Courses

Courses at the Center for Big Data in Finance

Courses

 

 

Big Data Asset Pricing (PhD course)

Faculty
Lasse Heje Pedersen and Theis Ingerslev Jensen

Prerequisites
The course is designed as a first-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 aim of the class is to introduce Ph.D. students in finance and related fields to empirical asset pricing research methods using big data.

Find more information about the course here.

Empirical Finance: Fixed income (PhD course)

Faculty
Peter Feldhütter

Prerequisites
Knowledge of asset pricing, corporate finance and econometrics at a M.Sc. level is expected. Otherwise, the course is designed as a first PhD course in empirical finance.
The course is open for other participants with an adequate background

Aim
This course is a course on fixed income at the PhD level. The course attempts to lay the groundwork for students who will later do actual empirical research work in fixed income. It is therefore a hands on course where the students will have to perform analysis on actual data, and where the examples are chosen to illustrate the typical questions asked in finance research. The focus is on classic estimation methods, but the course will also, where relevant, outline recent developments.

Find more information about the course here.

Asset Management and Hedge Fund Strategies (Master's course)

Faculty
Lasse Heje Pedersen

Find more information about the course here. 

 

 

 

 

The page was last edited by: Department of Finance // 01/23/2023