利用机器学习算法对金融市场上股东的损益进行预测

Ramakant Upadhyay, Harinder Kaur
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引用次数: 0

摘要

股票的曲线出乎意料。股市预测的复杂性和不可预测性使得预测很难做出。预测未来股市的稳定性是说服听众的主要目标。许多分析师都对该行业未来的发展进行了研究。不可靠的信息是库存的一个组成部分,使知识成为力量的重要来源。预测强度对持续可能性的影响。作为当前交换预测技术发展的一部分,深度学习已经将自己融入到教学集和信息模型的开发和投影图像中。为了根据需要预测和改变事物,机器学习使用了完全不同的组件、方法和算法。本文的主要课题是LSTM和回归在股票价值预测中的应用。
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A ML Algorithm was used to Forecast the Gain or Loss of a Shareholder in the Financial Markets
The curve of stock is unexpected. The complexity and unpredictability of stock market predictions make them difficult to make. Predicting the stability of future market stocks is the main goal for persuading the audience. Numerous analysts have conducted their study on how the industry would evolve in the future. Unreliable information is a component of stock, making knowledge a vital source of power. Impact of the prediction's strength on enduring possibilities. Deep learning has incorporated itself into the image for the development and projection of instruction sets and information models as part of the current development of exchange forecasting technology. To forecast and alter things as needed, Machine Learning uses whole distinct components methods and algorithms. The main topic of the paper is the Application of LSTM and regression to forecast stock values.
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