GRA 6535 Derivatives

GRA 6535 Derivatives

Course code: 
GRA 6535
Department: 
Finance
Credits: 
6
Course coordinator: 
Tong Zhang
Course name in Norwegian: 
Derivatives
Product category: 
Master
Portfolio: 
MSc in Finance
Semester: 
2021 Autumn
Active status: 
Active
Level of study: 
Master
Teaching language: 
English
Course type: 
One semester
Introduction

This course provides a thorough understanding of the workings and pricing of derivative securities.

We cover model-free no-arbitrage bounds for derivatives prices, the binomial model and its continuous time limit, the mathematics of continuous time, the Black-Scholes model and its derivation, adjusting the Black-Scholes and binomial models to price futures and currency options, delta hedging and other hedging techniques, exotic derivatives, real options, credit risk, etc. A significant part of the course focuses on the numerical valuation of options.

Learning outcomes - Knowledge

By the end of the course the students are expected to know:

  • model-free, binomial, and Black-Scholes pricing of options
  • hedging of options
Learning outcomes - Skills

By the end of the course the students are expected to be able to:

  • value standard and exotic options using formulas or simple trees
  • code up option pricing models as trees or us Monte Carlo
General Competence

The students by the end of the course are expected to be able to understand the workings and limitations of option pricing theory.

Course content

1. Introduction

  • Options markets
  • Model-free no-arbitrage bounds
  • Trading strategies with options

2. Pricing

  • Binomial trees
  • Wiener processes, Ito's lemma, Black-Scholes-Merton and beyond
  • The Greeks

3. Numerical Methods and Applications

  • Empirical performance of option pricing models, volatility smiles
  • Numerical techniques, exotic options
  • Real options, credit Risk
  • International derivatives markets
Teaching and learning activities

Mostly lectures with theory, examples, in-class discussion, and exercises.

Software tools
R
Additional information

Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class.

This is a course with continuous assessment (several exam components) and one final exam code. Each exam component is graded by using points on a scale from 0-100. The components will be weighted together according to the information in the course description in order to calculate the final letter grade for the examination code (course). Students who fail to participate in one/some/all exam elements will get a lower grade or may fail the course. You will find detailed information about the point system and the cut off points with reference to the letter grades when the course starts.

At resit, all exam components must, as a main rule, be retaken during next scheduled course.

Honour Code

Academic honesty and trust are important to all of us as individuals, and represent values that are encouraged and promoted by the honour code system. This is a most significant university tradition. Students are responsible for familiarizing themselves with the ideals of the honour code system, to which the faculty are also deeply committed.

Any violation of the honour code will be dealt with in accordance with BI’s procedures for cheating. These issues are a serious matter to everyone associated with the programs at BI and are at the heart of the honour code and academic integrity. If you have any questions about your responsibilities under the honour code, please ask.

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 spesific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.

Covid-19 

Due to the Covid-19 pandemic, there may be deviations in teaching and learning activities as well as exams, compared with what is described in this course description.

Teaching 

Information about what is taught on campus and other digital forms will be presented with the lecture plan before the start of the course each semester.

Required prerequisite knowledge

College-level calculus (limit, differentiation, integration, Taylor expansion, etc), probability theory (cdf and pdf, common distributions, expectation, variance, etc), and basic knowledge in R (matrix indexation, basic operations, loop, if, plot, etc).

Assessments
Assessments
Exam category: 
Submission
Form of assessment: 
Written submission
Weight: 
20
Grouping: 
Group (2 - 3)
Duration: 
48 Hour(s)
Comment: 
Take-home examination
Exam code: 
GRA65353
Grading scale: 
Point scale leading to ECTS letter grade
Resit: 
All components must, as a main rule, be retaken during next scheduled course
Exam category: 
Submission
Form of assessment: 
Written submission
Invigilation
Weight: 
80
Grouping: 
Individual
Support materials: 
  • Bilingual dictionary
Duration: 
3 Hour(s)
Comment: 
Written examination under supervision.
Exam code: 
GRA65353
Grading scale: 
Point scale leading to ECTS letter grade
Resit: 
All components must, as a main rule, be retaken during next scheduled course
Type of Assessment: 
Continuous assessment
Grading scale: 
ECTS
Total weight: 
100
Sum workload: 
0

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.