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Classification of S&P 500 Stocks Based on Correlating Market Trends

  • Minakshi Tomer
  • Vaibhav AnandEmail author
  • Raghav Shandilya
  • Shubham Tiwari
Conference paper
  • 8 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1164)

Abstract

Stock market is a correlated entanglement of companies whose prices depend upon various factors including how well each individual company is doing, their stock’s performance and the general trend of the stock market. A simple linear prediction based upon the past performances of the stock is not enough to declare whether a particular stock will perform in a linear way. To predict the behavior of stocks, it is required to look at all of its correlated counterparts, compile their performance numbers and take a logical guess on whether the stock’s performance will be on the positive side or on the negative side. For that measure, data of all the stocks from Standard and Poor’s 500 Ratings (S&P 500) was collected. The novel idea in this paper is to classify a stock’s performance based upon its correlated features and predict that whether it should be bought, sold, or held.

Keywords

Supervised classification Support vector machines Random forest classifiers Stock market Correlation 

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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021

Authors and Affiliations

  • Minakshi Tomer
    • 1
  • Vaibhav Anand
    • 1
    Email author
  • Raghav Shandilya
    • 1
  • Shubham Tiwari
    • 1
  1. 1.Department of Information TechnologyMaharaja Surajmal Institute of TechnologyNew DelhiIndia

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