Financial Decisions under Risk 2. The main objective of this course is to present the application of machine learning in industries of asset management. This course contains three parts. The first part is devoted to the presentation of financial instruments (stock, bond, forward, future, option, etc.) in different asset classes such as equity, fixed-income, commodity, foreign exchange, and credit. The second part concerns the mathematical modeling of different assets and option pricing. The third part is devoted to the presentation of major machine learning algorithms (regularized linear regression, LASSO, RIDGE, logistic regression, Support Vector Machine, random forest, neural network) and their applications in asset management. Moreover, we introduce the portfolio optimization under risk and transaction constraints and present some alternative methods in portfolio construction. Also, the implementation in R is proposed to students to practice with real market datas.
Syllabus attached.
Course language: English
- Teaching coordinator: Amini Nina