Current active course description (last updated 2019/20)
Data Science for Economics and Finance
BE202E
Current active course description (last updated 2019/20)

Data Science for Economics and Finance

BE202E
This course provides a thorough introduction to computational economics and finance. You will learn how to use software to analyze financial data, estimating statistical models, and simulate observations. The course will apply a free statistical software, which can be downloaded via your web browser. You will learn to use statistical models to assess whether observations are normally distributed, methods to carry out hypothesis testing, and statistical inference. Students will also learn the basics of resampling methods, and how to apply this to various economic and financial problems. Students will also be able to determine optimal portfolios and investments with factor models.

Knowledge

The student..

  • Have broad knowledge of key issues and issues within the analysis of return and risk
  • Have knowledge of research and development in portfolio analysis and investment strategies
  • Can update their knowledge in topics related to statistical analysis of different investment strategies
  • Have knowledge of important findings in topics related to investment and risk, as well as traditions and how recent research questions fundamental assumptions in traditional models

Skills

  • Can apply professional knowledge and relevant results within investment analysis to issues related to topics in the subject
  • Can reflect on your own professional practice and adjust it under supervision
  • Can find, evaluate and refer to relevant subjects and produce this so that it highlights a problem related to investment analysis

General competence

The student should ...

  • Have insight into relevant issues related to investment analysis
  • Can plan and implement varied work tasks and projects that extend over time, alone or in groups, in line with ethical requirements and guidelines
  • Communicate central subjects such as theories, issues and solutions both in writing and verbally
  • Can exchange views and experiences with other people with a background in financial economics
  • Is familiar with innovation and innovation processes related to investment analysis
No tuition fees. Semester fees and cost of course literature apply.
Elective
Lectures with active and extensive use of computers and software. Online resources, such as courses offered through datacamp.com, is widely used throughout the course.
Evaluation using mid-term and final surveys. Students are also encouraged to participate in the central quality surveys.

Due to the Covid-19 epedemic, a number of assessments and exams at Nord University has been changed.

Changes are made in accordance with the Temporary Regulations on Supplements to Regulation 31/01/2019 no. 63: Concerning Studies and Examinations at Nord University - Extraordinary Measures as a Result of the Coronavirus Epidemic- according to §2 of the Corona Epidemic, Assessment Methods, Sections 1-3

To accommodate this, the form of assessment will be changed from Written School examination to Take -home Examination on this course in the spring of 2020.

Pencil, pen, ruler, financial calculator, dictionary

MA205E Matemathical methods in economics

BE206E Corporate Finance,

Overlap refers to a similarity between courses with the same content. Therefore, you will receive the following reduction in credits if you have taken the courses listed below:

ECO2002 - Introductory Empirical Finance and Data Science - 7.5 credits

Choose start semester
Curriculum literature
Leganto
Credits
10
Study location
Bodø
Responsible faculty
Nord University Business School
Course coordinator
Information about the course coordinator for the selected semester is no longer available. Please contact the current course coordinator.