The Grid template

Lecture Information

Instructor:   Adam Bowers
Time:   3:00-3:50 pm (MWF)
Location:   CSB 002

[an error occurred while processing this directive]
TA Name Section Time (Friday) Location Office Hours
Jacob Robins A1 5 pm APM B402A Thursday 2:00-4:00 pm (APM 6446)
Haik Manukian A2 6 pm APM B402A Thursday 5:00-7:00 pm (APM 6446)
A3 7 pm


(30 Jan 2015) The midterm exam has been moved to Week 6. (Click here for the date.)
(14 Jan 2015) The midterm exam date is posted here.
(12 Jan 2015) Homework 1 is posted to Ted.

COURSE DESCRIPTION: This course provides an introduction to the mathematics of some financial models. The aim is to provide students with an introduction to some basic probabilistic models of finance and associated mathematical machinery. The course focuses largely on financial derivatives and related mathematics.

The course begins with the development of the basic ideas of hedging and pricing of derivatives in the discrete (i.e., discrete time and discrete state) setting of binomial tree models. The famous Black-Scholes option pricing formula is derived as a limit from these models. Then a general discrete finite market model is introduced, and the fundamental theorems of asset pricing are proved in this setting. Tools from probability such as conditional expectation, filtration, (super)martingale, equivalent martingale measure, and martingale representation are all introduced and used in this discrete setting.

This course requires a solid background in probability, preferably at the level of the undergraduate probability course Math 180A at UCSD. It also uses a certain amount of geometric linear algebra, so it is a good idea to review background from Math 20F.

The graduate course, Math 294, which has a similar title, is at a more advanced level and has much more emphasis on continuous time models which use measure theory.

RECOMMENDED TEXT: Introduction to the Mathematics of Finance, R. J. Williams, American Mathematical Society, 2006.
We will follow the first three chapters of this book.

F. AitSahlia and K. L. Chung, Elementary Probability Theory, Springer, Fourth Edition.
Capinski and Zastawniak, Mathematics for finance: an introduction to financial engineering, Springer, 2010.
S. Pliska, Introduction to Mathematical Finance, Blackwell, 1998.
V. Goodman and J. Stampfli, The Mathematics of Finance: Modeling and Hedging, AMS, 2001.

J. Cvitanic and F. Zapatero, Economics and Mathematics of Financial Markets, MIT Press, 2004.
T. S. Y. Ho and S. B. Lee, The Oxford Guide to Financial Modeling, Oxford, 2004.
J. Hull, Options, Futures and Other Derivative Securities, Prentice Hall.
S. Ross, An Introduction to Mathematical Finance, Options and Other Topics, Cambridge Univ. Press, 1999.
P. Wilmott et al., The Mathematics of Financial Derivatives, Cambridge University Press, 1995.
Incomplete Markets by Jeremy Staum, article in Handbooks in OR and MS, Vol. 15, 2008, Elsevier.

Linear algebra lectures by Gil Strang (MIT). You may find lecture 1, 9, 14 helpful in reviewing geometric aspects of linear algebra.



Course description, list of references, and other resources provided by Professor Ruth Williams.