Financial Econometrics

Course Code: 
Elective Courses

Number of credits allocated: 6 ECTS Credits

Objective of the course (expected learning outcomes and competences to be acquired)

The aim of the course is to introduce students to econometric models that apply to finance and general economics. The material involves stochastic processes such as ARMA, GARCH, EGARCH, and heteroskedastic in Mean. Stochastic and deterministic non-stationarity as well as cointegration are also examined. Part of the lesson is student involvement with real data. All econometric exercises are held in the department's laboratory. Upon successful completion of the course, the students will:

  • have fully understood the statistical properties of financial returns,
  • be able to formulate and analyze the properties of ARIMA models as well as to evaluate, analyze and evaluate these models based on their predictive ability,
  • have understood the principle of Maximum Likelihood and will employ it for estimation and statistical inference,
  • have comprehended ARCH and GARCH models and will be able to apply them to financial assets that exhibit volatility clustering and dynamic asymmetry, and
  • apply cointegration techniques to exemplify long-term and short-term relationships between financial data

Prerequisites: none

Course contents

Covered Material:

  1. Characteristics of financial series: independence, stationarity and normality.
  2. Introduction to ARMA models.
  3. Introduction to non-stationary time series, Cointegration.
  4. Introduction to GARCH type of models.
  5. Efficiency, Random Walk, Predictability and volatility of financial time series.
  6. Test for Market Efficiency and time varying risk premium: stocks, bonds, exchange rates.
  7. Testing of Asset Pricing Models.

Recommended reading

  • Brooks C., 2002, Introductory Econometrics for Finance, Cambridge University Press.
  • Campbell J., A. Lo and G. MacKinlay, 1997, The Econometrics of Financial Markets, Princeton Univ. Press
  • Gourieroux C., 1997, ARCH Models and Financial Applications, Springer
  • Enders W., 1995, Applied Econometrc Time Series, Wiley.
  • Hamilton J. D.,  1994, Time Series Analysis, Princeton University Press.
  • Mills T. and R Markellos 2008, The Econometric Modelling of Financial Time Series, Cambridge Univ. Press
  • Xekalaki E. and  S. Degiannakis 2010, ARCH Models for Financial Applications, J. Wiley and Sons
  • Notes (in English)

Teaching methods : For every 3 hours Lectures 1 hour lab.

Assessment methods: Final written exam

Language of instruction: Greek-English