Course aims:

The course aims to provide theoretical knowledge and practical skills related to quantitative analysis.
It is focused on modeling in econometrics and prediction in financial phenomena.
The issues described in this course are concerned with econometrics models based on time series with applicability in risk models,

Course Entry Requirements:

Statistics FB221, Econometrics FB321 - recommended but not mandatory

Course contents:

I. Examples and applications related to the role of time series in financial econometrics II. Applications for financial series modeling, based on autoregressive - moving average - ARIMA models and Garch models III. Aplications and case studies related to econometrics models for stationary and nonstationary financial series

Teaching methods:

Instruction is a combination of lectures, seminars and individual work; there are also compulsory assignments. There is 80% attendance requirement for seminars.

Learning outcomes:

- assimilating fundamental knowledge in the field of modeling and prediction of financial time series. - forming aptitudes needed for the analysis and prediction of financial series and for the elaboration of financial econometric models. - developing the capacity to analyze, communicate and control financial decisional models.

Learning outcomes verification and assessment criteria:

Final evaluation–project based on a particular econometric model related to real time series : Assessment of the specific knowledge during the presentation of the project (90% of the final grade).

Recommended reading:

W. Enders, Applied Econometric Time Series, John Willey and Sons, INC, Series in Probability and Mathematical Statistics, Iowa, 1995, -.
J. Johnston, J. DiNardo, Econometric Methods, 4th ed, Mc Graw-Hill, New York, 1997, -.
G. Smith, Essential Statistics, Regression, and Econometrics, 1st Edition, Elsevier, Academic Press, -, 2011, -.
L. Swift, Mathematics And Statistics For Business, Management And Finance,, MacMillan Publishers LTD, Hampshire, 1997, -.