Syllabus

Title
6164 Convex Analysis for Finance and Economics
Instructors
Univ.Prof. Dipl.Wirtsch.-Math.Dr. Birgit Rudloff
Contact details
Type
PI SE
Weekly hours
2
Language of instruction
Englisch
Registration
02/05/16 to 02/26/16
Registration via LPIS
Notes to the course
Dates
Day Date Time Room
Wednesday 03/02/16 09:00 AM - 12:00 PM D4.0.047
Wednesday 03/09/16 09:00 AM - 12:00 PM D4.0.047
Wednesday 03/16/16 09:00 AM - 12:00 PM D4.0.047
Wednesday 04/06/16 09:00 AM - 12:00 PM D4.0.047
Wednesday 04/13/16 09:00 AM - 12:00 PM D4.0.047
Wednesday 04/20/16 09:00 AM - 12:00 PM D4.0.047
Wednesday 04/27/16 09:00 AM - 12:00 PM D4.0.047
Wednesday 05/04/16 09:00 AM - 12:00 PM D4.0.047

Contents

Tools from Convex Analysis, in particular duality methods, arise frequently in Mathematical Finance and Economics. In this course, we will review and motivate some basic concepts in Convex Analysis (Hahn-Banach theorem, biconjugation theorem, subdifferentials, Fenchel-Rockafellar duality theorem) on infinite dimensional spaces.

These tools are going to be applied to a special type of functions which frequently appears in Finance and Economics, in particular when it comes to pricing, risk evaluation or utility measurement. Examples are coherent and convex risk measures, no arbitrage price bounds, good deal bounds and optimized certainty equivalents, among many others. Duality concepts will be discussed and examples including risk measures, portfolio optimization, the Fundamental Theorem of Asset Pricing, hedging and capital/risk allocation problems will be studied. 

Learning outcomes

The students should become familiar with basic tools from infinite dimensional Convex Analysis and be able to apply them, in particular to problems in Economics and Financial Mathematics.

Teaching/learning method(s)

There will be classroom lectures and assignments for the participants. Lecture notes will be posted online.

Assessment

There will be homework assignments (30%), a minitest (15%) and a final (55%).

Availability of lecturer(s)

brudloff@wu.ac.at

Additional material on learn@WU

Lecture notes will be distributed during the course.
Last edited: 2016-02-23



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