From Returns to Tweets and Back: An Investigation of the Stocks in the Dow Jones Industrial Average

References

• Anonymous. “Banking, Financial Services; BMO InvestorLine Study: Online Investors Flocking to Social Media Platforms for Advice.” Marketing Weekly News, 199, ( June 11, 2011).
   Google Scholar
• Antweiler, W. and M. Z. Frank. “Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards.” Journal of Finance, 59, (2004), pp. 1259–1294.
   Web of Science ®Google Scholar
• Au, K., F. Chan, D. Wang, and I. Vertinsky. “Mood in Foreign Exchange Trading: Cognitive Processes and Performance.” Organizational Behavior and Human Decision Processes, 91, (2003), pp. 322–338.
   Web of Science ®Google Scholar
• Bollen, J., H. Mao, and X. J. Zeng. “Twitter Mood Predicts the Stock Market.” Journal of Computational Science, 2, (2011), pp. 1–8.
   Web of Science ®Google Scholar
• Bordino, I., S. Battiston, G. Caldarelli, M. Cristelli, A. Ukkonen, and I. Weber. “Web Search Queries Can Predict Stock Market Volumes.” PLoS ONE, 7, (2012), e40014.
   PubMed Web of Science ®Google Scholar
• Box, G. E. P. and D. R. Cox. “An Analysis of Transformations.” Journal of the Royal Statistical Society. Series B (Methodological), 26, (1964), pp, 211–252.
   Web of Science ®Google Scholar
• Carr, D. F. “Social Media Stock Picks Come to Bloomberg.” InformationWeek – Online, ( August 29, 2011). Retrieved from http://www.informationweek.com/software/social/social-media-stock-picks-come-to-bloomberg/d/d-id/1099869
   Google Scholar
• Chen, H., P. De, Y. J. Hu, and B.-H. Hwang. “Customers as Advisors: The Role of Social Media in Financial Markets.” Purdue University, Working Paper (2013). Retrieved from http://web.ics.purdue.edu/∼bhwang/customers.pdf
   Google Scholar
• Choi, H. and H. Varian. “Predicting the Present with Google Trends.” The Economic Record, 88, (2012), pp. 2–9.
   Web of Science ®Google Scholar
• Cogent Research. “Social Media's Impact on Personal Finance & Investing.” (2008). Retrieved from http://www.businesswire.com/news/home/20130222005037/en/Cogent-Research-Trending---Social-Media-Fuels
   Google Scholar
• Da, Z., J. Engelberg, and P. Gao. “In Search of Attention.” The Journal of Finance, 66, (2011), pp. 461–1499.
   Web of Science ®Google Scholar
• De Choudhury, M., H, Sundaram, A. John, and D. D. Seligmann. “Can Blog Communication Dynamics Be Correlated With Stock Market Activity?” in 19^th ACM Conference on Hypertext and Hypermedia (pp. 55–60). ACM Press, 2008.
   Google Scholar
• Dickey, D. A. and W. A. Fuller. “Distribution of the Estimators for Autoregressive Time Series with a Unit Root.” Journal of the American Statistical Association, 74, (1979), pp. 427–431.
   Web of Science ®Google Scholar
• Engle, R. F. and K. F. Kroner. “Multivariate Simultaneous Generalized ARCH.” Econometric Theory, 11, (1995), pp. 122–150.
   Web of Science ®Google Scholar
• Ettredge, M., J. Gerdes, and G. Karuga. “Using Web-Based Search Data to Predict Macro-Economic Statistics.” Communications of the ACM, 48, (2005), pp. 87–92.
   Web of Science ®Google Scholar
• Gilbert, E. and K. Karahalios. “Widespread Worry and the Stock Market” in Fourth International Conference on Weblogs and Social Media (pp. 58–65). AAAI Press, 2010.
   Google Scholar
• Guzman, G. “Internet Search Behavior as an Economic Forecasting Tool: The Case of Inflation Expectations.” Journal of Economic and Social Measurement, 36, (2011), pp. 119–167.
   Google Scholar
• Hachman, M. “Study Claims Stock Price, Social Media Are Linked.” PC Magazine. ( March 22, 2011). Retrieved from http://www.pcmag.com/article2/0,2817,2382391,00.asp
   Google Scholar
• Hogan, M. “Social-Network Investing.” Barron's, 90, ( October 25, 2010), 43:41.
