Stochastic Processes for Finance

2018-2019

Course Objective

To learn basics of stochastic processes, including the concepts of
martingales and stochastic integration; apply these concepts to price
options on stocks and interest rates by the no-arbitrage principle.

Course Content

Financial institutions trade in risk, and it is therefore essential to
measure and control such risks. Financial instruments such as options,
swaps, forwards, etc. play an important role in risk management, and to
handle them one needs to be able to price them. This course gives an
introduction to the mathematical tools and theory behind risk
management.

A "stochastic process" is a collection of random variables, indexed by a
set T. In financial applications the elements of T model time, and T is
the set of natural numbers (discrete time), or an interval in the
positive real line (continuous time). "Martingales" are processes whose
increments over an interval in the future have zero expectation given
knowledge of the past history of the process. They play an important
role in financial calculus, because the price of an option (on a stock
or an interest rate) can be expressed as an expectation under a
so-called martingale measure. In this course we develop this theory in
discrete and continuous time. Most models for financial processes in
continuous time are based on a special Gaussian process, called Brownian
motion. We discuss some properties of this process and introduce
"stochastic integrals" with Brownian motion as the integrator. Financial
processes can next be modeled as solutions to "stochastic differential
equations". After developing these mathematical tools we turn to finance
by applying the concepts and results to the pricing of derivative
instruments. Foremost, we develop the theory of no-arbitrage pricing of
derivatives, which are basic tools for risk management.

Teaching Methods

Lectures and discussion of exercises

Method of Assessment

Assignments and written examination.

Entry Requirements

Probability (X_400622) and Analysis 1 (X_400005), or their equivalents.

Literature

Lecture notes

Additional literature:
Shreve, "Stochastic Calculus for Finance I: The Binomial Asset Pricing
Model", Springer;
Shreve, "Stochastic Calculus for Finance II: Continuous-time models",
Springer.

Target Audience

mBA, mBA-D, mMath, mSFM, master Econometrics.

Additional Information

A significant part of the course is used to introduce mathematical
subjects and techniques like Brownian motion, stochastic integration and
Ito calculus. In view of this, the course is NOT meant for students who
already followed the master course "Stochastic Integration" or
"Stochastic differential equations". On the other hand, after completing
this course, students may be motivated to follow other courses (like the
two mentioned above) where stochastic calculus is treated in a deeper
and more rigorous way.

Recommended background knowledge

Measure Theory.

General Information

Course Code X_400352
Credits 6 EC
Period P1+2
Course Level 400
Language of Tuition English
Faculty Faculty of Science
Course Coordinator dr. E.N. Belitser
Examiner dr. E.N. Belitser
Teaching Staff dr. E.N. Belitser

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Lecture
Target audiences

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