Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.
By the end of the course students, students will be familiar with basic quantitative methods used for analyzing financial data and the empirical asset pricing literature; be able to implement those skills in the context of potential applications for portfolio construction using a programming language. Also, students will be faimiliar with basic concepts of machine learning and its applications to quantitative finance.
Schedule: 13.01.2021 - 22.02.2021
Teacher in charge (valid 01.08.2020-31.07.2022): Sean Shin
Teacher in charge (applies in this implementation): Sean Shin
Contact information for the course (applies in this implementation):
CEFR level (applies in this implementation):
Language of instruction and studies (valid 01.08.2020-31.07.2022):
Teaching language: English
Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
This course covers basic quantitative skills for analyzing financial data. This course also reviews basic academic papers related to empirical topics, such as behaviors of securities prices relative to the benchmark asset pricing models.
Details of assignments will be provided by the lecturer through MyCourses.
Assessment Methods and Criteria
The final grade (0 5 scale) is based on total points (max 100 points); combining assignments (50 %) and exam (50 %) points. To pass the course, you have to get at least 40% of exam points, i.e. 20 points. Conditional on that, your final grade is based on the following scale:
90 x 100: Final grade = 5
80 x<90: Final grade = 4
70 x<80: Final grade = 3
60 x<70: Final grade = 2
50 x<60: Final grade = 1
0 x<50: Final grade = 0, Fail
Classroom hours 24h
Class preparation 40h
Preparing Exam 34h
Total 160h (6 op)
Readings, slides, and other materials will be provided by the lecturer through MyCourses.
Substitutes for Courses
Substitutes a course 28E35600 Quantitative Finance
Rahoituksen perusteet or Principles of Corporate Financial Management,
Investment Management (28C00300) and Econometrics for Finance (28C00200), or equivalent courses.
SDG: Sustainable Development Goals
1 No Poverty
8 Decent Work and Economic Growth
- Opettaja: Sean Shin