DocumentCode
3723762
Title
Stock market prediction: A big data approach
Author
Girija V Attigeri; Manohara Pai M M;Radhika M Pai;Aparna Nayak
Author_Institution
Manipal Institute of Technology, 576104, India
fYear
2015
Firstpage
1
Lastpage
5
Abstract
The Stock market process is full of uncertainty and is affected by many factors. Hence the Stock market prediction is one of the important exertions in finance and business. There are two types of analysis possible for prediction, technical and fundamental. In this paper both technical and fundamental analysis are considered. Technical analysis is done using historical data of stock prices by applying machine learning and fundamental analysis is done using social media data by applying sentiment analysis. Social media data has high impact today than ever, it can aide in predicting the trend of the stock market. The method involves collecting news and social media data and extracting sentiments expressed by individual. Then the correlation between the sentiments and the stock values is analyzed. The learned model can then be used to make future predictions about stock values. It can be shown that this method is able to predict the sentiment and the stock performance and its recent news and social data are also closely correlated.
Keywords
"Companies","Market research","Prediction algorithms","Algorithm design and analysis","Annealing","Support vector machines"
Publisher
ieee
Conference_Titel
TENCON 2015 - 2015 IEEE Region 10 Conference
ISSN
2159-3442
Print_ISBN
978-1-4799-8639-2
Electronic_ISBN
2159-3450
Type
conf
DOI
10.1109/TENCON.2015.7373006
Filename
7373006
Link To Document