GRA 6557 Internship for MSc in Quantitative Finance +1 model

GRA 6557 Internship for MSc in Quantitative Finance +1 model

Course code: 
GRA 6557
Department: 
Finance
Credits: 
18
Program of study: 
Master of Science in Quantitative Finance
Course coordinator: 
Costas Xiouros
Product category: 
Master
Portfolio: 
MSc in Quantitative Finance
Semester: 
2020 Spring
Active status: 
Active
Teaching language: 
English
Course type: 
One semester
Introduction

This course, Internship for MSc in Quantitative Finance (18 ECTS), is part of the +1 Model for Msc in Quantitative Finance.

The internship is an opportunity to work at a company during your studies and gain professional experience. This is particularly important for a programme like quantitative finance, an area in which companies have developed state-of-the-art technology and analytical tools for many relevant finance problems. The internship will give you valuable insights in real-world challenges, and should help you in applying your academic background toward increasing organizational effectiveness and growth.

Learning outcomes - Knowledge

At the end of the internship, the student should know the specific challenges faced by companies in using quantitative finance tools and methods to create value, both for the company and for its relevant stakeholders.

The overall goal of the internship is to increase the employability of the students. More specifically, at the end of the internship, the student should have acquired an understanding of:

  • the practical issues and dilemmas faced by companies or departments operating in the quantitative finance industry
  • the data value chain and how it can be used to develop a competitive advantage
  • the implications of using data and models in decision-making for the company’s data infrastructure and organizational culture and structure, and
  • the time and efficiency constraints imposed by competition
Learning outcomes - Skills

The student at the end of the internship is expected to acquire skills in relation to:

  • career management and job seeking
  • defining and executing tasks under conditions of uncertainty, change and time pressure
  • supporting suggestions for practical solutions with sound argumentation and grounded in superior analytics and modelling
  • applying theoretical and technical knowledge to specific tasks and problems, and
  • collaborating and working in teams
General Competence

The student should reflect on the complexity of the work environment, the market forces that drive businesses and how companies create value based on analytics in view of new opportunities, innovation and growth.

Course content

Students will work in groups from 1-3 either 100% for 12 weeks or 80% for 15 weeks (450-500 hours) in a selected company and the quantitative finance-related tasks are assigned by the company. The company should be in business for at least 3 years, have 5 or more employees, and a turnover of NOK 5 million or more. Students must attend work as agreed upon with the company they are assigned to. Students are obliged to attend a compulsory CV/application/interview workshop before finding their internship. Each student is entitled to a maximum of 3 hours of supervision. Part of the supervision is a mandatory follow-up meeting with the academic supervisor (and other internship students) half-way the semester.

As part of this course, it is compulsory to participate in an employability course. 

The internship may be paid or unpaid.

Teaching and learning activities

Software tools: The required computer-based tools depend on the type of position the student will be working in. These requirements will be communicated by the employer in the position announcements.

Software tools
Software defined under the section "Teaching and learning activities".
Additional information

Both parts of the examination must be passed in order to receive a final grade in the course.

Qualifications

All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.

Exam categoryWeightInvigilationDurationGroupingComment exam
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
GRA65571
Grading scale:
Pass/fail
Grading rules:
-
Resit:
Examination next semester, thereafter when next scheduled course
50No2 Week(s)Individual Report. Students submit a company evaluation together with their paper.
Exam category:
Activity
Form of assessment:
Oral examination
Exam code:
GRA65572
Grading scale:
Pass/fail
Grading rules:
Internal and external examiner
Resit:
Examination next semester, thereafter when next scheduled course
50No 45 Minute(s)Individual Oral examination
Exams:
Exam category:Submission
Form of assessment:Written submission
Weight:50
Invigilation:No
Grouping (size):Individual
Duration:2 Week(s)
Comment:Report. Students submit a company evaluation together with their paper.
Exam code:GRA65571
Grading scale:Pass/fail
Resit:Examination next semester, thereafter when next scheduled course
Exam category:Activity
Form of assessment:Oral examination
Weight:50
Invigilation:No
Grouping (size):Individual
Duration: 45 Minute(s)
Comment:Oral examination
Exam code:GRA65572
Grading scale:Pass/fail
Resit:Examination next semester, thereafter when next scheduled course
Type of Assessment: 
Ordinary examination
Total weight: 
100
Sum workload: 
0

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore acourse of 18 ECTS credit corresponds to a workload of at least 480 hours.