使用Python的交易模拟和基于机器学习决策树的流光可视化

I. Simanjuntak, Heriyanto Heriyant, Agus Rochendi, Yosy Rahmawati, Ketty Salamah, S. Sulistiyono
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引用次数: 0

摘要

如今,人们开始对投资股票市场和加密货币产生浓厚兴趣,以获取利润。然而,在2022年初,许多欺诈性投资,如非法交易机器人,被巨额利润所说服。当人们用错误的策略和决策进行交易时,会造成重大损失。因此,我们需要一个系统,可以帮助模拟交易使用技术指标分析和机器学习决策树。测试进行了几个JCI股票和加密货币。仿真结果数据以表格数据和图形的形式显示。因此,从机器学习决策树的交易模拟中获得的好处不仅仅是使用技术指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trading Simulation Using Python and Visualization on Streamlit with Machine Learning Decision Tree
Nowadays, people are starting to have much interest in investing in the stock market and cryptocurrencies to profit. However, at the beginning of 2022, many fraudulent investments, such as illegal trading robots, are persuaded by big profits. People cause a significant loss when trading with the wrong strategies and decisions. Therefore, we need a system that can help simulate trading using technical indicator analysis and machine learning decision trees. Tests carry on several JCI stocks and cryptocurrencies. The simulation result data display as table data and graphs. As a result, the benefits obtained from trading simulations with machine learning decision trees are more than using only technical indicators.
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