Syllabus

LEARNING OUTCOMES

Credits: 6

Schedule: 27.02.2020 - 08.04.2020

Teacher in charge (valid 01.08.2020-31.07.2022):

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

Contact information for the course (valid 23.01.2020-21.12.2112):

Feel free to ask any questions via email.

CEFR level (applies in this implementation):

Language of instruction and studies (valid 01.08.2020-31.07.2022):

English

CONTENT, ASSESSMENT AND WORKLOAD

Content

• Valid 01.08.2020-31.07.2022:

  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.

• Applies in this implementation:

  The following contents are tentative and subject to change as needed:

  #1. Course Orientation and Introduction. 

   

  #2. Evaluating asset returns: Time-Series vs. Cross-sectional tests.

  #3. Value Investing. 

  #4. Momentum Investing. 

  #5. Quality Investing, Betting against Beta, and Q-factor Model 

  #6. Group Presentation: Key Paper and Project Execution Plan

  #7. Factor Investing: is it robust?  

  #8. Investing Other Asset Market: Fixed Income Markets   

  #9. Big Data and Machine Learning in Finance Research

  #10. Big Data and Machine Learning in Finance Research (cont.)

  #11. Final Group Presentation 1

  #12. Final Group Presentation 2

   

   

Assessment Methods and Criteria

• Valid 01.08.2020-31.07.2022:

  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

• Applies in this implementation:

   

  Individual Assignment (15%)

  Group Works (35%)

  Exam (50%)

   

   

Workload

• Valid 01.08.2020-31.07.2022:

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

  Total 160h (6 op)

• Applies in this implementation:

  -

DETAILS

Study Material

• Valid 01.08.2020-31.07.2022:

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

• Applies in this implementation:

  -

Prerequisites

• Valid 01.08.2020-31.07.2022:

  Investment Management (28C00300) and Econometrics for Finance (28C00200), or equivalent courses.

Registration for Courses

• Valid 01.08.2020-31.07.2022:

  The course registration is done via WebOodi and closes always 7 days before the first lecture/ start of the teaching period. The study coordinator will check the registrations first and then discuss with the lecturer and provide the lists. We have student quotas for our M.Sc. level courses and we use prioritization list.

• Applies in this implementation:

  -

FURTHER INFORMATION

Further Information

• Valid 01.08.2020-31.07.2022:

  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
  
  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.

• Applies in this implementation:

  -

Details on the schedule

• Applies in this implementation:

  This will be announced during the first class.