Econometric Methods

Code:

2MiF03

Acronym:

EM

Keywords
Classification	Keyword
OFICIAL	Management Studies

Instance: 2020/2021 - 1S

Active?	Yes
Course/CS Responsible:	Master in Finance

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MIF	42	Official Syllabus after 2020-2021	1	-	6	42	162

Teaching language

English

Objectives

The main goal of the course is to introduce econometric methods which are useful in the study of financial questions. The methods will be demonstrated by resorting to financial data and to specialized software. The course should also prepare the students to create and analyze empirical models in their dissertation or in the context of other scientific research in the financial area.

 

Learning outcomes and competences

More specifically, the students will learn

- to create, estimate and interpret financial econometric models;

- to read and interpret articles in scientific Finance journals;

- to work with specialized software (EViews); and

- will develop skills on financial data use.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Statistics and multiple regression.

Program

Course Outline:

1. Introduction. Structural models and time series models in Finance. Returns and risk. Asymmetry, non-linearity and volatility.

2. Classical Linear Regression Model. Hypotheses.

3. Heteroskedastic models.

4. Autocorrelated models.

5. Qualitative dependent variable models.

6. Time series and dynamic models. 

7. Panel data models.

8. Case studies of financial problems using EViews software.

 

Mandatory literature

Chris Brooks; Econometrics for Finance, Cambridge University Press, 2008

Complementary Bibliography

Chistiaan Heij, Paul de Boer, Philip Hans Franses, Teun Kloek and Herman K. Van Dijk; Econometric Methods with Applications in Business and Economics, Oxford University Press, 2004

Teaching methods and learning activities

Several econometric models will be presented from the theoretical and technical perspectives, and will be illustrated through “case studies” – the methodology which we call RMRD, for Real Models with Real Data, in which applied studies of relevant financial problems with resort to real data an adequate software are made. Scientific literature which contains these econometric models will also be discussed.

The course will look for the active participation of students and encourage experimenting with data econometric methods and the use of software. The interplay between financial theory and practice will also be stressed, thus preparing the students to use financial econometric models in their future academic, scientific or industry research.

 

Software

Econometric Views v8

keywords

Social sciences > Economics > Financial science

Evaluation Type

Evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	100,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	146,50
Frequência das aulas	56,00
Total:	202,50

Eligibility for exams

NA

Calculation formula of final grade

The final grade will be determined from one final exam.