Current active subject description (last updated 2024/25)
Introductory Empirical Finance and Data Science
ECO2002
Current active subject description (last updated 2024/25)

Introductory Empirical Finance and Data Science

ECO2002
The course provides an introduction to ethics related to finance, reporting standards, portfolio analysis, as well as the basic methods needed to conduct such an analysis in practice. The course introduces the use of software and data processing, as well as how to write a report with the main results of a portfolio. The course lays a solid foundation for writing a longer assignment that utilizes quantitative methods. The course cover central topics in syllabus from the most acknowledged financial certification in finance, the Certified Financial Analyst (CFA).

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. 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. The students will also receive an introduction to the ethical standards required of investment professionals, and the commitment to place clients' interests first.

For students who can document that the exam for CFA Level 1 s passed, the course is voided.

Knowledge

The student..

  • Have broad knowledge of key issues and issues within the analysis of return and risk, and the appropriate methods for such analyses.
  • 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.
Paid semester fee and syllabus literature. It is also required that students have a laptop at their disposal.
Elective course
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.
The study programme is evaluated annually by students by way of course evaluation studies. These evaluations are included in the universitys quality assurance system.

All support materials allowed. Generating an answer using ChatGPT or similar artificial intelligence and submitting it wholly or partially as one's own answer is considered cheating.

MA205E Matemathical methods in economics

BE206E Corporate Finance,

Credits
7.5
Study location
Bodø
Responsible faculty
Nord University Business School
Course coordinator
Employee photo: Thomas Leirvik
Associate Professor

Thomas Leirvik

thomas.leirvik@nord.no