通过对输入使用高级表示来提高智能股票交易系统的性能

Mojtaba Azimifar, Babak Nadjar Araabi, Hadi Moradi
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引用次数: 2

摘要

智能股票交易系统使用软计算技术来预测股票价格的趋势。但所谓的市场噪音通常会导致过度交易和利润损失。为了减少噪声对交易决策的影响,可以对交易系统的输出使用高级表示。但作为交易系统输入的技术指标也受到这些短期违规行为的影响。本文提出了一种与产出信息水平相匹配的技术指标的高层次表示。数字低通滤波器经过精心设计,可以消除技术指标的瞬态波动,而不会丢失太多信息。对德黑兰证券交易所不同股票的实验表明,智能股票交易系统的性能有了很大的提高。
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Improving the performance of intelligent stock trading systems by using a high level representation for the inputs
Intelligent stock trading systems use soft computing techniques for forecasting the trend of the stock price. But the so-called noise in the market usually results in overtrading and loss of profit. In order to reduce the effect of noise on the trading decisions, high level representations can be used for the output of the trading systems. But the technical indicators which act as the inputs of the trading system, suffer from these short term irregularities as well. This paper suggests a high level representation for the technical indicators to match the level of information in the outputs. Digital low pass filters are carefully designed to remove the transient fluctuations of the technical indicators without losing too much information. Several experiments on different stocks in Tehran Stock Exchange shows a major improvement in the performance of the intelligent stock trading systems.
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