Using machine learning algorithms to find patterns in stock prices
AbstractWe 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.
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Bibliographic InfoPaper provided by FEDEA in its series Working Papers with number 2006-12.
Date of creation: Jun 2006
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NBER Working Papers
2168, National Bureau of Economic Research, Inc.
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