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2020/2021  KAN-CCMVI2099U  Quantitative Investment Strategies

English Title
Quantitative Investment Strategies

Course information

Language English
Course ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration Summer
Start time of the course Summer
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 80
Study board
Study Board for MSc in Economics and Business Administration
Course coordinator
  • Sven Bislev - Department of Management, Society and Communication (MSC)
For academic questions related to the course, please contact instructors Mr. Asmund Belcaid at asmundbelcaid@yahoo.dk or
Miss Amanda Storm Jørgensen at amandastorm93@gmail.com
Other academic questions: contact Sven Bislev at sb.msc@cbs.dk
Main academic disciplines
  • Finance
  • Statistics and quantitative methods
Teaching methods
  • Online teaching
Last updated on 21/01/2021

Relevant links

Learning objectives
To achieve the grade 12, students should meet the following learning objectives with no or only minor mistakes or errors:
  • Understand conceptually the presented investment strategies that have been covered in class.
  • Use Python to design, calculate, and evaluate investment strategies.
  • Ability to manipulate, analyse and visualise large datasets in Python.
  • Ability to articulate why alternative risk premia exist for Value, Size, Quality and Momentum factors.
  • Analyse how strategies have performed based on performance (return, Sharpe ratio, Information ratio, Maximum drawdown) and risk measures (volatility, VaR, cVaR, coherent risk measures, Sortino ratio).
  • Identify and explain pitfalls, risks and limitations using financial and statistical measures.
  • Explain which agents are active in the financial market and to whom the strategies are suitable for.
Course prerequisites
The student should be familiar with basic statistical concepts such as standard deviation, normal distributions and linear regressions.
There are no prerequisites in Python nor other coding languages, but it will be advantageous for the student to have experience in some coding.
Quantitative Investment Strategies:
Exam ECTS 7.5
Examination form Home assignment - written product
Individual or group exam Individual exam
Size of written product Max. 15 pages
Assignment type Project
Duration Written product to be submitted on specified date and time.
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Summer, Ordinary exam: Home Assignment: 22 June-30 July 2021. Please note that exam will start on the first teaching day and will run in parallel with the course.
Retake exam: Home Assignment: 72-hour home assignment: 27-30 September 2021 – for all ISUP courses simultaneously
3rd attempt (2nd retake) exam: 72-hour home assignment: 22–25 November 2021 – for all ISUP courses simultaneously

Exam schedules available on https:/​/​www.cbs.dk/​uddannelse/​international-summer-university-programme-isup/​courses-and-exams
Make-up exam/re-exam
Same examination form as the ordinary exam
Retake exam: 72-hour home project assignment, max. 10 pages, new exam question.
Exam for for 3rd attempt (2nd retake): 72-hour home project assignment, max. 10 pages, new exam question.
Course content, structure and pedagogical approach

Course content:

The course is designed to teach students to understand, build, and evaluate quantitative investment strategies.

The lectures are structured to present a theoretical framework followed by practical examples in Python with the aim to apply the theory in practice.

It is not expected that the student has prior knowledge in Python, but experience in any coding language is a plus. There will be optional preliminary home exercises in Python, designed to quickly grasp and be familiar with the basics of Python. 
The course will be useful for students planning a career within the financial industry, whether it is portfolio management, quantitative research, trading, risk management or data analytics. 

Course structure:

Preliminary assignment: Download and install Python. We will provide basic and non-graded exercises to be solved in Python.

Class 1: Introduction + Python setup and exercises 
Class 2: Fama French three factor model + Python exercises 
Class 3: Momentum and quality + Python exercises 
Class 4: Portfolio Construction + Python exercises 
Class 5: Performance measurement and attributions + Python exercises 
Class 6: VaR and investment risk + Python exercises Feedback Activity 
Class 7: Combining quantitative factors into one strategy 
Class 8: Signaling and timing strategies 
Class 9: Market participants and how to trade and finance a strategy 
Class 10: Case study 
Class 11: Case study


Description of the teaching methods
This year all courses are taught digitally over the Internet. Instructors will apply direct/live teaching through a link (like Skype, Team, Zoom). In some courses, pre-recorded material will also be used.
Feedback during the teaching period
We will provide the students with time during class 6 to fill in the feedback questionnaire. Their responses will be taking very seriously and we will adjust the following classes accordingly.
Student workload
Preliminary assignment 20 hours
Classroom attendance 33 hours
Preparation 126 hours
Feedback activity 7 hours
Examination 20 hours
Further Information

Preliminary Assignment: To help students get maximum vlaue from ISUP courses, instructors provide a reading or a small number of readings or video clips to be read or viewed before the start of classes with a related task scheduled for class 1 in order to "jump-start" the learning process.


Course timetable is available on https://www.cbs.dk/uddannelse/international-summer-university-programme-isup/courses-and-exams


We reserve the right to cancel the course if we do not get enough applicaitons. This will be communicated on https://www.cbs.dk/uddannelse/international-summer-university-programme-isup/courses-and-exams in March 2021.

Expected literature

Mandatory readings:


Jorion, Philippe (2006) “ Value at Risk: The New Benchmark for 
Managing Financial Risk” , Third edition, chapter 5
Womack, Zhang, Borchert, Ensz, Knijn, Pope, Smith (2003) “
Understanding Risk and Return, the CAPM, and the Fama-French  Three-Factor Model     ”


Additional relevant readings:


Asness, Clifford (1997) “ The Interaction of Value and Momentum




Jorion, Philippe (2006) “ Value at Risk: The New Benchmark for


Managing Financial Risk” , Third edition, chapter 6 and 7


This is a constantly developing field so the reading list can change if relevant articles are published.  


Last updated on 21/01/2021