Portfolio theory
2018-2019
NWI-WB090, NWI-WM990B

Contents

In this course we treat the foundations of mathematical finance, its fundamental concepts like arbitrage, equivalent martingale measures, and fundamental economic notions as preference relations and utility functions and show how these are applied in portfolio optimization. This will be done first for static markets and extended later on to a dynamic setting, where time is discrete. Finally we will show how stochastic control theory and dynamic programming can be applied to problems of portfolio optimization.

Aim and objectives

The general aim is to make students familiar with the mathematical foundations of mathematical finance in discrete time and the fundamentals of portfolio selection. Specific objectives to be met at the end of the course:
1. Students are familiar with fundamental concepts of financial mathematics and know how to apply them.
2. Students know the theory behind portfolio optimization and know how to solve such optimisation problems.
3. Students are able to optimize under order restrictions.
4. Students are able to prove a number of well selected theorems.
5. Students know how to apply dynamic programming to investment-consumption problems.

Prerequisites

Basic concepts of probability and measure theory, for instance at the level of Measure theoretic probability (used for the Mastermath course with the same name).

Literature

The course is mainly based on H. Föllmer and A. Schied, Stochastic Finance, An Introduction in Discrete Time and on S.R. Pliska, Introduction to Mathematical Finance: Discrete Time Models. A set of lecture notes also containing the exercises will be the main source for this course.

Examination

Take home exercises (compulsory!) and oral exam. Deadlines for homework: solutions have to be handed in within one week! Oral exams: before the start of the summer holidays, selected dates will be published later. What do you have to know? The theory, i.e. all important definitions and results (lemma's, theorems, etc.). You also have to know three or four theorems together with their proofs. You select your favourite ones! Criteria to consider: they should be interesting, non-trivial and explainable in a reasonably short time span. Selected exam dates are June 6, (a part of 19), 26 and 28. July offers ample opportunities, but my holiday (July 23 - August 20) doesn't. See below for the schedule (you can always swap with a fellow student, but let me know in such a case).

June 6: 14:00 Jasper
June 19: 11:00 Luc
June 26: 11:00 Amber
June 26: 12:00 Oscar
June 26: 13:30 Paul
June 26: 15:00 Laurens
June 26: 16:00

People

Lectures by Peter Spreij.
Tutorials by Bob Driessen.

General schedule

Spring semester. Lectures mostly on Wednesdays in HG03.632, 10:30 - 12:15, first lecture on January 30, 2019. No lectures on March 20, 27, April 3, May 1; Tutorial of Feb 22 moved to Feb 21, 13:30 - 15:15 in HFML0220. Tutorials mostly on Fridays, 13:30 - 15:15, in HG00.062. First tutorial on February 1, 2019. Sometimes lectures and tutorials are swapped, see the precise schedule below, also for possible further changes.

Precise schedule

Lecture 1: Wed Jan 30 Tutorial 1: Fri Feb 1
Lecture 2: Wed Feb 6 Tutorial 2: Wed Feb 13
Lecture 3: Fri Feb 8 Tutorial 3: Fri Feb 15
Lecture 4: Wed Feb 20 Tutorial 4: Thu Feb 21, 13:30 in HFML0220
Lecture 5: Wed Feb 27 Tutorial 5: Fri Mar 1
Lecture 6: Wed Mar 6 Tutorial 6: Wed Mar 13
Lecture 7: Fri Mar 8 Tutorial 7: Fri Mar 15
Lecture 8: Wed Apr 10 Tutorial 8: Fri Apr 12
Lecture 9: Wed Apr 17 Tutorial 9: Fri Apr 26(!)
Lecture 10: Wed Apr 24 Tutorial 10: Fri Apr 26
Lecture 11: Wed May 8 Tutorial 11: Fri May 10
Lecture 12: Wed May 15 Tutorial 12: Fri May 17
Lecture 13: Wed May 22 Tutorial 13: Fri May 24

Updated Programme
(regularly updated, )

