Current active course description (last updated 2021/22)
Introductory Empirical Finance and Data Science
ECO2002
Current active course description (last updated 2021/22)
Introductory Empirical Finance and Data Science
ECO2002
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, 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.
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.
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:
BE202E - Data Science for Economics and Finance - 7.5 credits