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Title: Automated stock price prediction and trading framework for Nifty intraday trading
Authors: Bhat, A.A.
Sowmya, Kamath S.
Issue Date: 2013
Citation: 2013 4th International Conference on Computing, Communications and Networking Technologies, ICCCNT 2013, 2013, Vol., , pp.-
Abstract: 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. � 2013 IEEE.
Appears in Collections:2. Conference Papers

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