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Applying Market Profile Theory to Analyze Financial Big Data and Discover Financial Market Trading Behavior - A Case Study of Taiwan Futures Market

机译:应用市场概况理论分析金融大数据并发现金融市场交易行为-以台湾期货市场为例

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With financial market constantly changing, prices are often affected by many factors that we cannot predict its direction easily especially in the market correction. If investors want to make profits, they must find a relatively low-risk entry points. This study is based on Market Profile Theory to use the displacement of point of control (POC) in different trading days to find out the best extremely short-term entry and exit points in financial big data in order to have experiment and analysis. We expect to find knowledge and behavior of the potential market that can help traders to make profits in extremely short-term trading. And at the end of this study, we can refute that Taiwan Index Futures Market conform to the weak form of efficient market hypothesis. This study found that the POC of historical trading day can be the reference and recommendation of entry point. The greatest performance of making profit is using 5-days historical POC to join the experiment. And it shows POC has the characteristic that the most traders accept its price.
机译:由于金融市场不断变化,价格往往受到许多因素的影响,我们无法轻易预测其方向,特别是在市场纠正中。如果投资者想要赚取利润,他们必须找到一个相对低风险的入口点。本研究基于市场简介理论,在不同的交易日使用控制点(POC)的位移,以找出金融大数据中最佳的极短期进入和退出点,以进行实验和分析。我们希望能够找到潜在市场的知识和行为,这些市场可以帮助贸易商在极短信的交易中赚取利润。在本研究结束时,我们可以反驳台湾指数期货市场符合弱势市场假设的弱势形式。本研究发现,历史贸易日的POC可以是入学点的参考和推荐。利润的最大表现正在使用5天的历史POC加入实验。它显示PoC具有最多的交易商接受其价格的特征。

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