Schulenburg (2000) first proposed the idea to model different trader types by supplying different input information sets to a group of homogenous LCS agent. Gershoff (2006) investigated this idea further with XCS agent. This paper takes an extra step to build a trading system that not only adopts the multi-XCS agent idea, but also utilizes knowledge from discretization theory, modern portfolio theory, options theory and methods of combining multiple models. In comparison to previous work, a wider range of input data were used including technical analysis, general market conditions and options market conditions. Secondly, quantization of continuous financial series was achieved using entropy-based discretization and histogram equalization. Thirdly, subtle investment strategies can now be generated as a result of taking stock price magnitude into account. Finally, multiple agents' predictions were combined using a variant of stacking. Empirical results show the best-performing XCS agents always outclass benchmark agents in every stock examined. Variance is reduced after combining predictions from multiple models. The technical analysis XCS agent was able to replicate a well known technical trading rule widely used in the 60s.
Schulenburg(2000)首先提出了通过向一组同质LCS代理提供不同的输入信息集来模拟不同的交易者类型。 Gershoff(2006)将此想法进一步调查了XCS代理人。本文采取额外的步骤来构建一个交易系统,不仅采用多XCS代理理念,而且还利用了来自离散化理论,现代组合理论,选项理论和结合多种模型的方法的知识。与以前的工作相比,使用了更广泛的输入数据,包括技术分析,一般市场条件和期权市场条件。其次,使用基于熵的离散化和直方图均衡来实现连续财务系列的量化。第三,现在可以在考虑股票价格幅度的结果中产生微妙的投资策略。最后,使用堆叠的变体组合多种代理的预测。经验结果表明,最好的XCS代理总是在每个股票中均出售基准代理商。在组合多种模型的预测之后,方差减少。技术分析XCS代理能够复制在60年代广泛使用的众所周知的技术交易规则。 p>
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