Breakout Stocks Identification using Machine Learning Approaches

Md. Siam Ansary
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Abstract

Stock market offers a platform for people to engage in trading. It contributes to the growth of nation. Decision making regarding investments needs to be done very carefully so that an investor does not suffer massive loss. Since the share market is susceptible to experience huge change at any given moment, with the probability of profit comes huge risks of losing a fortune. In our research, we have worked on prediction of breakout stocks. If identified properly, it can help one to invest efficiently. We have used multiple machine learning approaches as ML models can offer more effective predictions compared to other methods due to the ability to learn and adapt from dataset information. In our experiment, the models have yielded very good results.
使用机器学习方法识别突破库存
股票市场为人们提供了一个进行交易的平台。它有助于国家的发展。有关投资的决策需要非常谨慎,这样投资者才不会遭受巨大的损失。由于股票市场在任何给定的时刻都容易经历巨大的变化,随着盈利的可能性而来的是损失财富的巨大风险。在我们的研究中,我们研究了突破股的预测。如果识别得当,它可以帮助人们有效地进行投资。我们使用了多种机器学习方法,因为与其他方法相比,ML模型可以提供更有效的预测,因为它能够从数据集信息中学习和适应。在我们的实验中,这些模型取得了很好的效果。
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