Publication Date

Summer 2012

Document Type


Degree Name

Master of Science


Computer Science

First Advisor

Yun-Yau (Steve) Shih, Ph.D.

Second Advisor

Soon-Ok Park, Ph.D.

Third Advisor

Dingbang Xu, Ph.D.


In today’s world of high frequency trading and volatile markets, it is next to impossible for the average investor to make good decisions about where to put their money and for how long. There is a multitude of “hype” from many different directions including, television, magazine ads, internet searches, and emails. These companies usually sell computer programs to take the guess work out of it and do the thinking for you. They show successful results and it seems very promising. Unfortunately, most of these programs tend to come up short on their promises over the long run by having dismal results in the end. I believe this is because most trading systems are incomplete from the start. A complete trading strategy needs 3 things to be considered to be complete: A trigger to enter the trade, an exit trade management strategy that focusses on limited drawdown, and a money management system that focusses on preservation as well as equity growth. Instead, most trading strategies try to focus on being right all of the time rather than how to handle things when wrong. This research is about taking a general survey of what is currently out there, performing tests on them using various tools, and then comparing those results to the same tests with added trade and money management and analyzing the results for statistical significance. The intent of this research is to show that an “always correct” entry signal is simply not needed as long as a good trade management and money management model is also applied to a profitable system. Most systems only focus on the 1st part while ignoring the other 2 which then make it complete. Finally, a direction of areas of interest concerning future work will be discussed.


Student ID number has been redacted from the title page by OPUS staff.