更新時間：2024-10-06 15:53:55作者：留學之路
量化金融和風險管理碩士是理學碩士，屬于數學系和統計學系共同管理一個跨學科的理學碩士學位項目。
該課程重點關注高級數學和統計方法。畢業生將擁有復雜的量化技能，這將使他們能夠將自己的知識應用于解決現實世界的金融問題，成為量化分析師、風險經理、交易員、開發人員和金融行業的其他角色。
量化金融和風險管理課程旨在培養優秀的數學家在金融行業工作。除了完成我們要求苛刻的課程外，Quant的學生還需要在第二和第三學期之間完成暑期實習，以獲得實際的行業經驗。為此，學生可以獲得密歇根大學就業中心和Quant項目工作人員提供的豐富的職業準備資源和就業服務，包括個人咨詢、簡歷準備研討會、雇主信息會議和招聘會，以及校園面試。
該項目的目標是為畢業生提供強大的數學背景，并發展必要的技能，以應用他們的專業知識來解決現實世界的金融問題。學生培養建模技能，使他們能夠從金融語言的描述中形成一個合適的數學問題，使用隨機分析和概率論的工具進行相關的數學分析，使用先進的數值方法實現結果，并根據這些結果進行解釋和決策。
量化項目要求總共36學分的課程，其中24學分是必修的核心課程，12學分是選修課。大多數學生在三個學期內完成課程，但偶爾會將課程延長到第四個學期。碩士加速課程的學生將以不同的順序完成相同的課程。
結構和必修課程
除特殊情況外，學生將按照規定的順序修讀以下核心必修課程:
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.