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  Published Paper Details:

  Paper Title

STOCK MARKET PREDICTION AND RECOMMENDATION SYSTEM

  Authors

  Khushboo Dattani,  Ashutosh Shukla,  Devansh Shah,  Aarti Puthran

  Keywords

Prediction, Analysis

  Abstract


Since its inception, the Stock market has become a sophisticated way of investing money and a reliable source of income. Performance of stock relies on multiple factors which makes it very unpredictable and volatile. Hence, Prediction can play an important and helpful role here. Predicting markets can offer great profit avenues, and much research is going on for it. For prediction, most researchers use either technical analysis or fundamental analysis. Technical analysis can be referred to as prediction on the basis of previous stock prices while fundamental analysis can be referred to as analysing the unstructured textual data, example: news, tweets, etc. Today the world is digitalized, the market information is accessible to common people as well, this takes it to text mining strategies that would extract significant information to analyse market behaviour. In this project we will be using past prices of stock and news headlines together to predict the stock prices. The project will give recommendations on stock buy /sell on the basis of current news

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2203102

  Paper ID - 215193

  Page Number(s) - a771-a776

  Pubished in - Volume 10 | Issue 3 | March 2022

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Khushboo Dattani,  Ashutosh Shukla,  Devansh Shah,  Aarti Puthran,   "STOCK MARKET PREDICTION AND RECOMMENDATION SYSTEM", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 3, pp.a771-a776, March 2022, Available at :http://www.ijcrt.org/papers/IJCRT2203102.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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