Entropy rate and profitability of technical analysis: experiments on the NYSE US 100 stocks

Nicolas Navet 1 Shu-Heng Chen 2
1 TRIO - Real time and interoperability
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
2 AI-ECON Research Center
Abstract : The entropy rate of a dynamic process measures the uncertainty that remains in the next information produced by the process given complete knowledge of the past. It is thus a natural measure of the difficulty to predict the evolution of the process. The first question investigated here is whether stock price time series exhibit temporal dependencies that can be measured through entropy estimates. Then we study the extent to which the return of financial trading rules is correlated with the entropy rates of the price time series. Experiments are conducted on EOD data of the stocks composing the NYSE US 100 index during period 2000–2006, with the use of Genetic Programming to induce the trading rules.
Keywords : Entropy estimate surrogate testing genetic programming financial trading rules NYSE
Type de document :
Communication dans un congrès
6th International Conference on Computational Intelligence in Economics & Finance - CIEF 2007, Jul 2007, Salt-Lake City, United States. World Scientific Publishing, pp.501-507, 2007, INFORMATION SCIENCES 2007 - Proceedings of the 10th Joint Conference. 〈10.1142/9789812709677_0073〉
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Contributeur : Nicolas Navet <>
Soumis le : lundi 27 août 2007 - 16:09:12
Dernière modification le : jeudi 11 janvier 2018 - 06:20:05
Document(s) archivé(s) le : jeudi 8 avril 2010 - 21:28:45

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Nicolas Navet, Shu-Heng Chen. Entropy rate and profitability of technical analysis: experiments on the NYSE US 100 stocks. 6th International Conference on Computational Intelligence in Economics & Finance - CIEF 2007, Jul 2007, Salt-Lake City, United States. World Scientific Publishing, pp.501-507, 2007, INFORMATION SCIENCES 2007 - Proceedings of the 10th Joint Conference. 〈10.1142/9789812709677_0073〉. 〈inria-00168347〉

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