Using Machine Learning Algorithms to Find Patterns in Stock Prices

We use a machine learning algorithm called Adaboost to find direction-of-change patterns for the Samp;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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Year of publication:	[2006]
Authors:	Rodriguez, Pedro N.
Other Persons:	Sosvilla-Rivero, Simon (contributor)
Publisher:	[2006]: [S.l.] : SSRN

Extent:	1 Online-Ressource (20 p)
Series:	FEDEA Working Paper ; No. 2006-12
Type of publication:	Book / Working Paper
Notes:	Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments October 25, 2006 erstellt
Other identifiers:	10.2139/ssrn.893141 [DOI]
Classification:	C45 - Neural Networks and Related Topics ; G11 - Portfolio Choice ; G14 - Information and Market Efficiency; Event Studies
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012733951