Type of Credit: Required
Credit(s)
Number of Students
This course is designed to provide postgraduate students with the econometric toolbox for conducting empirical research in finance. The semester will be divided into two major topics. The first part of the course is the lecture on linear regression and regularization techniques, with the empirical application in equity premium predictability. The second topic is panel data methods, with its main application in cross-sectional predictability in the equity market.
能力項目說明
| 教學週次Course Week | 彈性補充教學週次Flexible Supplemental Instruction Week | 彈性補充教學類別Flexible Supplemental Instruction Type |
|---|---|---|
| Week | Topic | Content and Reading Assignment | Teaching Activities and Homework | Student workload expectation | |
| In-class Hours | Outside-of-class Hours | ||||
| 1 | Class introduction | 3 | 0 | ||
| 2 | Review of Linear Algebra | Lecture notes | Lecture | 3 | 0 |
| 3 | Linear regression (I) | Lecture notes | Lecture | 3 | 3 |
| 4 | Linear regression (II) | Lecture notes | Lecture | 3 | 3 |
| 5 | Forecast evaluation (I) | Lecture notes | Lecture | 3 | 3 |
| 6 | Forecast evaluation (II) | Lecture notes | Lecture | 3 | 3 |
| 7 | Dimension reduction | Lecture notes | Lecture | 3 | 3 |
| 8 | Regularization | Lecture notes | Lecture | 3 | 3 |
| 9 | Midterm Exam | Exam | 3 | 6 | |
| 10 | Panel data | Lecture notes | Lecture | 3 | 3 |
| 11 | Maximum likelihood | Lecture notes | Lecture | 3 | 3 |
| 12 | Generalized method of moments | Lecture notes | Lecture | 3 | 3 |
| 13 | Instrumental variables | Lecture notes | Lecture | 3 | 3 |
| 14 | Boosting | Lecture notes | Lecture | 3 | 3 |
| 15 | Multiple testing | Lecture notes | Lecture | 3 | 3 |
| 16 | Final Exam | Exam | 3 | 6 | |