Identifying stock patterns and training Classifiers for suggesting investments

Nikhil Sharma; Praveen Kumar; Hisham Hussen

doi:10.1109/CONFLUENCE.2019.8776912

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Conference proceeding

Identifying stock patterns and training Classifiers for suggesting investments

Nikhil Sharma, Praveen Kumar and Hisham Hussen

2019 9TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING, DATA SCIENCE & ENGINEERING (CONFLUENCE 2019), pp.273-277

01/01/2019

DOI: https://doi.org/10.1109/CONFLUENCE.2019.8776912

Abstract

Computer Science

Computer Science, Information Systems

Computer Science, Theory & Methods

Science & Technology

Technology

This paper explores and analyzes the stock data of companies listed in NASDAQ100 and tries to find out if there is any correlation between various attributes of stock data like opening, closing, daily, weekly, monthly and yearly change in stock prices of these companies. The paper also explores for any market trends that may exist in the stock data up to 2017, and finally train a classifier that gives investing advice to buy/hold/sell stock for the companies listed in NASDAQ100 using machine learning.

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Details

Title: Identifying stock patterns and training Classifiers for suggesting investments
Creators - without role: Nikhil Sharma - Amity University
Praveen Kumar - Amity University
Hisham Hussen - University of Ha'il
Contributors - without role: A Bansal
A Singhal
Publication Details: 2019 9TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING, DATA SCIENCE & ENGINEERING (CONFLUENCE 2019), pp.273-277
Publisher: IEEE
Number of pages: 5
Identifiers: 9932346408331
Academic Unit: University Ha'il
Language: English
Resource Type: Conference proceeding