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Automated Stock Price Prediction and Trading Framework for Nifty Intraday Trading

机译：漂亮股票价预测及交易框架，供漂亮的盘区交易

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摘要

Research on automated systems for Stock price prediction has gained much momentum in recent years owing to its potential to yield profits. In this paper, we present an automatic trading system for Nifty for deciding the buying and selling calls for intra-day trading that combines various methods to improve the quality and precision of the prediction. Historical data has been used to implement the various technical indicators and also to train the Neural Network that predicts movement for intra-day Nifty. Further, Sentiment Analysis techniques are applied to popular blog articles written by domain experts and to user comments to find sentiment orientation, so that analysis can be further improved and better prediction accuracy can be achieved. The system makes a prediction for every trading day with these methods to forecast if next day will be a positive day or negative. Further, buy and sell calls for intra-day trading are also decided by the system thus achieving full automation in stock trading.
机译：由于其促进利润潜力，近年来股票价格预测自动化系统的研究取得了很多动力。在本文中，我们提供了一个自动交易系统，用于决定购买和销售呼叫的频率，以提高预测的质量和精度的日期交易。历史数据已被用来实施各种技术指标，也用于培训预测日期内漂亮运动的神经网络。此外，情绪分析技术应用于由域专家编写的流行博客文章以及用户评论以找到情绪取向，从而可以进一步提高分析，并且可以实现更好的预测精度。如果第二天将是一个正面或负面的方法，该系统对每个交易日进行预测。此外，购买和销售呼叫对日内交易的呼叫也决定了该系统，从而实现了股票交易的完整自动化。

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