1
Class: A super crash course in measure theory at the start. Then Sections 1.1, 1.2 up to Theorem 1.12 (with partial proof).
Tutorial: Make Exercise 1.3 and 1.15 (for this you have to read section A.1; this exercise is the same as Exercise A.1).
Homework: Read in the lecture notes also the parts before Theorem 1.12 that I skipped. Make Exercises 1.1 and 1.8.
2
Class: Section 1.2 from Definition 1.13, Section 1.3 and a very brief intro to Sections 2.1, 2.2.
Tutorial: Make Exercises 1.2 and 1.5.
Homework: Make Exercise 1.4 and 1.11.
3
Class: Most of Sections 2.1, 2.2 (you can read Proposition 2.10 yourself, optional).
Tutorial: Make Exercises 2.2, 2.3, 2.6.
Homework: Make Exercises 2.1, 2.8, 2.9. [If you really like: In the proof of Theorem 2.12 it is tacitly assumed that the order dense subset is infinite. Show that a finite dense subset cannot exist.]
4
Class: Most of Section 3.1.
Tutorial: Make Exercises 3.4, 3.5, 3.6.
Homework: Make Exercises 3.1, 3.3.
5
Class: Sections 4.1 and Section 4.2.
Tutorial: Make Exercises 4.1, 4.6 and 4.7.
Homework: Make Exercises 3.2 (read carefully the text pertaining to Corolllary 3.10 and keep the argumentation short by referring to Theorem 3.9 where useful), 4.2 and 4.3.
6
Class: Sections 5.1, 5.2
Tutorial: Make Exercises 5.2 and 5.5.
Homework: Make Exercises 5.3 and 5.4.
7
Class: Section 6.1
Tutorial: Make Exercises 6.3, 6.6 and 6.7.
Homework: Make Exercises 6.1 and 6.4.
8
Class: Sections 6.2, 7.1
Tutorial: Make Exercises 7.1, 7.3 (and 7.4 if there is enough time).
Homework: Make Exercises 6.5 (actually this exercise belongs to week 7 and 6.4 to this week), 6.9 and 7.5.
9
Class: Sections 7.2, 8.1. You may have a look at the MTP lecture notes for some elementary properties of quantile functions (around Theorem 3.10), used in today's lecture.
Tutorial (on Friday 26 April!): Make Exercises 7.7, 7.10.
Homework: Make Exercises 7.8, 7.9.
10
Class: From Section 8.2: Theorem 8.9 (with partial proofs), Theorem 8.12. From Section 8.3: Lemmas 8.16, 8.17, mentioning of Lemmas 8.19 and 8.20, Proposition 8.21; Lemma 8.22.
Tutorial: Make Exercises 8.2, (read the proof of Lemma 8.19 and make) 8.11, 8.14.
Homework: Make Exercises 8.1, 8.3 (it is sufficient to give a relation between $\mu$ and $\sigma^2$).
11
Class: Remaining parts of Section 8.3, most of Section 8.4, from Section 8.5 the first part of Theorem 8.32 and quick mentioning of Section 8.6.
Tutorial: Make Exercises 8.4, 8.5, 8.13.
Homework: Read Section 8.6 (and check also that the CRR model satisfies the assertion of Theorem 8.32 about atoms) and make Exercises 8.7, 8.8.
12
Class: Most of Section 9.1 (and Appendix A.5) and the beginning of Section 9.2.
Tutorial: Make Exercises 9.1, 9.2 and 9.5 (for which you need to read the first one and a half page of Section 9.2).
Homework: Make Exercises 9.4 and A.2 (from the Appendix).
13
Class: Section 9.3.
Tutorial: Make Exercises 9.6, 9.7.
Homework: No exercises, but it could be useful to have a look at Appendix B of the updated lecture notes for a concise review of measure and probability theory. There are more (mostly minor) changes, which may have resulted in a different numbering.

OLD Programme




Links

Institute for Mathematics, Astrophysics and Particle Physics
Korteweg-de Vries Institute for Mathematics
Master Stochastics and Financial Mathematics