DocumentCode
2910262
Title
Testing the Dinosaur Hypothesis under different GP algorithms
Author
Kampouridis, Michael ; Chen, Shu-Heng ; Tsang, Edward
fYear
2010
fDate
8-10 Sept. 2010
Firstpage
1
Lastpage
7
Abstract
The Dinosaur Hypothesis states that the behaviour of a market never settles down and that the population of predictors continually co-evolves with this market. This observation had been made and tested under artificial datasets. Recently, we formalized this hypothesis and also tested it under 10 empirical datasets. The tests were based on a GP system. However, it could be argued that results are dependent on the GP algorithm. In this paper, we test the Dinosaur Hypothesis under two different GP algorithms, in order to prove that the previous results are rigorous and are not sensitive to the choice of GP. We thus test again the hypothesis under the same 10 empirical datasets. Results are consistent among all three algorithms and thus suggest that market behavior can actually repeat itself, and have a number of `typical states´, where past rules may become useful again.
Keywords
genetic algorithms; stock markets; GP algorithm; dinosaur hypothesis testing; market behavior; DH-HEMTs; Decision trees; Dinosaurs; Genetics; Prediction algorithms; Radio frequency; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence (UKCI), 2010 UK Workshop on
Conference_Location
Colchester
Print_ISBN
978-1-4244-8774-5
Electronic_ISBN
978-1-4244-8773-8
Type
conf
DOI
10.1109/UKCI.2010.5625593
Filename
5625593
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