根大学安娜堡分校量化金融与风险管理硕士课程
该项目的目标是为毕业生提供强大的数学背景，并发展必要的技能，以应用他们的专业知识来解决现实世界的金融问题。学生培养建模技能，使他们能够从金融语言的描述中形成一个合适的数学问题，使用随机分析和概率论的工具进行相关的数学分析，使用先进的数值方法实现结果，并根据这些结果进行解释和决策。
量化项目要求总共36学分的课程，其中24学分是必修的核心课程，12学分是选修课。大多数学生在三个学期内完成课程，但偶尔会将课程延长到第四个学期。硕士加速课程的学生将以不同的顺序完成相同的课程。
结构和必修课程
除特殊情况外，学生将按照规定的顺序修读以下核心必修课程:
Semester 1
§ Math 472: Numerical Analysis with Financial Applications§ Math 526: Discrete State Stochastic Processes§ Math 573: Advanced Financial Mathematics I§ Stats 500: Applied Statistics I
Semester 2
§ Math 506: Stochastic Analysis for Finance§ Math 574: Advanced Financial Mathematics II§ Stats 509: Statistical Analysis of Financial Data§ 3 credits of electives
Semester 3
§ Math 623: Computational Finance§ 9 credits of electives This course plan is structured around four course sequences that serve as the foundation of the program. Successful completion of the first course in each sequence is necessary in order to move on to the second. These sequences are described below:I. Math 573 – Math 574 : introduces students to the main concepts of Financial Mathematics and Engineering. II. Math 526 – Math 506: analyzes in more detail the mathematical tools used in Math 573 - Math 574. The two sequences of courses discuss similar problems; however, the coursework in Math 526 – Math 506 focuses on the associated mathematical challenges, while the Math 573 - Math 574 sequence emphasizes the application of mathematical methods to the relevant problems in the financial industry.III. Math 472-Math 623: focuses on the implementation of the models using tools from numerical methods for solving partial differential equations and Monte-Carlo methods. The students will develop computer programs to calculate the prices of financial derivatives and find ways of hedging risk.IV. Stats 500 – Stats 509: introduces the basic statistical tools for financial data, including regression and time series models, as well as various inference techniques.
