Empirical Finance

2019-2020

Course Objective

The student is able to:
1) translate a financial research question into a modelling equation
that can be operationalized for statistical or mathematical analysis.
2) Apply various empirical models and methods - ranging from linear
regression, maximum likelihood, time series models and forecasting – on
empirical data, using statistical software
3) Report the results of his/her analysis clearly according to academic
standards.

Course Content

This course offers students the opportunity to study advanced empirical
research methods in finance. The objective is to increase the students'
ability to understand and to apply empirical methods in finance. The
course represents an integration of theory, methods and examples. We use
STATA as our standard software. The aim of the course is to enable
students to undertake their own quantitative research projects in
practice.
The course concentrates on the following methodologies: regression
models, panel data, endogeneity and instrumental variables, non-linear
models, logit / probit, credit risk, time series models, volatility
models (GARCH), forecasting.

Teaching Methods

The first week there is an introductory computer lab session to get
familiar with the software used in class, STATA. There are two lecture
sessions each week for six weeks. Next to this, there is a lab session
or a tutorial each weak in smaller groups.
The programme consists of lectures, classroom discussions, case work,
and computer exercises. Students are expected to actively participate in
all classroom discussions. The purpose of the compulsory case work is to
give students the practical skills for solving empirical finance
problems.

Method of Assessment

There is a final written exam (70 percent; minimum grade 5.0 to pass the
course).
An important part of this course is also the case work (30 percent). The
case has been developed in close cooperation with a partner company. The
aim of the case is to give you insight into what might be expected of
you in your first job in the role of a model builder for financial
decision making. Not only will you apply your methodological tools, but
you will also practice team work, reporting skills, and the skill to
look for the managerial implications of what you have done.

Entry Requirements

Students should have a sound knowledge of introductory mathematics
(including linear algebra) and statistics at the bachelor economics
level and be familiar with key concepts of corporate finance,
investments and financial markets.

Indication of entry level:
Sydsaeter and Hammond (2006, Prentice Hall): Essential Mathematics for
Economic Analysis.
Business Statistics Berenson, Levine, Krehbiel (2002): Basic Business
Statistics.
Brealey and Myers (2002): Principles of Corporate Finance, 7th ed.
Bodie, Kane, and Marcus (1996): Investments.

Literature

Book: Introductory Econometrics for Finance, 4th Edition, Chris Brooks,
Cambridge University Press.
Slides and lecture notes.
Relevant academic papers (to be indicated at the start of the course).

Target Audience

MSc Finance

Recommended background knowledge

Core courses Advanced Corporate Finance (4.1) and Asset Pricing (4.1).

General Information

Course Code E_FIN_EF
Credits 6 EC
Period P2
Course Level 400
Language of Tuition English
Faculty School of Business and Economics
Course Coordinator dr. A. Opschoor
Examiner dr. A. Opschoor
Teaching Staff dr. A. Opschoor

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Seminar, Lecture, College case
Target audiences

This course is also available as: