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  Published Paper Details:

  Paper Title

STOCK MARKET PRICE PREDICTION USING RANDOM FOREST AND SUPPORT VECTOR MACHINE

  Authors

  R S Abirami,  K.Varalakshmi,  Maddika Jaswanth Reddy,  Kota Venkata Madhava Reddy,  Chittipi Reddy Akash

  Keywords

STOCK MARKET PRICE PREDICTION USING RANDOM FOREST AND SUPPORT VECTOR MACHINE

  Abstract


In the past decades, there is an increasing interest in predicting markets among economists, policymakers, academics and market makers. The objective of the proposed work is to study and improve the supervised learning algorithms to predict the stock price.Stock Market Analysis of stocks using data mining will be useful for new investors to invest in stock market based on the various factors considered by the software. Stock market includes daily activities like Sensex calculation, exchange of shares. The exchange provides an efficient and transparent market for trading in equity, debt instruments and derivatives. Our aim is to create software that analyses previous stock data of certain companies, with help of certain parameters that affect stock value. We are going to implement these values in data mining algorithms and we will be able to decide which algorithm gives the best result. This will also help us to determine the values that particular stock will have in near future. We will determine the patterns in data with help of machine learning algorithms.

  IJCRT's Publication Details

  Unique Identification Number - IJCRTS020003

  Paper ID - 223525

  Page Number(s) - 18-24

  Pubished in - Volume 10 | Issue 6 | June 2022

  DOI (Digital Object Identifier) -   

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

  E-ISSN Number - 2320-2882

  Cite this article

  R S Abirami,  K.Varalakshmi,  Maddika Jaswanth Reddy,  Kota Venkata Madhava Reddy,  Chittipi Reddy Akash,   "STOCK MARKET PRICE PREDICTION USING RANDOM FOREST AND SUPPORT VECTOR MACHINE", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 6, pp.18-24, June 2022, Available at :http://www.ijcrt.org/papers/IJCRTS020003.pdf

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


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