Courses

Courses taught by BIGFI members

Courses

 

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

Faculty
Lasse Heje Pedersen

Find more information about the course here. 

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.

Corporate Finance (Bachelor's course)

Faculty
Markus Ibert

Learning objectives

  • Identify, explain, discuss, and apply the core concepts, models, and methods
  • Calculate, interpret, and compare financial statistics, prices, returns, and costs
  • Elaborate, present, and discuss solutions for financial decision problems

Find more information about the course here.

Derivatives and Fixed Income (Master's course)

Faculty
Peter Feldhütter

Learning objectives

  • Understand and explain the payoff and risk properties of the main types of derivative securities
  • Understand and explain how derivative securities can be used for risk management
  • Understand, explain, and apply the central methods and models for the pricing of derivative securities

Find more information about the course here.

Derivatives and Risk Management (Master's course)

Faculty
Peter Feldhütter

Prerequisites
This is a mandatory course for the MSc in Advanced Economics and Finance. It is assumed that students have knowledge similar to the entry requirements for the MSc in Advanced Economics and Finance. For spring courses knowledge similar to the content of the 1st-semester courses is assumed as well. The courses have 45 contact hours (lectures and exercises), and there is a high level of interaction between lecturer and students, and in general a high work load. 

To sign up send a 1-page motivational letter, a 1-page CV, and a grade transcript to ily.stu@cbs.dk before the registration deadline for elective courses. You may find the registration deadlines on my.cbs.dk ( https:/​/​studentcbs.sharepoint.com/​graduate/​pages/​registration-for-electives.aspx ). 
 
Learning objectives
  • Be able to analyze, price, and discuss the use of derivative securities
  • Be able to analyze, discuss, and apply the concept of no-arbitrage and its limitations
  • Be able to analyze, discuss, and apply interest rate risk and credit risk modelling concepts
  • Be able to apply and analyze Value-at-Risk based risk measures
  • Be able to analyze and discuss financial risk management in financial institutions

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.

Finansiering (Bachelor's course)

Faculty
Jens Dick-Nielsen

Find more information about the course here.

 

Financial Econometrics (Master's course)

Faculty
Rasmus Tangsgaard Varneskov

Learning objectives
The course will provide students with an understanding of how carry out econometric analysis within different subfields of finance. In particular, the students will obtain a toolbox consisting of knowledge of modern models, methods, and econometrics that are required for analyzing financial data

Prerequisites
Baseline knowledge of statistics, econometrics and asset pricing. Experience with coding is an advantage.

Find more information about the course here.

 

 

 

The page was last edited by: Department of Finance // 02/21/2023