JSM 2005 Online Program

Abstract #304757

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	195
Type:	Contributed
Date/Time:	Monday, August 8, 2005 : 2:00 PM to 3:50 PM
Sponsor:	IMS
Abstract - #304757
Title:	A Comparison of Automated Investment Strategies
Author(s):	Alexander White*+ and Fotios Kokkotos
Companies:	American University and American University
Address:	Dept of Math and Stat, Washington, DC, 20016, United States
Keywords:	Geometric Brownian Motion ; Automated Investment ; Universal Portofolio
Abstract:	We could develop the ideal investment strategy if we could see tomorrow's prices today. While this is unattainable, Cover proposed as a reasonable target the wealth generated by the best constant rebalanced portfolio. This strategy peers into the future path of stock prices and chooses what would have been the best constant mix of stocks (i.e., If I were to hold a fixed percentage of my wealth in each of the stocks, which percentages would maximize my wealth?). This wealth is guaranteed to be greater than a buy-and-hold strategy in the best stock. In fact, in most markets, it is much greater. Two automated procedures, the universal portfolio and the exponentiatied gradient portfolio, have been shown to generate nearly the same wealth as the best constant rebalanced portfolio. The analysis of these methods has been paradoxical. While the worst-case bounds of performance are much better for the universal portfolio, the exponentiated gradient portfolio performs better with long series (> 30 years) of historical stock data.

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