TIME SERIES
Syllabus
EN
IT
Learning Objectives
LEARNING OUTCOMES: Students are expected to gain theoretical knowledge and advanced skills on the econometric analysis of economic and financial phenomena over time.
KNOWLEDGE AND UNDERSTANDING: Students will be able to autonomously develop all the phases of an empirical project aiming at analyzing and forecasting economic and financial time series.
APPLYING KNOWLEDGE AND UNDERSTANDING: Students will be able to understand an apply the main dynamic models that are used in empirical analyses.
MAKING JUDGEMENTS: Students will gain the ability to make judgments about implications of the statistical results for the issue at hand.
COMMUNICATION SKILLS: Students will be able to present and communicate effectively the results of the empirical analyses on time series data.
LEARNING SKILLS: Students will have the ability to develop and increase their skills through the consultation of the published scientific literature and the use of databases and other information.
KNOWLEDGE AND UNDERSTANDING: Students will be able to autonomously develop all the phases of an empirical project aiming at analyzing and forecasting economic and financial time series.
APPLYING KNOWLEDGE AND UNDERSTANDING: Students will be able to understand an apply the main dynamic models that are used in empirical analyses.
MAKING JUDGEMENTS: Students will gain the ability to make judgments about implications of the statistical results for the issue at hand.
COMMUNICATION SKILLS: Students will be able to present and communicate effectively the results of the empirical analyses on time series data.
LEARNING SKILLS: Students will have the ability to develop and increase their skills through the consultation of the published scientific literature and the use of databases and other information.
Prerequisites
Mathematics
Statistics
Linear regression model
Statistics
Linear regression model
Program
Univariate Time Series:
1) Stationary and non-stationary time series (first week)
2) Statistical inference and forecasting (second week)
3) Unit-roots in economics and finance (third week)
Multivariate Time Series:
4) Stationary and Ergodic Multivariate Time Series; Multivariate Wold Representation;
Vector Auto-Regressive (VAR) Models (fourth week)
5) Structural VAR Models (fifth week)
6) Cointegration (sixth week)
1) Stationary and non-stationary time series (first week)
2) Statistical inference and forecasting (second week)
3) Unit-roots in economics and finance (third week)
Multivariate Time Series:
4) Stationary and Ergodic Multivariate Time Series; Multivariate Wold Representation;
Vector Auto-Regressive (VAR) Models (fourth week)
5) Structural VAR Models (fifth week)
6) Cointegration (sixth week)
Books
Hansen, B.E. (2022), Econometrics, Princeton University Press (PDF freely available at GitHub).
Bibliography
Cochrane, J.H. (2005), Time Series for Macroeconomics and Finance, Manuscript.
Mills, T.C. & R.N. Markellos (2008), The Econometric Modelling of Financial Time Series, 3rd Edition, Cambridge University Press.
Mills, T.C. & R.N. Markellos (2008), The Econometric Modelling of Financial Time Series, 3rd Edition, Cambridge University Press.
Teaching methods
Lessons and practice in class, homework.
Exam Rules
The evaluation consists of a written exam that involves theoretical exercises and questions about the topics of the course. The average mark of the homework (if taken) will be weighted for 20% of the overall mark.
The student should demonstrate to have learned the theory and the advanced skills required for the econometric analysis of empirical phenomenons over time.
The exam cannot be taken twice in the winter session.
The criteria underlying the evaluation of the final exam are the following:
o 18-20: barely sufficient knowledge and understanding of the topics with possible imperfections; sufficient capacity for analysis, synthesis and autonomy of judgement.
o 21-23: Routine knowledge and understanding of the topics; Correct analysis and synthesis skills with coherent logical argumentation.
o 24-26: Fair knowledge and understanding of the topics; good capacity for analysis and synthesis with rigorously expressed arguments.
o 27-29: Comprehensive knowledge and understanding of the topics; Considerable ability to analyze, synthesize. Good autonomy of judgement.
o 30-30L: Excellent level of knowledge and understanding of the topics. Remarkable analytical and synthetic skills and independent judgement. Arguments expressed in an original manner.
The student should demonstrate to have learned the theory and the advanced skills required for the econometric analysis of empirical phenomenons over time.
The exam cannot be taken twice in the winter session.
The criteria underlying the evaluation of the final exam are the following:
o 18-20: barely sufficient knowledge and understanding of the topics with possible imperfections; sufficient capacity for analysis, synthesis and autonomy of judgement.
o 21-23: Routine knowledge and understanding of the topics; Correct analysis and synthesis skills with coherent logical argumentation.
o 24-26: Fair knowledge and understanding of the topics; good capacity for analysis and synthesis with rigorously expressed arguments.
o 27-29: Comprehensive knowledge and understanding of the topics; Considerable ability to analyze, synthesize. Good autonomy of judgement.
o 30-30L: Excellent level of knowledge and understanding of the topics. Remarkable analytical and synthetic skills and independent judgement. Arguments expressed in an original manner.
Attendance Rules
Although class attendance is not formally compulsory for bureaucratic reasons, it is considered of primary importance for a sound understanding of the subject.