Open AccessA SURVEY ON STOCK PRICE PREDICTION USING MACHINE LEARNING
Author(s) -
Manavi Mishra,
Manjushree Patil,
Geetanjali Raut,
Tushar Chaudhari
Publication year - 2021
Publication title -
international journal of engineering applied science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-2143
DOI - 10.33564/ijeast.2021.v05i11.033
Subject(s) - stock (firearms) , stock price , stock market , restricted stock , financial economics , stock market bubble , market maker , economics , econometrics , computer science , business , engineering , geography , mechanical engineering , paleontology , context (archaeology) , archaeology , series (stratigraphy) , biology
Stock returns are very fluctuating in nature.They rely upon various factors like previous stock prices,current market trends, financial news, etc. To feature theirannual income, people have now started watching stockinvestments as a remunerative option. There are many toolsavailable to investors using technical analysis to formdecisions. With expert guidance and intelligent planning, wewill almost double our annual income through stockreturns. These days, social media has become a mirror. Itreflects people’s thoughts and opinions on any particularevent or news. Sentiments of the general public associatedwith an organization can have an upshot on its stock prices.This paper surveys various machine learning techniquesand algorithms employed to boost the accuracy of stockprice prediction.