Volume : VII, Issue : XI, November - 2018

Significance of Data Pre-Processing techniques in stock market

Prof. Kainaz Bomi Sherdiwala, Dr. Samrat O. Khanna

Abstract :

 In this paper, we have focused on the importance and necessity of pre–processing of raw data. Preprocessing helps to improve the quality of all types of data which turns out to be useful for Apriori algorithm in discovering Association Rules. Stock market data of past 7.3 years for the period between 01/01/2011 and 31/03/2018 is collected from NSE website. Apart from the stock prices, we have also collected data of NIFTY 50 index for the same period. Database was built for the same. Attributes like Company’s symbol, Date, Open, High, Low and Close were considered for our research problem. This raw data will be pre–processed. This pre–processed will be used in Association Rule Mining (ARM) to generate high quality rules which will help us in discovering useful pattern from our dataset. The main aim of our research is to find co–relation between index value and price of the scripts. Therefore we have employed ARM in our study. Various preprocessing techniques such as data cleaning, data integration, binning was employed to make the quality of data better which can yield accurate results

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Article: Download PDF   DOI : 10.36106/ijsr  

Cite This Article:

Significance of Data Pre-Processing techniques in stock market , Prof. Kainaz Bomi Sherdiwala, Dr. Samrat O. Khanna , INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH : Volume-7|Issue-11| November-2018

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