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Hybrid Automatic Trading Systems: Technical Analysis Group Method of Data Handling

机译：混合自动交易系统：技术分析和数据处理方法

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For building an automatic trading system one needs: a significant variable for characterizing the financial asset behaviours; a suitable algorithm for finding out the information hidden in such a variable; and a proper Trading strategy for transforming these information in operative indications. Starting from recent results proposed in literature, we have conjectured that the Technical Analysis approach could reasonably extract the information present in prices and volumes. Like tool able to find out the relation existing between the Technical Analysis inputs and an output we properly defined, we use the Group Method of Data Handling, a soft-computing approach which gives back a polynomial approximation of the unknown relationship between the inputs and the output. The automatic Trading Strategy we implement is able both to work in real-time and to return operative signals. The system we create in such a way not only performs pattern recognition, but also generates its own patterns. The results obtained during an intraday operating simulation on the US T-bond futures is satisfactory, particularly from the point of view of the trend direction detection, and from the net profit standpoint.
机译：为构建自动交易系统，需要一种需要：用于表征金融资产行为的重要变量;一种用于查找隐藏在这种变量中的信息的合适算法;以及用于在手术迹象中转换这些信息的适当交易策略。从文学中提出的最近结果开始，我们猜想技术分析方法可以合理地提取价格和卷中存在的信息。类似于能够在技术分析输入和输出之间找到的关系的工具，我们使用数据处理的组方法，一种软计算方法，它给出了输入和输入之间未知关系的多项式近似输出。我们实施的自动交易策略能够实时工作并返回操作信号。我们以这样的方式创建的系统不仅执行模式识别，而且还生成了自己的模式。在美国T键期货的盘中操作模拟期间获得的结果令人满意，特别是从趋势方向检测的角度来看，净利润立场。

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