Regression analysis

Finite and large sample properties of least squares estimates

Specifications and model selection

Regression diagnostics

Generalized least squares

Endogeneity and instrumental variable estimation

Generalized method of moments

Maximum likelihood estimation; LM, LR and Wald tests

Time Series Analysis (ARMA, GARCH and nonstationary models)

Vector-autoregressive models

Cointegration and error correction models

After passing this course students will have acquired a basic knowledge of regression and time series analysis. Students will have learned to apply topics from these fields from a rather wide range of applications, mainly in finance. Students will have acquired econometric theory on a level which is sufficient to understand empirical financial research. They will know how to appropriately use selected econometric techniques depending on the research question. Students will have learned basic ideas, techniques, methods, models and tests so that these skills can also serve as a starting point for a more advanced course in econometrics.

Participants are expected to have read the appropriate sections (announced at the end of each class) from the lecture notes. They should be well acquainted with the contents of the reviews. These will not be repeated during the course. Participants have to do assignments based on the exercises specified in the lecture notes. The purpose of the assignments is to practice, to repeat the theory, and to obtain a collection of empirical evidence on financial data.

80% of the final grade are based on the final exam. 20% are based on the quality of your presentations and answers when presenting/reviewing homework assignments in class and, equally or even more importantly, your active contributions during class (both when reviewing homework assignments and otherwise). Executing and delivering homework assignments is a necessary but not a sufficient condition for obtaining a positive evaluation. Note that the main purpose of carrying out and reviewing homework assignments is to prepare for the final exam. An opportunity to retake the final exam may be granted to those who failed the first exam. The first and second take will be aggregated using equal weights to obtain the final grade on the final exam. This will still account for 80% of the overall grade. You can only pass the class if the homework/classroom part and the final exam are graded positively. Homework assignments can be done in groups consisting of not more than three students. However, each student must be able to explain all aspects of an assignment (i.e. it is not recommended that group members only do parts of an assignment; all group members should work jointly and take equal responsibility). The assignments must be uploaded to Learn@WU at least one day before the next class. Students must upload their assignment in time even if they cannot attend. Students will be randomly and individually selected to present the results of the assignments in class. This is a very informal presentation. However, all students in class (i.e. not only those who are currently presenting) should be prepared to answer questions asked about their own or other students’ solutions and the relevant methodological foundations. Thereby, topics covered in the previous unit(s) are thoroughly reviewed. This provides a very good preparation for the final exam, in which similar questions will be covered. Grading of the final exam depends very much upon the way you deal with the questions, on the competence expressed, and on the precision of your answers. The more you are able to show your skills and a thorough understanding of the subject the better the grade will be.

Mathematics (e.g. matrix algebra, polynomials, derivatives, etc.), statistics (e.g. probability theory, sampling distributions, hypothesis testing, etc.) and basic finance. Computing skills required: Excel and EViews. EViews is very easy to learn and use (mainly from watching me during class or using my EViews support.

1	Author: Alois Geyer Title: Basic Financial Econometrics Year: 2010 Content relevant for class examination: Yes Recommendation: Essential reading for all students Type: Script

Office hours (and exceptions): www.wu.ac.at/~geyer e-mail: alois.geyer@wu.ac.at