3603714: Econometrics and time series analysis

Description

• The General Linear Model of Econometrics
• Single Equation Models
• Multiple Equation Models
• Hypotheses Tests (significance, normal distribution, auto-correlation, etc.)
• Data Collection, specifically financial market time series
• Empirical description of time series
• Time Series Stationarity
• Co-Integration and Error-Correction Model
• Econometric Application in Financial Market Econometrics
• Categorial Data in Econometrics (logit and probit model )
• Econometric Applications in Gretl

Learning Outcomes

• Illustrating the general econometric linear model
• Demonstrating estimation procedure in single and multiple equation models
• Choosing tests to confirm or reject general hypotheses
• Comparing models for time series prognosis
• Applying econometric methods in financial market theory
• Considering procedures and particularities in collecting categorial data
• Applying software for calculating econometric models

Lectures Method

Interactive lecture with exercises

Literature

Required reading:

• Veerbek, M. (2008). A Guide to Modern Econometrics. New York: John Wiley.
• Davidson, R. / MacKinnon, J.G. (2004). Econometric Theory and Methods. Oxford University Press.

• Wooldridge, J. (2005). Introductory Econometrics: A Modern Approach. Cengage Learning/ Thomson.
• Schröder, M. (2002). Finanzmarkt-Ökonometrie. Stuttgart: Schäffer-Poeschel.
• Hamilton, J. D. (1994). Time Series Analysis. New Jersey: Princeton University Press.
• Campbell, J. / Lo, A. / MacKinley, A.C. (1997): The Econometrics of Financial Markets. New Jersey: Princeton University Press.
• Wooldridge, J.M. (2002): Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: MIT Press.
• Greene, W. H. (2002): Econometric Analysis. Prentice Hall International.

Materials

Lecture slides, exercises, sample questions will be available on the moodle.