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Big Data Analytics Model for Comprehensive Stock Market Anatomization

Dr. Satyen M. Parikh, Dhara N. Darji

Abstract


Prediction of future value specific stock is most complicated job. Researchers have proposed several processes, methods to evaluate the intrinsic value of stock largely categorized in fundamental, technical and sentimental analysis of the data and its changing pattern. Scope to perform in-depth end to end analysis of real time stock market and related data is increased along with development of data mining and analytics techniques. The proposed model of big data analytics integrate traditional approaches of fundamental, technical and sentimental analysis with extensive data sources available on stock exchanges, trade data stream (stock quotes) and traders sentiments (social media and comments on websites), Data needs to be analyze is  available in structured, semi structured and unstructured formats. This model also describes gathering, mapping and processing of stock market data for anatomization using the big data components like flume, hive, sqoop for different need of data processing for analytics and decision purpose.

Keywords


Analytics, Big Data, Prediction, Stock Market, Stream Data.

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References


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