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Predicting Financial Markets: Comparing Survey, News, Twitter and Search Engine Data

Citations

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Cited by:

  1. Thomas Forss & Peter Sarlin, 2017. "News-sentiment networks as a risk indicator," Papers 1706.05812, arXiv.org, revised May 2018.
  2. Peter Gabrovšek & Darko Aleksovski & Igor Mozetič & Miha Grčar, 2017. "Twitter sentiment around the Earnings Announcement events," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-21, February.
  3. David Garcia & Claudio Juan Tessone & Pavlin Mavrodiev & Nicolas Perony, 2014. "The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy," Papers 1408.1494, arXiv.org.
  4. Ji, Qiang & Guo, Jian-Feng, 2015. "Oil price volatility and oil-related events: An Internet concern study perspective," Applied Energy, Elsevier, vol. 137(C), pages 256-264.
  5. Tushar Rao & Saket Srivastava, 2012. "Modeling Movements in Oil, Gold, Forex and Market Indices using Search Volume Index and Twitter Sentiments," Papers 1212.1037, arXiv.org.
  6. Thierry Warin & Nathalie De Marcellis-Warin & William Sanger & Bertrand Nembot & Venus Hosseinali Mirza, 2015. "Corporate reputation and social media: a game theory approach," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 9(1), pages 1-22.
  7. Sushant Chari & Purva Hegde Desai & Nilesh Borde & Babu George, 2023. "Aggregate News Sentiment and Stock Market Returns in India," JRFM, MDPI, vol. 16(8), pages 1-18, August.
  8. Ali Asgarov, 2023. "Predicting Financial Market Trends using Time Series Analysis and Natural Language Processing," Papers 2309.00136, arXiv.org.
  9. Paolo Cremonesi & Chiara Francalanci & Alessandro Poli & Roberto Pagano & Luca Mazzoni & Alberto Maggioni & Mehdi Elahi, 2018. "Social Network based Short-Term Stock Trading System," Papers 1801.05295, arXiv.org.
  10. Ying Liu & Yibing Chen & Sheng Wu & Geng Peng & Benfu Lv, 2015. "Composite leading search index: a preprocessing method of internet search data for stock trends prediction," Annals of Operations Research, Springer, vol. 234(1), pages 77-94, November.
  11. Al-Nasseri, Alya & Menla Ali, Faek & Tucker, Allan, 2021. "Investor sentiment and the dispersion of stock returns: Evidence based on the social network of investors," International Review of Financial Analysis, Elsevier, vol. 78(C).
  12. Justina Deveikyte & Helyette Geman & Carlo Piccari & Alessandro Provetti, 2020. "A Sentiment Analysis Approach to the Prediction of Market Volatility," Papers 2012.05906, arXiv.org.
  13. Andrew Todd & James Bowden & Yashar Moshfeghi, 2024. "Text‐based sentiment analysis in finance: Synthesising the existing literature and exploring future directions," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(1), March.
  14. Guo, Jian-Feng & Ji, Qiang, 2013. "How does market concern derived from the Internet affect oil prices?," Applied Energy, Elsevier, vol. 112(C), pages 1536-1543.
  15. Alexander Gilgur & Jose Emmanuel Ramirez-Marquez, 2020. "Using Deductive Reasoning to Identify Unhappy Communities," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(2), pages 581-605, November.
  16. Halousková, Martina & Stašek, Daniel & Horváth, Matúš, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Finance Research Letters, Elsevier, vol. 50(C).
  17. Stanislaus Maier-Paape & Andreas Platen, 2015. "Lead-Lag Relationship using a Stop-and-Reverse-MinMax Process," Papers 1504.06235, arXiv.org.
  18. Damien Challet & Ahmed Bel Hadj Ayed, 2014. "Do Google Trend data contain more predictability than price returns?," Papers 1403.1715, arXiv.org.
  19. Qihui Xie & Yanan Xue, 2022. "The Prediction of Public Risk Perception by Internal Characteristics and External Environment: Machine Learning on Big Data," IJERPH, MDPI, vol. 19(15), pages 1-20, August.
  20. Jaroslav Bukovina, 2016. "Social Media and Capital Markets – an Overview," MENDELU Working Papers in Business and Economics 2016-57, Mendel University in Brno, Faculty of Business and Economics.
  21. Matija Piv{s}korec & Nino Antulov-Fantulin & Petra Kralj Novak & Igor Mozetiv{c} & Miha Grv{c}ar & Irena Vodenska & Tomislav v{S}muc, 2014. "News Cohesiveness: an Indicator of Systemic Risk in Financial Markets," Papers 1402.3483, arXiv.org.
  22. Stanislaus Maier-Paape & Andreas Platen, 2016. "Lead–Lag Relationship Using a Stop-and-Reverse-MinMax Process," Risks, MDPI, vol. 4(3), pages 1-20, July.
  23. Arezoo Hatefi Ghahfarrokhi & Mehrnoush Shamsfard, 2020. "Tehran stock exchange prediction using sentiment analysis of online textual opinions," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(1), pages 22-37, January.
