CFP last date
20 May 2024
Reseach Article

Why Social Media Matters: The Use of Twitter in Portfolio Strategies

by Francesco Corea
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 128 - Number 6
Year of Publication: 2015
Authors: Francesco Corea
10.5120/ijca2015906580

Francesco Corea . Why Social Media Matters: The Use of Twitter in Portfolio Strategies. International Journal of Computer Applications. 128, 6 ( October 2015), 25-30. DOI=10.5120/ijca2015906580

@article{ 10.5120/ijca2015906580,
author = { Francesco Corea },
title = { Why Social Media Matters: The Use of Twitter in Portfolio Strategies },
journal = { International Journal of Computer Applications },
issue_date = { October 2015 },
volume = { 128 },
number = { 6 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = { 25-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume128/number6/22878-2015906580/ },
doi = { 10.5120/ijca2015906580 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:20:42.224693+05:30
%A Francesco Corea
%T Why Social Media Matters: The Use of Twitter in Portfolio Strategies
%J International Journal of Computer Applications
%@ 0975-8887
%V 128
%N 6
%P 25-30
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In previous works ([8], [12]), it has already been showed that Twitter and social media in general give an interesting additional predictive power to the models that take them into account. However, the contribution of social media is relatively small on a daily basis, because of the speed and the increasing efficiency of the stock markets. It has been decided then to deal with intraday prices to test whether micro-blogging data may actually be used to implement high-frequency forecasting models. It has been constructed an indicator to earn some insights on the Nasdaq-100’s future movements. Once again, the results are very encouraging: the use of social media data increases the predictive power for general stock market index such as the Nasdaq, and becomes thus an essential building block for any pricing model.

