运用技术分析指标预测股票市场价格走势

Ramazan Faruk Oguz, Yasin Uygun, M. Aktaş, Ishak Aykurt
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引用次数: 5

摘要

技术指标是以金融时间序列数据为输入,根据数学计算预测价格运动方向的算法。技术分析师可以通过解释不同技术指标的结果来预测股价走势。在本研究中,我们研究了基于学习算法中技术指标的价格运动方向预测。我们探索了当它们在学习算法中一起使用时提供最成功预测的技术指标。在本文中,我们研究了导致最成功的价格运动方向预测的技术指标。为了做到这一点,我们探索了各种机器学习算法的指标的所有可能组合。本文提出了一种决策支持系统,利用机器学习算法中的技术指标来预测金融时间序列数据的价格运动方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Use of Technical Analysis Indicators for Stock Market Price Movement Direction Prediction
Technical indicators are algorithms that take financial time series data as input and predict price movement directions based on mathematical calculations. Technical analysts can predict the stock price trends by interpreting the results of different technical indicators. In this study, we investigate the prediction of price movement directions based on the use of technical indicators in learning algorithms. We explore the technical indicators that provide the most successful prediction when they are used together in learning algorithms. In this paper, we investigate the technical indicators that lead to the most successful price movement direction prediction. To do this, we explore all possible combinations of indicators with various machine learning algorithms. Here, a decision support system is proposed to predict price movement direction on financial time series data by using technical indicators in machine learning algorithms.
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