Sentiment analysis of news and social-media for creating trading strategies

Please use this identifier to cite or link to this item: http://repository.iiitd.edu.in/xmlui/handle/123456789/790

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DC Field	Value	Language
dc.contributor.author	Kataria, Tushar	-
dc.contributor.author	Agarwal, Vasu	-
dc.contributor.author	Chakraborty, Tanmoy (Advisor)	-
dc.date.accessioned	2019-10-14T10:05:43Z	-
dc.date.available	2019-10-14T10:05:43Z	-
dc.date.issued	2018-11-26	-
dc.identifier.uri	http://repository.iiitd.edu.in/xmlui/handle/123456789/790	-
dc.description.abstract	The problem of stock market predictability has intrigued both academia and industry. In this thesis, we try to empirically predict the stock market using models from deep natural language processing. We review existing literature and also create a new dataset for the Indian market.	en_US
dc.language.iso	en_US	en_US
dc.publisher	IIITD-Delhi	en_US
dc.subject	Natural Language Processing	en_US
dc.subject	Stock Market	en_US
dc.title	Sentiment analysis of news and social-media for creating trading strategies	en_US
dc.type	Other	en_US
Appears in Collections:	Year-2018

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