  24. Jung, Sang Hoon & Jeong, Yong Jin, 2021. "Examining stock markets and societal mood using Internet memes," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
  25. Jaroslav Bukovina, 2015. "Sentiment of a society and large-cap stock liquidity," MENDELU Working Papers in Business and Economics 2015-56, Mendel University in Brno, Faculty of Business and Economics.
  26. Saurabh, Samant & Dey, Kushankur, 2020. "Unraveling the relationship between social moods and the stock market: Evidence from the United Kingdom," Journal of Behavioral and Experimental Finance, Elsevier, vol. 26(C).
  27. Qingguo Ma & Wuke Zhang, 2015. "Public Mood and Consumption Choices: Evidence from Sales of Sony Cameras on Taobao," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-11, April.
  28. Li, Zhenghui & Chen, Liming & Dong, Hao, 2021. "What are bitcoin market reactions to its-related events?," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 1-10.
  29. Bianconi, Marcelo & Hua, Xiaxin & Tan, Chih Ming, 2015. "Determinants of systemic risk and information dissemination," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 352-368.
  30. Audrino, Francesco & Sigrist, Fabio & Ballinari, Daniele, 2020. "The impact of sentiment and attention measures on stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 334-357.
  31. Eric. W. K. See-To & Yang Yang, 2017. "Market sentiment dispersion and its effects on stock return and volatility," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(3), pages 283-296, August.
  32. Qing Liu & Hosung Son, 2024. "Data selection and collection for constructing investor sentiment from social media," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
  33. Gabriele Ranco & Ilaria Bordino & Giacomo Bormetti & Guido Caldarelli & Fabrizio Lillo & Michele Treccani, 2014. "Coupling news sentiment with web browsing data improves prediction of intra-day price dynamics," Papers 1412.3948, arXiv.org, revised Dec 2015.
  34. Gabriele Ranco & Ilaria Bordino & Giacomo Bormetti & Guido Caldarelli & Fabrizio Lillo & Michele Treccani, 2016. "Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-14, January.
  35. Kraaijeveld, Olivier & De Smedt, Johannes, 2020. "The predictive power of public Twitter sentiment for forecasting cryptocurrency prices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
  36. Gabriele Ranco & Darko Aleksovski & Guido Caldarelli & Miha Grčar & Igor Mozetič, 2015. "The Effects of Twitter Sentiment on Stock Price Returns," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-21, September.
  37. Francesco Corea & Enrico Maria Cervellati, 2015. "The Power of Micro-Blogging: How to Use Twitter for Predicting the Stock Market," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 3(4), pages 1-7.
  38. Lars Steinert & Christian Herff, 2018. "Predicting altcoin returns using social media," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-12, December.
  39. Brian J Goode & Siddharth Krishnan & Michael Roan & Naren Ramakrishnan, 2015. "Pricing a Protest: Forecasting the Dynamics of Civil Unrest Activity in Social Media," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-25, October.
  40. Tsapeli, Fani & Musolesi, Mirco & Tino, Peter, 2017. "Non-parametric causality detection: An application to social media and financial data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 139-155.
  41. Arezoo Hatefi Ghahfarrokhi & Mehrnoush Shamsfard, 2019. "Tehran Stock Exchange Prediction Using Sentiment Analysis of Online Textual Opinions," Papers 1909.03792, arXiv.org, revised Sep 2019.
  42. Heleen Brans & Bert Scholtens, 2020. "Under his thumb the effect of president Donald Trump’s Twitter messages on the US stock market," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-11, March.
  43. Li, Yue & W. Goodell, John & Shen, Dehua, 2021. "Does happiness forecast implied volatility? Evidence from nonparametric wave-based Granger causality testing," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 113-122.
  44. Al-Nasseri, Alya & Menla Ali, Faek, 2018. "What does investors' online divergence of opinion tell us about stock returns and trading volume?," Journal of Business Research, Elsevier, vol. 86(C), pages 166-178.
  45. Yousra Trichilli & Mouna Abdelhédi & Mouna Boujelbène Abbes, 2020. "The thermal optimal path model: Does Google search queries help to predict dynamic relationship between investor’s sentiment and indexes returns?," Journal of Asset Management, Palgrave Macmillan, vol. 21(3), pages 261-279, May.
  46. repec:men:wpaper:57_2015 is not listed on IDEAS
  47. Jamal Bouoiyour & Refk Selmi, 2018. "Terrorism, Colonialism and Voter Psychology: Evidence from the United Kingdom," Working Papers hal-01687662, HAL.
  48. Fang, