AØKA08152U Financial Econometrics A: Univariate Models for Volatility
Volume 2013/2014
Education
BSc in Economics
MSc in Economics
MSc in Economics
Content
An outline of the
contents:
- Properties and stylized facts of univariate asset returns and their variability.
- Analysis and discussion of volatility models such as GARCH-type models and stochastic volatility (SV) models as well as realized volatility (RV) and switching volatility models. In particular, stochastic properties of the processes will be discussed.
- Estimation of volatility and volatility models based primarily on (quasi) maximum likelihood. This includes application of the EM-algorithm as well as the Kalman-filter.
Learning Outcome
Applying and
understanding volatility models such as the well-known ARCH, GARCH
and stochastic volatility models require a background of
fundamental methodological concepts such as estimation, stochastic
properties of time series as well as simple programming. The aim of
the course is to provide students with an introduction to these
issues in financial time series analysis such that, on the one
hand, volatility models can be implemented and discussed, while at
the same time advanced financial econometric models can be
approached. This is achieved by analyzing implementation and theory
of univariate volatility models.
After completion of the course the student will specifically be able to:
After completion of the course the student will specifically be able to:
- Analyze and discuss classic univariate volatility models and volatility modeling in financial econometrics.
- Analyze and discuss stochastic properties of the models.
- Implement estimation of volatility and volatility models.
Literature
Syllabus
The course will be based on S. J. Taylor, Asset Price Dynamics, Volatility and Prediction, Princeton University Press, 2007 or 2005 edition, as well as lecture notes by Anders Rahbek handed out during term.
Supplementary reading: Tsay, Analysis of Financial Time Series. Wiley, 2005.
The course will be based on S. J. Taylor, Asset Price Dynamics, Volatility and Prediction, Princeton University Press, 2007 or 2005 edition, as well as lecture notes by Anders Rahbek handed out during term.
Supplementary reading: Tsay, Analysis of Financial Time Series. Wiley, 2005.
Academic qualifications
Econometrics C or similar.
This may be followed at the same time.
Teaching and learning methods
4 hours of lectures and 2
hours of classes per week in 14 weeks.
Workload
- Category
- Hours
- Class Exercises
- 28
- Exam
- 3
- Lectures
- 56
- Preparation
- 188
- Total
- 275
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Exam (Written)
- Credit
- 10 ECTS
- Type of assessment
- Written examination, 3 hours under invigilationA 3 hours written examination taking place at Peter Bangs Vej 36.
- Exam registration requirements
- During the semester there will be a number of small hand-in exercises that have to be accepted.
- Aid
- Written aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- External censorship
20 % censurship
- Exam period
- Will be updated before the start of the semester
- Re-exam
- Same as ordinary. But if only a few students have registered for the re-exam, the exam might change to an oral exams with a synopsis to be handed in. This means that the examination date also will change.
Criteria for exam assesment
The Student must in a satisfactory way demonstrate that he/she
has mastered the learning outcome of the
course.
Course information
- Language
- English
- Course code
- AØKA08152U
- Credit
- 10 ECTS
- Level
- Full Degree MasterBachelor
- Duration
- 1 semester
- Placement
- Autumn
- Schedule
- Autumn (week 36-50)
- Course capacity
- No limits
- Continuing and further education
- Price
- 320 DKK per ECTS
- Study board
- Department of Economics, Study Council
Contracting department
- Department of Economics
Course responsibles
- Anders Rahbek (13-6a776d6e7b7c377b6a716b6e74496e6c787737747e376d74)
Lecturers
Hold 1 Philipp Kless
Hold 2 Rasmus S Pedersen
Saved on the
17-07-2013