Course manual 2020/2021

Course content

Changing interest rates constitute one of the major risk sources for banks, insurance companies, and other financial institutions. Modeling the term-structure movements of interest rates is a challenging task. This course gives an introduction to the mathematics of term-structure models in continuous time. It includes practical aspects for fixed-income markets such as day-count conventions, duration of coupon-paying bonds and yield curve construction; arbitrage theory; short-rate models; the Heath-Jarrow-Morton methodology; consistent term-structure parametrizations; affine diffusion processes and option pricing with Fourier transform; LIBOR market models; and credit risk. The focus is on a mathematically straightforward but rigorous development of the theory.

Study materials

Literature

  • Damir Filipovic, 'Term-Structure Model', Springer, ISBN 978-3-540-09726-6

Objectives

  • To make the students familiar with interest rate models and the mathematics needed to construct and analyze them.

Teaching methods

  • Lecture
  • Self-study

The course is mainly theoretical.

Learning activities

Activity

Number of hours

Hoorcollege

32

Oral exam

1

Zelfstudie

133

Attendance

This programme does not have requirements concerning attendance (TER-B).

Assessment

Item and weight Details

Final grade

There will be an oral exam for each part of the course. Erik Winands will give an oral exam for the first part of the course. Misha van Beek will give an oral exam for the second part of the course. To have the exam, you make an appointment with the lecturers. 

The final grade will be a combination of the results of the take home assignments and the oral exam , i.e.,

Final-grade = Homework-grade*40% + exam-grade*60%.

To pass the exam the final grade should be equal to or higher than 5,6 AND the grade for the oral exam should be higher than 5,0.


The same applies in case of a resit. That is the final grade will be a combination of the results of the take home assignments (which counts 40 %)  and the resit grade (60%).

Inspection of assessed work

Contact the course coordinator to make an appointment for inspection.

Assignments

During the course, the students will have to hand in homework excercises. The average homework grade will count for 40% in the final grade.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

No.

Contents

Lecturer

Date

1

Lecture: Chapter 2 (Sections 2.1 - 2.4)

Erik Winands

Sep 4

2

Lecture: Chapter 2 (Sections 2.4 - 2.7)

Erik Winands

Sep 11

3

Lecture: Chapter 3 (Sections 3.1 - 3.2)

Erik Winands

Sep 18

4

No lecture

 

Deadline of first take home assignment (2.1, 2.3, 2.4, 2.8)

-

Sep 25

5

Lecture: Chapter 3 (Section 3.4)

Erik Winands

Oct 2

6

Lecture: Chapter 5 (Sections 5.1-5.4.1)

Erik Winands

Oct 9

7

Lecture: Chapter 5 (Section 5.4) and Chapter 12 (Sections 12.1-12.2)

 

 

Erik Winands

Oct 16

8

No lecture

 

Deadline of second take home assignment (Exercises 3.3,3.4,5.2,5.3)

-

Oct 23

9

Lecture: Chapter 6

 

 

Misha van Beek

Oct 30

10

Lecture: Chapter 6 / 7

 

Misha van Beek

Nov 7

11

No lecture

 

Deadline of the third  take home assignment

-

Nov 14

12

Lecture Chapter 7

Misha van Beek

Nov 21

13

Lecture: Chapter 10

 

 

Misha van Beek

Nov 28

14

Lecture: Chapter 10

 

Deadline of the fourth take home assignment

Misha van Beek

Dec 5

15

Questions

Misha van Beek

Erik Winands

Dec 12

Timetable

The schedule for this course is published on DataNose.

Additional information

Recommended prior knowledge: Measure theory, stochastic processes at the level of the course Measure Theoretic Probability, knowledge of stochastic integrals (key words: continuous time martingales, progressive processes, Girsanov transformation, stochastic differential equations) at the level of Stochastic Integration, knowledge of principles of financial mathematics, for instance at the level of Stochastic Processes for Finance.

Contact information

Coordinator

  • dr. ir. E.M.M. Winands

Staff

  • dr. ir. E.M.M. Winands