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.

LEARNING OUTCOMES

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.

Credits: 6

Schedule: 12.01.2022 - 21.02.2022

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Sean Shin

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content
  • valid for whole curriculum period:

    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
  • valid for whole curriculum period:

    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

Workload
  • valid for whole curriculum period:

    Classroom hours 24h
    Class preparation 40h
    Assignments/projects 60h
    Preparing Exam 34h
    Exam 2h

    Total 160h (6 op)

DETAILS

Study Material
  • valid for whole curriculum period:

    Readings, slides, and other materials will be provided by the lecturer through MyCourses.

Substitutes for Courses
Prerequisites
SDG: Sustainable Development Goals

    1 No Poverty

    8 Decent Work and Economic Growth

FURTHER INFORMATION

Further Information
  • valid for whole curriculum period:

    Teaching Period:

    2020-2021 Spring III

    2021-2022 Spring III


    Course Homepage: https://mycourses.aalto.fi/course/search.php?search=FIN-E0308


    Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.


    A maximum of 40 students can be accepted to the course.

    First priority are Finance M.Sc. programme students (i.e. who have graduated as B.Sc.) and CEMS students (those courses that have been designated as CEMS courses).

    Remaining seats are prioritized as follows, in the order of registration in WebOodi within one category:
    1. Finance M.Sc. exchange students from other universities
    2. Aalto Finance B.Sc. students with a finished B.Sc. thesis (registered in transcript of records)
    3. All other M.Sc. students at the School of Business


    Please follow carefully the registration deadlines of the courses and exams! Missing registration deadline automatically foregoes a guaranteed seat for Finance M.Sc. courses and puts prospective student at the bottom of the prioritization list.

    Students may be required to confirm their registration by signing the participation list circulated during the first lecture.