Prediction Models for Indian Stock Market

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Stock market price data is generated in huge volume and it changes every second. Stock market is a complex and challenging system where people will either gain money or lose their entire life savings. In this work, an attempt is made for prediction of stock market trend. Two models are built one for daily prediction and the other one is for monthly prediction. Supervised machine learning algorithms are used to build the models. As part of the daily prediction model, historical prices are combined with sentiments. Up to 70% of accuracy is observed using supervised machine learning algorithms on daily prediction model. Monthly prediction model tries to evaluate whether there is any similarity between any two months trend. Evaluation proves that trend of one month is least correlated with the trend of another month.

Original languageEnglish
Pages (from-to)441-449
Number of pages9
JournalProcedia Computer Science
Volume89
DOIs
Publication statusPublished - 2016

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Learning algorithms
Learning systems
Financial markets

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

Cite this

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Prediction Models for Indian Stock Market. / Nayak, Aparna; Pai, M. M.Manohara; Pai, Radhika M.

In: Procedia Computer Science, Vol. 89, 2016, p. 441-449.

Research output: Contribution to journalArticle

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