Mining Financial News for Major Events and Their Impacts on the Market

Author

Mahajan, Anuj ; Dey, Lipika ; Haque, Sk Mirajul

Author_Institution

Innovation Labs., Tata Consultancy Services, Delhi

Volume

1

fYear

2008

fDate

9-12 Dec. 2008

Firstpage

423

Lastpage

426

Abstract

In this paper we have proposed a stock market analysis system that analyzes financial news items to identify and characterize major events that impact the market. The events have been identified using latent Dirichlet allocation (LDA) based topic extraction mechanism. These topics have been thereafter analyzed in conjunction with actual market data to understand their impact on the market. A prediction system has been proposed which can predict whether the stock market will fall or rise, based on news items.

Keywords

data mining; economic forecasting; financial data processing; stock markets; text analysis; financial news items; latent Dirichlet allocation; prediction system; stock market analysis system; text mining; topic extraction; Data analysis; Data mining; Economic forecasting; Intelligent agent; Linear discriminant analysis; Portfolios; Predictive models; Stock markets; Technological innovation; Text mining; Financial News; LDA; Stock Market; prediction.; sensex; topic;

fLanguage

English

Publisher

ieee

Conference_Titel

Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on

Conference_Location

Sydney, NSW

Print_ISBN

978-0-7695-3496-1

Type

conf

DOI

10.1109/WIIAT.2008.309

Filename

4740487