Economics, Financial Econometrics, Second Cycle, 15 credits

Aims and objectives

General aims for second cycle education

Second-cycle courses and study programmes shall involve the acquisition of specialist knowledge, competence and skills in relation to first-cycle courses and study programmes, and in addition to the requirements for first-cycle courses and study programmes shall

• further develop the ability of students to integrate and make autonomous use of their knowledge
• develop the students' ability to deal with complex phenomena, issues and situations, and
• develop the students' potential for professional activities that demand considerable autonomy, or for research and development work.

(Higher Education Act, Chapter 1, Section 9)

Course objectives

Subcourse 1: Econometrics

Knowledge and understanding

After completion of the course, the student will have

• deeper knowledge of basic concepts in econometrics
• knowledge of regression models using cross-sectional data, panel data.

Competence and skills

After completion of the course, the student will have

• the ability to use the knowledge in applied situations within financial economics supported by statistical software.

Judgement and approach

After completion of the course, the student will have

• the ability to critically review and evaluate econometric models.

Subcourse 2: Time Series Analysis and Forecasting

After completion of the course, the student will have

• knowledge of basic concepts in time series analysis
• knowledge of time series regression
• knowledge of ARIMA modelling of stationary and nonstationary time series
• knowledge of frequently used volatility models
• an understanding of problems arising when analyzing unit root processes
• the abilty to apply the knowledge on real world time series and forecast problems
• the ability to critically review and evaluate time series models and choose the best modelling approach
• an understanding of the use of time series models for forecasting and the limitations of the methods
• the ability to convey relevant aspects of modelling issues and results.
• the ability to use these models to analyze financial time series data.

Main content of the course

Econometrics, 7,5 Credits

• Basic concepts in econometrics: model, non-observable heterogeneity, endogeneity
• Simple and multiple linear regression using cross-sectional data
• Regression models for binary response
• Regression modelling for panel data
• Instrumental variables estimation.

Time Series Analysis and Forecasting, 7,5 Credits

• Basic concepts in time series analysis: stationarity, autocovariance, autocorrelation, partial autocorrelation.
• ARIMA modelling: Autoregressive models, moving average models, duality, model properties, parameter estimates, forecasts.
• Volatility models: ARCH and GARCH modelling, testing strategy for heteroscedastic models, volatility forecasts.
• Integrated processes: Difference stationarity, teting for unit roots, spurious correlation
• Multivariate time series: Time series regression, VAR models, cointegration, forecasting properties

Teaching methods

Teaching is done in the form of computer exercises and lectures.

Students who have been admitted to and registered on a course have the right to receive tuition and/or supervision for the duration of the time period specified for the particular course to which they were accepted (see, the university's admission regulations (in Swedish)). After that, the right to receive tuition and/or supervision expires.

Examination methods

Econometrics

Econometrics, Written Examination, 6 credits (Code: A001)
Individual written examination.

Econometrics, Computer Labs, 1.5 credits (Code: A002)
Written assignments.

Time Series Analysis and Forecasting

Time Series Analysis and Forecasting, Written Examination, 6 credits (Code: B001)
Individual written examination.

Time Series Analysis and Forecasting, Computer Labs, 1.5 credits (Code: B002)
Written individual assignments.

For students with a documented disability, the university may approve applications for adapted or other forms of examinations.

For further information, see the university's local examination regulations (in Swedish).

Grades

According to the Higher Education Ordinance, Chapter 6, Section 18, a grade is to be awarded on the completion of a course, unless otherwise prescribed by the university. The university may prescribe which grading system shall apply. The grade is to be determined by a teacher specifically appointed by the university (an examiner).

In accordance with university regulations regarding grading systems for first and second-cycle courses (Vice-Chancellor’s decision ORU 2018/00929), one of the following grades shall be used: Fail (U), Pass (G) or Pass with Distinction (VG). For courses that are included in an international Master’s programme (60 or 120 credits) or offered to the university’s incoming exchange students, the grading scale of A-F shall be used. The vice-chancellor, or a person appointed by the vice-chancellor, may decide on exceptions from this provision for a specific course, if there are special grounds.

Grades used on course are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Econometrics, Written Examination
Grades used are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Econometrics, Computer Labs
Grades used are Fail (U) or Pass (G).

Time Series Analysis and Forecasting, Written Examination
Grades used are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Time Series Analysis and Forecasting, Computer Labs
Grades used are Fail (U) or Pass (G).

For further information, see the university's local examination regulations (in Swedish).

Comments on grades

To obtain a passing grade for a subcourse (Econometrics; Time Series Analysis and Forecasting), a minimum of grade E is required on the written examination and a passing grade on the computer lab assignments. The grade on the subcourse is then awarded based on the written examination.

To obtain a passing grade for the course as a whole, a minimum of grade E is required for the both subcourses (Econometrics, Time Series Analysis and Forecasting). To arrive at the course grade, the grades awarded for subcourses, grades A-E, are first converted to the numerical values 5-1. An average value is then calculated and converted to the course grade.

Specific entry requirements

75 credits in Business Administration or Economics at basic level and 12 credits from Basic Statistics, 15 credits. In addition, 1.5 credits from Statistics, Regression Analysis, Basic Course, 7.5 credits or 7.5 credits in regression analysis / econometrics / scientific method in business administration, economics or statistics and English 6 / English B.

For further information, see the university's admission regulations (in Swedish).

Transfer of credits for previous studies

Students who have previously completed higher education or other activities are, in accordance with the Higher Education Ordinance, entitled to have these credited towards the current programme, providing that the previous studies or activities meet certain criteria.

For further information, see the university's local credit transfer regulations (in Swedish).

Reading list and other teaching materials

Econometrics, 7,5 Credits

Required Reading

Stock, James H. & Mark W. Watson, 2020, Global Edition, 4th Edition (latest edition)
Introduction to Econometrics
Pearson Education, 800 pages, approx 340 pages to be read

Time Series Analysis and Forecasting, 7,5 Credits

Required Reading

Becketti, Sean (2013)
Introduction to Time Series Using Stata
Stata Press, College Station, Texas, ISBN/ISSN: 978-1-59718-132-7, 443 pages, Chapters included: 3-10