Modeling movements in oil, gold, forex and market indices using search volume index and Twitter sentiments

Rao, Tushar and Srivastava, Saket (2013) Modeling movements in oil, gold, forex and market indices using search volume index and Twitter sentiments. In: Web Science Conference WebSci2013, 2 - 4 May 2013, Paris.

Full content URL: http://delivery.acm.org/10.1145/2470000/2464521/p3...

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Item Type:Conference or Workshop contribution (Poster)
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Abstract

Study of the forecasting models using large scale microblog discussions and the search behavior data can provide a good insight for better understanding the market movements. In this work we collected a dataset of 2 million tweets and search volume index (SVI from Google) for a period of June 2010 to September 2011. We model a set of comprehensive causative relationships over this dataset for various market securities like equity (Dow Jones Industrial Average-DJIA and NASDAQ-100), commodity markets (oil and gold) and Euro Forex rates. We also investigate the lagged and statistically causative relations of Twitter sentiments developed during active trading days and market inactive days in combination with the search behavior of public before any change in the prices/ indices. Our results show extent of lagged significance with high correlation value upto 0.82 between search volumes and gold price in USD. We find weekly accuracy in direction (up and down prediction) uptil 94.3% for DJIA and 90% for NASDAQ-100 with significant reduction in mean average percentage error for all the forecasting models.

Keywords:Twiter, Microblogging, stock market, sentiment analysis, Social Network Analysis, oil, gold, forex
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Engineering
ID Code:11261
Deposited On:20 Oct 2015 09:14

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