This paper is published in Volume-5, Issue-2, 2019
Area
Data Analysis
Author
Munaf Patel
Co-authors
Zahir Aalam
Org/Univ
Thakur College of Engineering and Technology, Mumbai, Maharashtra, India
Pub. Date
15 March, 2019
Paper ID
V5I2-1300
Publisher
Keywords
Linear regression, Data analysis, Correlation, Beta, Time series

Citationsacebook

IEEE
Munaf Patel, Zahir Aalam. Share market analysis for share selection using data mining technique, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Munaf Patel, Zahir Aalam (2019). Share market analysis for share selection using data mining technique. International Journal of Advance Research, Ideas and Innovations in Technology, 5(2) www.IJARIIT.com.

MLA
Munaf Patel, Zahir Aalam. "Share market analysis for share selection using data mining technique." International Journal of Advance Research, Ideas and Innovations in Technology 5.2 (2019). www.IJARIIT.com.

Abstract

The share market has been a field of vast interest both for those who wish to make money by trading shares in the share market. Generally, there is an opinion about share markets like high risk and high returns. Even though we have a huge number of potential investors, only very few of them are invested in the share market. The main purpose is they are not able to take risk of taking the skill of investors. Though get low returns they want to save their money. One important reason for this problem is that they don’t have proper guidance for making their portfolio. In this paper we focus the real-world problem; we had selected three indices such as SENSEX, NIFTY. The analysis is purely based on the data collected from the past three years. The Data mining technique, Time series interpretation is applied for the Data analysis to show the ups and downs of a particular index. The correlation and Beta are the tools which give the suggestion about the share and its risk. The correlation tool is used to identify the relationship between the index and the company individually. This Beta is used to identify the risk associated with the share.
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