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, Principal Component Analysis, Factor Analysis, Discriminant Analysis, LOGIT, and Cluster Analysis. The statistical program SPSS is used in the course.

The course is built on the concept of cooperative learning in small teams.You will get a joint grade for the overall performance of your team.

The course provides the student with an introduction to advanced econometrics. The subjects include regression theory, estimation theory, probability, asymptotic theory, time series, volatility models and simulation methods in econometrics.

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

The course alternates and is given every other year. (Given in the Autumn 2017, not given in the Academic Year 2018-2019.)

AE course description 2017 23.8.2017.pdfAE course description 2017 23.8.2017.pdf

The course focuses on econometric models for financial data, in particular high-frequency and irregularly spaced data. The emphasis is on the analysis of data.
The course covers
- ARCH, GARCH and other volatility models;
- autoregressive conditional duration (ACD) and other models for the time between irregularly spaced financial events.

The course alternates and is given every other year (see Additional information).

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

Course key: FE2016

FE Course description 22.8.2016 latest.pdfFE Course description 22.8.2016 latest.pdfOutline_Hautsch updated 28.11.2016.pdfOutline_Hautsch updated 28.11.2016.pdf

Ekonomisk matematik fokuserar på användningen och nyttan av differential- och integralkalkyl för funktioner av en eller av flera variabler vid ekonomiska tillämpningar som t.ex. optimering av intäkts-, kostnads- eller vinstfunktioner.

Obligatorisk grundkurs inom kandidatexamen.

Kursnyckel: EMS2017.

Kursen 1112-1 EMS-del1: Ekonomisk matematik fokuserar på användningen och nyttan av differential- och integralkalkyl för funktioner av en eller av flera variabler vid ekonomiska tillämpningar som t ex optimering av intäkts-, kostnads- eller vinstfunktioner.

Kursbeskrivning.pdfKursbeskrivning.pdf

Kursen 1112-1 EMS-del1: Ekonomisk matematik fokuserar på användningen och nyttan av differential- och integralkalkyl för funktioner av en eller av flera variabler vid ekonomiska tillämpningar som t ex optimering av intäkts-, kostnads- eller vinstfunktioner.

Kursen 1112-2 EMS-2:Statistik omfattar grunderna i sannolikhetskalkyl och deskriptiv statistik, som förutsätts bl.a. i kursen 7777 Forsknings- och undersökningsmetodik (FUM)

Ekonomisk matematik fokuserar på användningen och nyttan av differential- och integralkalkyl för funktioner av en eller av flera variabler vid ekonomiska tillämpningar som t.ex. optimering av intäkts-, kostnads- eller vinstfunktioner.

Obligatorisk grundkurs inom kandidatexamen. Denna kurs ersätter den tidigare grundkursen 1112-1 EMS-matematik.

KursbeskrivningEkonmat2015.pdfKursbeskrivningEkonmat2015.pdf

The course is an introduction to multivariate analysis (i.e. statistical techniques that simultaneously analyse multiple measurements on individuals or objects). The course covers multivariate techniques such as MANOVA, Principal Component Analysis, Factor Analysis, Discriminant Analysis, LOGIT, and Cluster Analysis. The objective is to develop an understanding as well as a working knowledge of multivariate techniques. The statistical program SPSS is used in the course.

The course can be included in bachelor's studies by students with Statistics as their minor. The course can also be included as a methods course in master's or doctoral studies in other subjects than statistics.

MDA-syllabus15 new.pdfMDA-syllabus15 new.pdf

The course is an introduction to multivariate analysis (i.e. statistical techniques that simultaneously analyse multiple measurements on individuals or objects). The course covers multivariate techniques such as MANOVA, Principal Component Analysis, Factor Analysis, Discriminant Analysis, LOGIT, and Cluster Analysis. The objective is to develop an understanding as well as a working knowledge of multivariate techniques. The statistical program SPSS is used in the course.

The target group is non-statistic master's students and statistics bachelor's students.
The course can also be included as a methods course in doctoral studies in other subjects than statistics, subject to the approval of the student's supervisor.

MDA-syllabus spring term 2015.pdfMDA-syllabus spring term 2015.pdf

Estimation and Inference in Econometrics is a second course in econometrics. Part 1 of the course deals with estimation and inference in the linear regression model, least squares, generalised least squares and instrumental variables. Some results from matrix algebra are reviewed. Part 2 of the course provides an introduction to large-sample theory and maximum likelihood methods in econometrics. Some results from probability are reviewed.

Course key in Moodle: EIE17.

eie17.pdfeie17.pdf

The course introduces the student to time series models commonly used in econometrics. About half of the course is devoted to stationary ARMA models. The course then considers multivariate time series models, unit roots, cointegration, and ARCH and GARCH models. Examples are taken from financial economics.

The course alternates and is given every other year.

FUM-kursen ger en inblick i grundläggande statistisk undersökningsmetodik för insamling och analys av data. På kursen behandlas intervallestimering och hypetestest; bl.a. t-test, ANOVA, regressionsanalys och icke-parametriska test. Det statistiska programpaketet SPSS används under kursen.

FUMsyllabus2014.pdfFUMsyllabus2014.pdf

FUM-kursen ger en inblick i grundläggande statistisk undersökningsmetodik för insamling och analys av data. På kursen behandlas intervallestimering och hypotestest; bl.a. t-test, ANOVA, regressionsanalys och icke-parametriska test. Det statistiska programpaketet SPSS används under kursen.

FUMsyllabus2015.pdfFUMsyllabus2015.pdf