Open AccessStock Market Prediction Using Machine Learning
Author(s) -
Srihitha Podduturi,
Geohnavi Marskatla,
Dr. SN Chandrashekhar,
Mr. P. Anvesh,
Ms. E. Lavanya,
Mr. P. Pradeep Kumar,
Sunil Rao
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.40857
Subject(s) - stock market , portfolio , stock (firearms) , computer science , financial market , task (project management) , stock market prediction , finance , business , economics , engineering , mechanical engineering , paleontology , management , horse , biology
Wise use of financial predictions plays a vital role in facilitating investment decisions for many investors. With the right information, investors can adjust their portfolio to maximize returns while minimizing risk. However, not all investments guarantee a good return, and this is mainly due to the fact that many investors have limited knowledge and skills to predict stock trends. However, the complexity and turmoil of the stock market, make any prediction efforts extremely difficult. This paper aims to provide a comprehensive review of the emerging research related to the use of Mechanical Learning and In-depth Learning models in the field of financial market forecast. To prepare for this task, more than sixty research papers have been thoroughly analyzed to extract the much needed information, application, and results of the various methods. It is found in this project that Intensive Reading is the most successful Automatic Reading in all the research papers collected, and is the most appropriate way to use the stock market prediction domain.