Big Data Asset Pricing
Details: A Concentrated Hybrid Class
Instructors: Lasse Heje Pedersen (LHP) and Theis Ingerslev Jensen (TIJ)
Prerequisites: The course is designed as a first- or second-year Ph.D. course. The prerequisites are knowledge of asset pricing theory and econometrics at a M.Sc. level and an ability to work independently with data using a programmatic computer language such as Matlab, R, or Python. Students must participate in the whole course and do all problem sets.
Aim: The class aims to introduce Ph.D. students in finance and related fields to research methods in big data asset pricing.
Format: Hybrid (the course can be followed online) over 6 weeks. There is one lecture per week, except that lectures 5-6 are held on two consecutive days, where participants from abroad are encouraged to show up physically at Copenhagen Business School.
Time. The class in held in the Spring of 2023 at Copenhagen Business School, likely around March.
Lecture plan (preliminary, 3h means 3 hours):
Exercises: must be handed in before the lecture in which they are discussed. Exercise 5 should be handed in 2 weeks after the last lecture.