1.选修课
Optimization 优化
Enterprise Risk Management 企业风险管理
Data mining and Machine Learning 数据挖掘和机器学习
Financial Markets 金融市场
Software Engineering Foundations 软件工程基础
Bayesian Inference and Computational Methods 贝叶斯推理和计算方法
Financial Engineering 金融工程
Numerical Analysis (PDEs) 数值分析二酯酶(PDE)
Advanced Derivative Pricing 高级衍生品定价
Numerical Techniques for PDE's with either Time Series or Financial Econometrics PDE的数字技术与任一时间序列或金融计量;
Advanced Software Engineering 高级软件工程。
2.必修课
Students will take a total of 8 courses, 4 in each of the 1st and 2nd Semesters followed by a 3-month Project in the summer.
Modelling and Tools;
Derivative Markets, Pricing and Financial Modelling;
Statistical Methods (recommended);
Stochastic Simulation;
Modern Portfolio Theory.
Progression to the MSc project phase is dependent on assessed performance. Typical project topics may include:
Applications of multilevel Monte-Carlo sampling in finance;
An investigation of new numerical methods for stochastic interest rate models;
Space time adaptivity for Fokker—Planck equations.
学生将修读共8门课程,分别在第一和第二学期各修读4门,并在夏天尽心为期3个月的项目。
模型和工具;
衍生工具市场,定价和财务建模;
统计方法(推荐);
随机模拟; 现代投资组合理论。
硕士项目进程依赖于评估表现。通常的项目主题包括:
在金融多蒙特卡洛采样中的应用; 对随机利率模型的新数值方法的调查; 为福克 - 普朗克方程式时空适应性。