Upon successful completion of this course the student should have a profound understanding of financial time series. (S)he should be able to combine financial theory with financial data and identify salient features of financial time series. The student should be able to subject financial theories to empirical testing in a critical manner and report the results to specialists and non-specialists alike.
This course is tailored to the needs of advanced graduated students of economics and finance. It augments the students knowledge of econometric methods for finance by focussing on financial time series analysis which is concerned with the theory and practice of asset valuation. The statistical knowledge necessary to reach a firm understanding of inferential procedures (estimation and testing) suitable in the context of financial models is provided. The practical skills needed to implement such techniques are build by (i) studying cases taken from the applied finance literature and (ii) by challenging the students through in-class projects involving real life financial data. Topics covered include: characteristics of financial time series, advanced linear time series analysis, conditional heteroscedastic models, non-linear time-series analysis, continuous time modeling, alternative approaches to Value at Risk (econometric, extreme value), multivariate times series, principal component/factor analysis, multivariate GARCH models, Kalman filtering and Markov-Chain-Monte-Carlo methods.
Lectures and group sessions (students present their project work).
Mandatory assignments comprising 40% of the final grade. A 3-hour final written exam comprising 60% of the final grade.
Second cycle i.e. master level.
Normally fourth year.
Student Adviser Anne Line Omsland.
The syllabus will be published on the home page of the course when finalised. See link in the upper right hand corner of the page.
Faculty of Economics and Social Sciences