   Google Scholar
• Hull, J. and A. White. “Incorporating Volatility Updating into the Historical Simulation Method for Value-at-risk.” Journal of Risk, 1, (1998), pp. 5–19.
   Google Scholar
• Kadleck, C. “Poke! Tweet! Buy! Sell! Social Media Influences World of Investing.” Crain's Cleveland Business, ( June 1, 2014). Retrieved from http://www.crainscleveland.com/article/20140601/SUB1/306019995/poke-tweet-buy-sell-social-media-influences-world-of-investing
   Google Scholar
• Langlois, C. “Social Media Influences 70% of Investors for Personal Finance and Investing.” Visible Banking, ( February 26, 2013). Retrieved from http://www.visiblebanking.com/social-media-influences-70-of-investors-for-personal-finance-and-investing-report-7548/
   Google Scholar
• McLaren, N. and R. Shanbhogue. “Using Internet Search Data as Economic Indicators.” Bank of England Quarterly Bulletin, 51, (2011), pp. 134–140.
   Google Scholar
• O'Connor, B., R. Balasubramanyan, B. R. Routledge, and N. A. Smith. “From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series.” In Proceedings of the International AAAI Conference on Weblogs and Social Media (pp. 122–129). Palo Alto: AAAI Press, 2010.
   Google Scholar
• Oh, C. and O. Sheng. “Investigating Predictive Power of Stock Micro Blog Sentiment in Forecasting Future Stock Price Directional Movement.” In 32^nd International Conference on Information Systems, AIS, (2011), pp. 17.
   Google Scholar
• Phillips, P. C. B. and P. Perron. “Testing for a Unit Root in Time Series Regression.” Biometrika, 75, (1988), pp. 335–346.
   Web of Science ®Google Scholar
• Securities and Exchange Commission. “Investment Adviser Use of Social Media.” National Examination Risk Alert, 2, (2012), pp. 1–7.
   Google Scholar
• Sprenger, T. O., A. Tumasjan, P. G. Sandner, and I. M. Welpe. “Tweets and Trades: The Information Content of Stock Microblogs.” European Financial Management, 20, (2014), pp. 926–957.
   Web of Science ®Google Scholar
• Vosen, S. and T. Schmidt. “Forecasting Private Consumption: Survey-Based Indicators vs. Google Trends.” Journal of Forecasting, 30, (2011), pp. 565–578.
   Web of Science ®Google Scholar
• Vosen, S. and T. Schmidt. “A Monthly Consumption Indicator for Germany Based on Internet Search Query Data.” Applied Economics Letters, 19, (2012), pp. 683–687.
   Web of Science ®Google Scholar
• Wang, X., M. S. Gerber, and D. E. Brown. “Automatic Crime Prediction Using Events Extracted from Twitter Posts.” In S. J. Yang, A. M. Greengerg and M. Endsley (eds.), SBP 2012, LNCS 7227 (pp, 231–238). Berlin: Springer-Verlag, 2012.
   Google Scholar
• Wu, L. and E. Brynjolfsson. “The Future of Prediction: How Google Searches Foreshadow Housing Prices and Quantities.” 30th International Conference on Information Systems, 2009. Retrieved from http://aisel.aisnet.org/icis2009/147
   Google Scholar
• Zhang, X., H. Fuehres, and P. A. Gloor. “Predicting Stock Market Indicators Through Twitter ‘I hope it is Not as Bad as I Fear’.” Procedia – Social and Behavioral Sciences, 26, (2011a), pp. 55–62.
   Google Scholar
• Zhang, X., H. Fuehres, and P. A. Gloor. “Predicting Asset Value through Twitter Buzz.” In J. Altmann et al. (eds), Advances in Collective Intelligence 2011 (pp. 23–34). AISC, 2011b.
   Google Scholar
• Zuckerman, G. “ETFs for Investing in Social Media and Gold; Investors Can Use Funds to Bet on These Sectors, But They Come With Risks.” Wall Street Journal (Online), ( June 15, 2014a). Retrieved from http://online.wsj.com/articles/alternative-investing-etfs-for-investing-in-social-media-gold-1402683259
   Google Scholar
• Zuckerman, G. “Wealth Management (A Special Report) – Alternative Investing: ETFs Let You Bet on a Continuing Boom in the Social-Media Sector.” Wall Street Journal, ( June 14, 2014b), R.4.
   Google Scholar