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典型量化金融硕士项目先修课要求——典型学校项目举例
1、耶鲁大学资产管理项目
作为金融大类中偏量化的项目，耶鲁大学资产管理硕士的先修课要求清晰反映了学校的审理倾向。尽管多元微积分、线性代数（或矩阵代数）、微观经济学、概率论与统计及相关编程课程并非硬性要求，但具备这些课程背景或通过学术/补充学习掌握相关知识，将为课程学习奠定坚实基础。学校会通过申请人的经历及技能补充情况评估其基础能力，而非仅以课程缺失直接拒录。
官方说明：A strong quantitative background will serve as a helpful foundation to prepare for the Master’s in Asset Management program. Courses in multivariable calculus, linear or matrix algebra, microeconomic theory, probability and statistics, and computer programming are not required for admission, but exposure to the subject matter through academic or supplemental study will provide a highly beneficial background for the curriculum. Applicants are asked to note any previous coursework in these topics in the application so the admissions committee can identify if you may benefit from additional quantitative exposure prior to matriculating at Yale SOM.
2、圣路易斯华盛顿大学金融项目
该项目下设四个方向，其中量化金融与财富管理为STEM认证方向。财富管理方向明确要求修过微积分I、统计学和微观经济学；量化金融方向虽无强制课程要求，但过往申请经验显示，上述三门课程仍为推荐背景，且该方向尤其偏好量化能力突出的申请人。
官方说明：Successful applicants demonstrate outstanding aptitude for advanced quantitative finance materials. Students who have majored in mathematics, computer science, quantitative economics, engineering, physics and statistics are especially encouraged to apply.
3、芝加哥大学金融硕士项目
作为2024年秋季新设的项目，芝加哥大学金融硕士课程设置偏量化，偏好具备量化背景的申请人。与耶鲁类似，项目无强制先修课要求，但倾向于申请人通过过往经历证明对线性代数、统计学、多元微积分、Python、C++等量化技能的掌握。
官方说明：While there are no specific required classes, it is recommended applicants have taken advanced quantitative coursework and have exposure to coding. Examples include: Linear Algebra, Statistics, Multivariable Calculus, Python, C++.
4、加州大学圣地亚哥分校（UCSD）量化金融项目
该项目注重实用技能，要求申请人掌握统计、计量经济学、数学应用相关课程及工具，并具备计算编程能力（如C++）。相关在线课程也可作为能力证明。
官方说明：Provide details regarding your experience with computational programming (for example, C++) and with statistical, econometrics and mathematical applications and tools (for example, SAS, Stata, MatLab, R, S-Plus, Mathematica).
金融工程/金融数学典型举例
金融工程/金融数学与金融（量化金融分支）存在显著差异：金融大类通常隶属于商学院，而金融工程/金融数学多归类为理科或工科，可理解为金融领域的“技术岗位”，更倾向理工科背景申请人。相比之下，商科背景学生更适配金融/量化金融方向。
哥伦比亚大学金融工程与金融数学项目
哥大在工学院和文理学院分别开设金融工程（MSFE）和金融数学项目，两者先修课要求明确，网申中需详细填写课程名称、修习平台、学分及成绩等信息。其要求可直观体现金融工程与金融数学的审理侧重点：
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金融工程（工学院）：
核心要求包括微积分、线性代数、概率论与统计学，微分方程背景为加分项。编程能力（如Python）为必备技能，哥大IEOR系提供编程训练营以帮助提升。尽管属于工程类项目，但因聚焦金融问题解决，扎实的金融知识（如衍生品、风险管理、投资组合理论及市场动态）及对金融科技（如大数据、AI在量化决策中的应用）的了解将提升竞争力。
官方说明：Applicants aspiring to join the MSFE program are expected to possess a strong foundational knowledge of essential subjects such as calculus, linear algebra, probability, and statistics. Familiarity with differential equations would also be advantageous. Proficiency in coding and the ability to work with financial models, conduct scenario simulations and analyze and mine data are integral to the program. Therefore, a mastery of programming languages like Python is not just valuable but essential. It's noteworthy that the IEOR department offers programming bootcamps to bolster your programming skills. A robust comprehension of finance concepts is indispensable. This includes a solid understanding of derivatives, risk management, portfolio theory, and the dynamics of financial markets. Immersing yourself in financial news and staying attuned to market trends can greatly enhance your perspective. The field of financial engineering has been substantially transformed by the advent of big data and artificial intelligence. It is highly recommended that you stay abreast of how machine learning and AI are being harnessed in this domain to drive data-centric decision-making. -
金融数学（文理学院）：
作为数学分支，该项目更侧重数学基础，必备课程包括微积分、线性代数、初等微分方程、概率论、统计学及编程语言。高阶课程（如高等微积分、数学分析、测度论）虽非必需，但能提升竞争力并帮助适应研究生阶段学习。
官方说明：Applicants should have a very good working knowledge of calculus, linear algebra, elementary differential equations, probability and statistics, and a programming language. Exposure to advanced calculus and mathematical analysis, including measure theory, is desirable but not required.
