Economics, Financial Econometrics, Second Cycle, 15 credits

Learning outcomes

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.

Content

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

Examinations and grades

Econometrics

Econometrics, Written Examination, 6 credits (Code: A001)
Grades used are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Econometrics, Computer Labs, 1.5 credits (Code: A002)
Grades used are Fail (U) or Pass (G).

Time Series Analysis and Forecasting

Time Series Analysis and Forecasting, Written Examination, 6 credits (Code: B001)
Grades used are Fail (F), Sufficient (E), Satisfactory (D), Good (C), Very Good (B) or Excellent (A).

Time Series Analysis and Forecasting, Computer Labs, 1.5 credits (Code: B002)
Grades used are Fail (U) or Pass (G).

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 determine which grading system is to be used. The grade must be determined by a teacher specifically nominated by the university (the examiner).

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

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

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.

Modes of assessment

Econometrics
Written Examination, 6 credits (Code: A001)
Computer Labs, 1.5 credits (Code: A002)

Time Series Analysis and Forecasting
Written Examination, 6 credits (Code: B001)
Computer Labs, 1.5 credits (Code: B002)

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

For further information, see the university's local examination regulations.

Specific entry requirements

75 credits in Business Administration or Economics at basic level and
12 credits on the course Basic Statistics, 15 credits and 3 credits on the course Data Mining and Business Analytics, Basic Course
alternatively
12 credits on the course Basic Statistics, 15 Credits and 1.5 credits on the course Statistics, Regression Analysis, Basic Course, 7.5 Credits. and English 6 / English B.

For further information, see the university's admission regulations.

Other provisions

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.

Reading list and other learning resources

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