Hanken Moodle

Moodle key: micro3_2026

Instructions here.

The course is intended as an introduction to time series models in econometrics. The first part of the course considers stationary linear time series model. The second part deals with multivariate time series models, unit roots, cointegration and volatility models. Empirical examples are mainly from Finance.

The course is intended for master's students in finance and economics with an interest in statistics and econometrics. The course can also be taken by doctoral students.

After completing the course, you will be able to:
Solve linear difference equations
Apply basic concepts from stochastic processes like stationarity and the autocovariance function to analyse time series
Analyse stationary linear time series models, fit the models to data and perform inference
Analyse non-stationary and cointegrated time series models, fit the models to data and perform inference
Analyse time series models with conditional heteroskedasticity, fit the models to data and perform inference
Perform statistical computations in R

Lecturer: Niklas Ahlgren
Teaching Assistant: Tatiana Terenteva

Exam dates: 10 March 9am to 11 March 8:59am (Part 1), 11 May 9am to 12 May 8:59am (Part 2 and whole course) and 11 June 9am to 12 June 8:59am.

The course is an introduction to multivariate analysis (i.e. statistical techniques that simultaneously analyse multiple measurements on individuals or objects). The course covers techniques such as MANOVA, Regression Analysis, Factor Analysis, and Cluster Analysis. The statistical program SPSS is used in the course.

Students with Statistics as their minor should take the course Multivariate Data Analysis (8 ECTS, course code 3613) in their bachelor's studies. That course is also recommended for students with a quantitative interest with other subjects as their major.

Kursen erbjuder en modern introduktion till ekonometrin med tyngdpunkten på ekonometriska metoder tillämpade på verkliga ekonomiska problem. Ekonometrin använder statistiska metoder för att undersöka ekonomiska frågeställningar. Ekonometri används på alla områden av empirisk ekonomi för att testa ekonomiska teorier, för ekonomiskt beslutfattande och för att prognosticera ekonomiska variabler. Metoderna som tas upp på kursen är motiverade av de problem som uppkommer vid analys av icke-experimentella ekonomiska data. På kursen behandlas huvudsakligen linjära regressionsmodeller för tvärsnittsdata.

The course covers multivariate techniques. Among the topics considered are:
(M)ANOVA, Multiple Regression, Principal Component Analysis, Factor Analysis, Cluster Analysis.
Course participants are supposed to acquire practical skills when it comes to using statistical software to perform such analyses.

Participants will also dissect and evaluate research reports/articles where multivariate analyses were applied. Articles are taken from the top journals in Marketing, Management, Supply Chain Management, Accounting, Finance and were published in the last five years.

Moodle self-enrollment key: please, check 'Messages' in SISU about one week before the start of the course.

The course covers a broad range of mathematical knowledge, techniques and tools
that are used in economic applications, and has a wealth of practice examples
integrated throughout, including software-based demonstrations.
Examples employed go beyond the basic level of mathematics
for economics and business.

Analytical and quantitative elements are implemented in software Python with
the aid of Markdown (generation of documents with text and code)
and Jupyter Notebook https://jupyter.org/.

Moodle self-enrollment key: Please, check messages in 'SISU' about one week before the start of the course.

On this course, we will study the digital economy and AI from a commercial perspective.

On this course, we will have a look at our digital economy through the lens of commercial law.