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

Course content

Autumn 2018:

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.

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

Spring 2019:

The purpose of the exercise is to offer the students an overview of the use of fundamental simulation-based methods (Monte Carlo methods) in econometrics and finance especially. 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.

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 of variance reduction, covering the theory and implementing them in a program eg. A horse race of 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. Possibly providing a small extension of an academic paper
Education

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

Spring 2019:

Additional for the learning outcome specified in the Curriculum the student should

• Have a basic overview of fundamental tools used in Monte Carlo methods applied in financial econometrics and finance
• Be able to learn new and more advanced methods not covered in the course on their own
• Be able to implement Monte Carlo methods in a suitable programming language such as Matlab, Python, R, C++ or Ox

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

The aim of the presentations is, that the student, who presents, uses the presentation as an opportunity to practice oral presentations skills and to receive feedback improving the seminar project.

Process:
It is strongly recommended that you start your search for a topic before the semester begins, as there is only a limited amount of weeks from the kick-off meeting to the first submission.

Before the presentations, your largely finished version of the seminar project paper must be uploaded in Absalon, as the opponents and the other seminar participants have to read and comment on the paper. It is important that you upload a nearly finished project due to the fact that the value of feedback and comments at the presentation is strongly associated with the skill of the seminar project paper.

After the presentations, you can make a light correction of the seminar project to include the feedback and comments emerged during the presentations. It is NOT intended that you rewrite or begin the writing of the full project AFTER the presentation has taken place.

The seminar project paper must be uploaded in the Digital Exam portal for assessment with in the deadline announced under Exam.

• 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

Autumn 2018:
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.

The course Econometrics II must have been followed.

Spring 2019:
• The student should be comfortable programming in a suitable language such as R, Ox, Python, C++ or Matlab
• The student should have an understanding of basic continuous time finance topics such as the Black-Scholes model. For example as covered in Derivative Pricing, Financial Econometrics A, Pricing Financial Assets or equivalent courses.
• The student should have a basic understanding of topics from probability theory from an introductory course

BSc in Economics or similar

Schedule:
Autumn 2018:
• 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

Spring 2019:
• Kick-off meeting: 7 February 2019. 17:00 - 20:00
• Additional teaching: 14 and 21 February. 17:00 - 20:00
• Deadline commitmentpaper: Decided by the supervisor and not later than March 1, 2019 at 10AM
• Deadline of pre-paper uploaded to Absalon: one week before presentations
• Presentations/Workshops: 23-24 of May full day 09-17

All information from the lecturer regarding the seminar is communicated through Absalon including venue.

ECTS
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.
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Aid
All aids allowed

for the project paper.

The supervisor defines the aids that must be used for the presentations.

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Marking 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