A Boosting Approach for Automated Trading
Germán G. Creamer
Stevens Institute of Technology - Wesley J. Howe School of Technology Management
University of California, San Diego
Journal of Trading, Vol. 2, No. 3, pp. 84-96.
This paper describes an algorithm for short-term technical trading. The algorithm was tested in the context of the Penn-Lehman Automated Trading (PLAT) competition. The algorithm is based on three main ideas. The first idea is to use a combination of technical indicators to predict the daily trend of the stock, the combination is optimized using a boosting algorithm. The second idea is to use the constant rebalanced portfolios within the day in order to take advantage of market volatility without increasing risk. The third idea is to use limit orders rather than market orders in order to minimize transaction costs.
Number of Pages in PDF File: 10
Keywords: Automated trading, machine learning, algorithmic trading, boosting
JEL Classification: C49, C63, G24Accepted Paper Series
Date posted: October 17, 2006 ; Last revised: February 20, 2013
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