Title: Implementations of data mining techniques in stock market forecasting: a generic framework

Authors: Aviral Sharma; Vishal Bhatnagar; Abhay Bansal

Addresses: Amity School of Engineering and Technology, Amity University, Uttar Pradesh, India ' Ambedkar Institute of Advanced Communication, Technologies and Research, Geeta Colony, Delhi – 110031, India ' Amity School of Engineering and Technology, Amity University, Uttar Pradesh, India

Abstract: This paper presents a categorical review of existing literature in the field of share market forecasting. Share market forecasting has been done in econometrics and statistics for quite some time and the emergence of artificial intelligence and data mining are giving new dimensions to it. Data mining is being used in modern day to mine terabytes of data to find new and useful patterns from existing data for the betterment of the society. One of the application of data is to mine the data regarding the stocks in the public domain and help investors formulate a decision. We have conducted an extensive review of existing literature regarding the use of data mining techniques on the domain of share market forecasting and propose a new framework for real time stock price forecasting.

Keywords: data mining; machine learning; stock markets; technical analysis; fundamental analysis; stock market forecasting; share forecasting; shares; investment decisions; decision making; stock prices; share prices; literature review.

DOI: 10.1504/IJIE.2016.078636

International Journal of Intelligent Enterprise, 2016 Vol.3 No.3/4, pp.311 - 326

Received: 12 Nov 2015
Accepted: 23 Mar 2016
Published online: 29 Aug 2016 *

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