EconPapers    
Economics at your fingertips  
 

Social Network based Short-Term Stock Trading System

Paolo Cremonesi, Chiara Francalanci, Alessandro Poli, Roberto Pagano, Luca Mazzoni, Alberto Maggioni and Mehdi Elahi

Papers from arXiv.org

Abstract: This paper proposes a novel adaptive algorithm for the automated short-term trading of financial instrument. The algorithm adopts a semantic sentiment analysis technique to inspect the Twitter posts and to use them to predict the behaviour of the stock market. Indeed, the algorithm is specifically developed to take advantage of both the sentiment and the past values of a certain financial instrument in order to choose the best investment decision. This allows the algorithm to ensure the maximization of the obtainable profits by trading on the stock market. We have conducted an investment simulation and compared the performance of our proposed with a well-known benchmark (DJTATO index) and the optimal results, in which an investor knows in advance the future price of a product. The result shows that our approach outperforms the benchmark and achieves the performance score close to the optimal result.

New Economics Papers: this item is included in nep-cmp
Date: 2018-01
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed

Downloads: (external link)
http://arxiv.org/pdf/1801.05295 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1801.05295

Access Statistics for this paper

More papers in Papers from arXiv.org
Series data maintained by arXiv administrators ().

 
Page updated 2018-02-17
Handle: RePEc:arx:papers:1801.05295