References
  1. Agarwal, A., Xie, B., Vovsha, I., Rambow, O., Passonneau, R. (2011). "Sentiment Analysis of Twitter Data". LSM ’11 Proceedings of the Work- shop on Languages in Social Media: 30-38.
  2. Antweiler, W., Frank, M.Z. (2004). "Is all that talk just noise? The information content of internet stock message boards". The Journal of Finance 59 (3): 1259-1294.
  3. Asur, S., Huberman, B. (2010). "Predicting the Future With Social Media". Web Intelligence and Intelligent Agent Technology (WI-IAT), 2010 IEEE/WIC/ACM International Conference on Volume 1: 492-499.
  4. Baker, M., Wurgler, J. (2006). "Investor Sentiment and the Cross-Section of Stock Returns". The Journal of Finance Volume 61 (4): 1645-1680.
  5. Baker, M., Wurgler, J. (2007). "Investor Sentiment in the Stock Market". Journal of Economics Perspectives Volume 21, No. 2: 129-151.
  6. Barber, B., Lehavy, R., McNichols, M., Trueman, B. (2001). "Can Investors Profit from the Prophets? Security Analyst Recommendations and Stock Returns". The Journal of Finance 56 (2): 531-563.
  7. Bollen, J., Mao, H. (2011). "Twitter Mood as a Stock Market Predictor". IEEE Computer. Vol. 44 (10): 91-94.
  8. Bollen, J., Mao, H., Zeng, X. (2011). "Twitter mood predicts the stock market". Journal of Computational Science Volume 2 (1): 1-8.
  9. Bordino, I., Battiston, S., Caldarelli, G., Cristelli, M., Ukkonen, A., Weber, I. (2012). "Web search queries can predict stock market volumes". PloS one 7 (7), e40014.
  10. Brown, E. D. (2012). "Will Twitter Make You a Better Investor? A Look at Sentiment, User Reputation and Their Effect on the Stock Market". SAIS 2012 Proceedings. Paper 7.
  11. Choi, H., Varian, H. (2012). "Predicting the Present with Google Trends". Economic Record, Special Issue: Selected Papers from the 40th Australian Conference of Economists Volume 88, Issue Supplement 1, pages 2-9.
  12. Corea, F., Cervellati, E. M. (2015). "The Power of Micro-Blogging: How to Use Twitter for Predicting the Stock Market". Eurasian Journal of Economics and Finance, 3 (4): 1-6.
  13. Culotta, A. (2010). "Towards detecting influenza epidemics by analysing Twitter messages". Proceedings of the First Workshop on Social Media Analytics: 115-122.
  14. Da, Z., Engelberg, J., Gao, P. (2012). "In search of attention". The Journal of Finance 66 (5): 1461-1499.
  15. Da, Z., Engelberg, J., Gao, P. (2015). "The Sum of All FEARS Investor Sentiment and Asset Prices". Review of Financial Studies 28 (1), 1-32.
  16. De Choudhury, M., Sundaram, H., John, A., Seligmann, D. D. (2008). "Can blog communication dynamics be correlated with stock market activity?". Proceedings of the nineteenth ACM conference on Hypertext and hypermedia: 55-60.
  17. Dhar, V., Chang, E. A. (2009). "Does Chatter Matter? The Impact of User-Generated Content on Music Sales". Journal of Interactive Marketing Volume 23 (4): 300-307.
  18. Fisher, K. L., Statman, M. (2000). "Investor Sentiment and Stock Returns". Financial Analysts Journal, Vol. 56, No. 2: 16-23.
  19. Koski, J. L., Rice, E. M., Tarhouni, A. (2008). "Day Trading and Volatility: Evidence from Message Board Postings in 2002 vs. 1999". Working paper under review by Management Science.
  20. Lavrenko, V., Schmill, M., Lawrie, D., Ogilvie, P., Jensen, D., Allan, J. (2000). "Language Models for Financial News Recommendation". Proceedings of the ninth international conference on Information and knowledge management: 389-396.
  21. Mao, H., Bollen, J., Counts, S. (2011)."Predicting Financial Markets: Comparing Survey, News, Twitter and Search Engine Data". Working Paper.
  22. Mao, H., Counts, S., Bollen, J. (2015). "Quantifying the effects of online bullishness on international financial markets". ECB Statistics Paper Series, 9.
  23. Mishne, G., Glance, N. (2006). "Predicting movie sales from blogger sentiment". In AAAI 2006 Spring Symposium on Computational Approaches to Analysing Weblogs.
  24. Mittal, A., Goel, A. (2012). "Stock Prediction Using Twitter Sentiment Analysis". Working Paper Stanford University CS 229.
  25. Nofsinger, J.R. (2005). "Social mood and financial economics". The Journal of Behavioural Finance 6 (3): 144-160.
  26. Oh, C., Sheng, O. R. L. (2011). "Investigating predictive power of stock micro blog sentiment in forecasting future stock price directional movement". ICIS 2011 Proceedings.
  27. Oliveira, N., Cortez, P., Areal, N. (2013). "On the Predictability of Stock Market Behaviour Using StockTwits Sentiment and Posting Volume". Progress in Artificial Intelligence, Lecture Notes in Computer Science Volume 8154: 355-365.
  28. Peterson, R.L. (2007). "Affect and financial decision-making: How neuroscience can inform market participants". The Journal of Behavioural Finance 8 (2): 70-78.
  29. Ruiz, E. J., Hristidis, V., Castillo, C., Gionis, A. (2012). "Correlating financial time series with micro-blogging activity". Proceedings of the fifth ACM international conference on Web search and data mining: 513-522.
  30. Schumaker, R.P., Chen, H. (2009). "Textual analysis of stock market prediction using breaking financial news: The azfin text system". ACM Transactions on Information Systems (TOIS) 27 (2), 12.
  31. Sprenger, T., Welpe, I. (2010). "Tweets and trades: The information content of stock microblogs". Social Science Research Network Working Paper Series: 1-89.
  32. Tetlock, P. C. (2007). "Giving content to investor sentiment: The role of media in the stock market". The Journal of Finance 62 (3): 1139-1168.
  33. Tetlock, P. C., Saar-Tsechansky, M., Macskassy, S. (2008). "More Than Words: Quantifying Language to Measure Firms’ Fundamentals". Journal of Finance 63, 1437-1467.
  34. Tumasjan, A., Sprenger, T. O., Sandner, P. G., Welpe, I. M. (2010). "Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment". Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media.
  35. Zhang, L. (2013). "Sentiment Analysis on Twitter with Stock Price and Significant Keyword Correlation". Thesis, Department of Computer Science, The University of Texas at Austin.
Index Terms

Computer Science
Information Sciences

Keywords

micro-blogging sentiment analysis forecasting Twitter index.