ELE 3911 Introduction to Quantitative Finance

ELE 3911 Introduction to Quantitative Finance

Course code: 
ELE 3911
Department: 
Finance
Credits: 
7.5
Course coordinator: 
Isaiah Hull
Course name in Norwegian: 
Introduction to Quantitative Finance
Product category: 
Bachelor
Portfolio: 
Bachelor - Programme Electives
Semester: 
2024 Autumn
Active status: 
Active
Level of study: 
Bachelor
Teaching language: 
English
Course type: 
One semester
Introduction

Quantitative finance is an exciting field where we apply mathematics, statistics, and computing to solve financial problems. The main finance areas where advanced quantitative techniques are applied are derivative securities (pricing and hedging), risk management, and portfolio management. This course introduces the fundamental mathematical and statistical tools of quantitative finance in a rigorous way and with applications. The core aims are the analysis of financial variables, the modeling of uncertainty and risk, and the building of market models for pricing and portfolio choices.

Learning outcomes - Knowledge

The students by the end of the course will know:

  • The fundamental probability theory and statistics underlying the modelling of uncertainty in finance
  • The fundamentals of matrix algebra and vector spaces as used for modelling multivariate structures or series
  • The theory of linear regression analysis
  • Models of financial time series
  • Market models and the notion of no arbitrage and replication
Learning outcomes - Skills

The students by the end of the course will be able to 

  • Model the time-value of money and analytically compute present and future values
  • Model uncertainty in financial markets using various models and approaches
  • Simulate univariate and multivariate financial time series using Monte Carlo simulations
  • Construct discrete-time market models for pricing derivative securities
General Competence

The students by the end of the course will be able to choose, analyze rigorously, and implement appropriate models of financial variables, depending on the problem at hand.

Course content

Subject to time constraints, the course will cover the following topics:

  1. A review of basic mathematics, including probability theory, statistics, linear algebra, and calculus.
  2. The time-value of money.
  3. Probability distributions.
  4. Bayesian analysis.
  5. Hypothesis testing.
  6. Linear algebra and vector spaces.
  7. Regression analysis.
  8. Time series models.
  9. Safe and risky assets.
  10. Discrete time market models.
Teaching and learning activities

The course contains lecturing, solving problems in class, online exercises, and a group project in R.

Software tools
R
Additional information

The course can be used as a preparation course for the Master's program.

Qualifications

Higher Education Entrance Qualification

Disclaimer

Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.

Required prerequisite knowledge

Basic courses in Mathematics, Statistics and Finance. 

Assessments
Assessments
Exam category: 
Submission
Form of assessment: 
Submission PDF
Exam/hand-in semester: 
First Semester
Weight: 
40
Grouping: 
Group/Individual (1 - 2)
Duration: 
1 Semester(s)
Comment: 
Assignment with data analysis and model implementation in R.
Exam code: 
ELE 39112
Grading scale: 
ECTS
Resit: 
Examination when next scheduled course
Exam category: 
School Exam
Form of assessment: 
Structured Test
Exam/hand-in semester: 
First Semester
Weight: 
60
Grouping: 
Individual
Support materials: 
  • BI-approved exam calculator
  • Simple calculator
  • Bilingual dictionary
Duration: 
4 Hour(s)
Comment: 
Individual final exam.
Exam code: 
ELE 39113
Grading scale: 
ECTS
Resit: 
Examination when next scheduled course
Type of Assessment: 
Ordinary examination
All exams must be passed to get a grade in this course.
Total weight: 
100
Student workload
ActivityDurationComment
Teaching
30 Hour(s)
Digital resources
15 Hour(s)
Student's own work with learning platform material
Student's own work with learning resources
100 Hour(s)
Group work / Assignments
51 Hour(s)
Examination
4 Hour(s)
Sum workload: 
200

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 7,5 ECTS credit corresponds to a workload of at least 200 hours.