Using Machine Learning Algorithms to Find Patterns in Stock Prices
FEDEA Working Paper No. 2006-12
20 Pages Posted: 27 Mar 2006
Date Written: October 25, 2006
We use a machine learning algorithm called Adaboost to find direction-of-change patterns for the S&P 500 index using daily prices from 1962 to 2004. The patterns are able to identify periods to take long and short positions in the index. This result, however, can largely be explained by first-order serial correlation in stock index returns.
Keywords: Direction-of-change predictability, Machine learning algorithms, Adaboost
JEL Classification: C45, G11, G14
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