Decision support system for stock trading using multiple indicators decision tree

2014 The 1st International Conference on Information Technology, Computer, and Electrical Engineering Pub Date : 2014-11-01 DOI:10.1109/ICITACEE.2014.7065759

F. Nugroho, T. B. Adji, S. Fauziati

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引用次数: 10

Abstract

Decision support system using decision tree classification can be used for stock trading technical analysis. Technical analysis is a stock analysis method which solely based on interpreting stock's price chart movement or trend. Historical stock prices and volume are used as variable input. The system is built based on financial market technical analysis indicators (Exponential Moving Average, Moving Average Convergence Divergence, Relative Strength Index, Money Flow Index, and parabolic Stop and Reverse). The proposed method is arrange indicators set into decision tree based on stock trading rules and it create buy, hold, and sell classes which represented decisions in trading. Decision classes then are analyzed for their profitability, geometric mean return, and cumulative wealth index. Furthermore sensitivity analysis is added into profitability analysis to obtain more positive value trading in decision making. The research purpose is to enhance decision making in technical stock trading. Compared to the single indicator decision tree multiple indicators offers 20% enhancement in decision making.

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股票交易决策支持系统采用多指标决策树

决策支持系统采用决策树分类，可用于股票交易技术分析。技术分析是一种完全基于对股票价格走势图运动或趋势的解释的股票分析方法。历史股票价格和成交量被用作变量输入。系统基于金融市场技术分析指标(指数移动平均、移动平均收敛发散、相对强弱指标、资金流动指标、抛物线止损反转)构建。该方法基于股票交易规则，将指标集排列到决策树中，创建买入、持有和卖出类，代表交易决策。然后分析决策类的盈利能力、几何平均回报和累积财富指数。此外，在盈利能力分析中加入敏感性分析，以获得更积极的交易决策价值。研究的目的是提高技术股票交易中的决策能力。与单指标决策树相比，多指标决策树的决策效率提高了20%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2014 The 1st International Conference on Information Technology, Computer, and Electrical Engineering

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