爱丁堡大学计算数学金融专业-新东方前途出国

There are three streams: the Financial stream, the Computational stream and the Machine Learning stream*. Each stream features different sets of compulsory and optional courses.

Compulsory courses (for all streams) have previously included:

• Stochastic Analysis in Finance (20 credits, S1)
• Discrete-Time Finance (10 credits, S1)
• Python Programming (10 credits, S1)
• Numerical Probability and Monte Carlo (10 points, S2)
• Risk-Neutral Asset Pricing (10 credits, S2)
• Stochastic Control and Dynamic Asset allocation (10 credits, S2)
• Research Skills for Financial Mathematics (10 credits, S2)

Financial stream compulsory courses have previously included:

• Financial Risk Theory (10 credits, S2)
• Optimization Methods in Finance (10 credits, S2)

Computational stream compulsory courses have previously included:

• Time Series (10 credits, S2)
• Numerical Partial Differential Equations (10 credits, S2)

Machine Learning stream compulsory courses have previously included:

• Machine Learning in Python (10 credits, S2)

Optional courses have previously included:

• Blockchains and Distributed Ledgers (10 credits, S1)
• Programming Skills (10 credits, S1)
• Finance, Risk and Uncertainty (10 credits, S1)
• Bayesian Theory (10 credits, S1)
• Reinforcement Learning (10 credits, S2)
• Algorithmic Game Theory and its Applications (10 credits, S2)
• Financial Risk Theory (10 credits, S2)
• Credit Scoring (10 credits, S2)
• Optimization Methods in Finance (10 credits, S2)
• Bayesian Data Analysis (10 credits, S2)
• Integer and Combinatorial Optimization (10 credits, S2)
• Time Series (10 credits, S2)
• Numerical Partial Differential Equations (10 credits, S2)