Seminar: Monte Carlo methods in econometrics and finance (F)

Course content

The purpose of the exercise is to offer the students an overview of the use of simulation-based methods (Monte Carlo methods) in econometrics and finance. The focus will be on understanding the underlying statistical theory as well as how to implement the methods in practice via computer programs written by the students.

Three lectures of 3 hours each will be held introducing the fundamental concepts and suggesting more advanced topics for papers. 



MSc programme in Economics

The seminar is primarily for students at the MSc of Economics

The seminar is part of the Financial line at the MSc programme in Economics,   symbolized by ‘F’.


Seminaret er ens med seminaret "Monte Carlo metoder i økonometri og finansiering (F)" (AØKK08374U). Grundet pensum overlab er det ikke tilladt at deltage på dette seminar, hvis man har deltaget på seminaret .

Learning outcome

After completing the seminar the student must have achieved the learning outcome specified in the Curriculum.


The seminar paper can be based on several different themes. For example:

  • The results of an academic paper is challenged by replicating central results with a new twist, eg. Size/power of a proposed test using different data generating processes
  • Examining an interesting problem which can be examined via simulation, eg. The impact of discreet hedging in the Black-Scholes setup
  • Review of a simulation problem and implementation of various solutions, fx. Far out of the money options and importance sampling
  • Simulation based exploration of a suspected but not proven result, eg. See section 3 in Pedersen and Rahbek (2016)
  • Discuss methods variance reduction, covering the theory and implementing them in a program eg. Control variates, importance sampling, conditional Monte Carlo etc.
  • Discuss methods for random variate generation, covering the theory and implementing them in a program, eg. Adaptive Acceptance-Rejection, MCMC

Kick-off meeting, research and writing process of the seminar paper, sessions with presentation of own paper and critical evaluation/feedback to another student´s paper, actively participating in discussions at class.

Before the session a "so-finalized-as-possible"-version of the paper must be uploaded in Absalon. After the presentations, the student submit an edited version of the paper in the Digital Exam portal as the final exam paper. The aim is that students use the presentation sessions as an opportunity to receive and use the constructive feedback to improve the paper.

  • Thor Pajhede (2017), "Backtesting Value-at-Risk: A Generalized Markov Framework", Journal of Forecasting
  • Paul Glasserman (2003), "Monte Carlo Methods in Financial Engineering", Springer, ISBN 978-0-387-21617-1
  • Søren Asmussen & Peter W. Glynn (2007), " Stochastic Simulation: Algorithms and Analysis", Springer, ISBN 978-0-387-69033-9


The student should be comfortable programming in a suitable language such as R, Ox, Python or Matlab

It is an advantage but not an absolute necesity to know basics of continuous time finance such as the basics of the Black-Scholes mode i.e from the courses Derivative Pricing, Financial Econometrics A, Pricing Financial Assets.

BSc in Economics or similar
The course Econometrics II must have been followed.

• Kick-off meeting: September 6, 2018 at 17-19
• Additional teaching: 13 and 20th of September 17-19
• Deadline commitmentpaper: not later than October 1, 2018 at 10AM
• Deadline of pre-paper uploaded to Absalon: one week before presentations
• Presentations/Workshops: November 22 and 23, 9-16

7,5 ECTS
Type of assessment
Written examination
- a seminar paper in English that meets the formal requirements for written papers stated in the curriculum of the Master programme and at KUNet for seminars.
All aids allowed
Marking scale
7-point grading scale
Censorship form
External censorship
Criteria for exam assessment

Students are assessed on the extent to which they master the learning outcome for the seminar and can make use of the knowledge, skills and competencies listed in the learning outcomes in the Curriculum  of the Master programme.

To receive the top grade, the student must with no or only a few minor weaknesses be able to demonstrate an excellent performance displaying a high level of command of all aspects of the relevant material.

  • Category
  • Hours
  • Seminar
  • 20
  • Project work
  • 186
  • English
  • 206