This is the course page for the 2018 edition of Econ 672 and Econ 872 at Duke University.
Overview
The course covers empirical methods in financial econometrics, with an emphasis on high-frequency data, volatility modeling, and asset pricing applications.
Course Logistics
- Instructor: Guilherme Salome (office hours by appointment)
- Teaching Associate: Ivan Abramov (office hours Wednesdays 12:00-1:30 pm, SocSci 213)
- Schedule: Tuesdays and Thursdays, 4:40-5:55 pm, Gray 228
Course Materials (2018)
Materials are listed in the original course sequence. The syllabus and data appear first, followed by lectures and projects.
- Syllabus - HTMLPDF
- Data - HTMLPDF
- Course Instructions - PDF
- Lecture 1 - LaTeX - HTMLPDF
- Lecture 1 - Git - HTMLPDF
- Lecture 2 - Jump-Diffusion Processes - PDF
- Lecture 2 - Simulation - PDF
- Project 1 - HTMLPDF
- Lecture 4 - IV Estimation - PDF
- Project 2 - HTMLPDF
- Lecture 6 - Jump Separation - PDF
- Project 3 - HTMLPDF
- Lecture 7 - The Bootstrap - HTMLPDF
- Lecture 7 - Delta Method - PDF
- Lecture 7 - Realized Beta - PDF
- Lecture 8 - Local Variance - PDF
- Midterm - HTMLPDF
- Lecture 9 - Jump Regression - PDF
- Project 4 - HTMLPDF
- Lecture 10 - Forecasting RV - PDF
- Lecture 11 - Part 1 (In-class notes) - HTMLPDF
- Project 5 - HTMLPDF
- Lecture 12 - Part 2 (In-class notes) - HTMLPDF
- Lecture 13 - Part 3 (In-class notes) - HTMLPDF
- Lecture 14 - Installing Python - PDF
- Lecture 14 - Managing Versions - PDF
- Lecture 15 - Jupyter Notebook - HTMLPDF
- Lecture 15 - Python - Notebook
- Lecture 16 - Numpy - Notebook
- Lecture 16 - TensorFlow - Notebook
- Lecture 16 - Matplotlib - Notebook
- Project 6 - HTMLPDF
- Lecture 17 - Options - PDF
- Lecture 17 - Microstructure Noise - PDF
- Lecture 17 - TSRV - PDF
- Final Exam - HTMLPDF