Topic for Spring 2008: Computational Finance
Note: Enrollment in this course will be restricted.
Office hours by appointment.
Applications of computer science to the study of modern financial markets. Motivation of finance as a source of important, interesting problems. Introduction to major markets, asset classes and market data. Characterization of price movements: random walks, ``crashes'', ``momentum'', mean reversion, etc. Mathematical financial models. Study of modern artificial intelligence (AI) tools and their applications, not only in finance but also in other research areas. Scientific computer analysis of large-scale data corpora to investigate hypotheses in finance research. Examination of behavioral finance with respect to human and computer traders in markets. Applications of AI in derivative pricing, time series analysis and price prediction, risk analysis. Discussion of terabyte-scale and millisecond-response-time systems challenges associated with analysis and trading in modern financial markets. Market impact of trading; reasoning about other traders. Applications of cryptography in securities trading.
Students will choose a final project from open finance research questions, or instead build an automated trading agent with an interface to professional-grade trading software.
In addition to fundamental courses in mathematics (such as Math 21a,b, AM 21a,b, or equivalent), students should have either a strong background in computer science or in economics and finance. Those with a computer science background should have taken at least CS 124 (algorithms), and CS 182 or 181 (artificial intelligence) or equivalents. Those with a finance background should have taken Economics 1723 and 1760 and their prerequisites, or equivalents.
The draft syllabus (subject to minor changes) is here. There is also an HTML version. (These links open in a new tab or window).
Previous weeks' readings are archived on the CS286r Readings page.
You should understand what the following concepts mean, though you need not master the math/number theory behind them. We briefly summarize them in the first paper, but you might find Internet resources helpful in understanding the core concepts.
The readings to prepare for the 25 April 2008 lecture are as follows:
Homework 1 (due 7 Feb 2008, 11:59 pm)
Homework 2 (due 14 Feb 2008, 11:59 pm)
Homework 3 (due 25 Feb 2008, 11:59 pm)
Homework 5 (due 20 Mar 2008, 11:59 pm)
Project Proposal Guidelines (due 4 Apr 2008, 12:00 noon)
Homework 6 (due MONDAY, 28 Apr 2008, 11:59 pm)