英文标题：
《Equity forecast: Predicting long term stock price movement using machine
  learning》
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作者：
Nikola Milosevic
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最新提交年份：
2018
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英文摘要：
  Long term investment is one of the major investment strategies. However, calculating intrinsic value of some company and evaluating shares for long term investment is not easy, since analyst have to care about a large number of financial indicators and evaluate them in a right manner. So far, little help in predicting the direction of the company value over the longer period of time has been provided from the machines. In this paper we present a machine learning aided approach to evaluate the equity\'s future price over the long time. Our method is able to correctly predict whether some company\'s value will be 10% higher or not over the period of one year in 76.5% of cases.
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中文摘要：
长期投资是主要的投资策略之一。然而，计算一些公司的内在价值和评估长期投资的股票并不容易，因为分析师必须关注大量财务指标，并以正确的方式进行评估。到目前为止，这些机器对预测公司在较长时期内的价值方向几乎没有帮助。在本文中，我们提出了一种机器学习辅助的方法来评估股票的未来长期价格。在76.5%的案例中，我们的方法能够正确预测某公司的价值在一年内是否会高出10%。
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Machine Learning        机器学习
分类描述：Papers on all aspects of machine learning research (supervised, unsupervised, reinforcement learning, bandit problems, and so on) including also robustness, explanation, fairness, and methodology. cs.LG is also an appropriate primary category for applications of machine learning methods.
关于机器学习研究的所有方面的论文（有监督的，无监督的，强化学习，强盗问题，等等），包括健壮性，解释性，公平性和方法论。对于机器学习方法的应用，CS.LG也是一个合适的主要类别。
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一级分类：Quantitative Finance        数量金融学
二级分类：General Finance        一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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