在不同GP算法下检验恐龙假说

Michael Kampouridis, Shu-Heng Chen, E. Tsang
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引用次数: 1

摘要

恐龙假说认为,市场的行为永远不会稳定下来,预测者的数量会随着市场的变化而不断变化。这一观察结果是在人工数据集下得出和测试的。最近,我们对这一假设进行了形式化,并在10个经验数据集下进行了检验。测试基于GP系统。然而,可以认为结果依赖于GP算法。本文在两种不同GP算法下对恐龙假设进行检验,以证明之前的结果是严格的,并且对GP的选择不敏感。因此,我们在相同的10个经验数据集下再次检验假设。所有三种算法的结果都是一致的,因此表明市场行为实际上可以重复自己,并且有许多“典型状态”,在这些状态下,过去的规则可能再次有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Testing the Dinosaur Hypothesis under different GP algorithms
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.
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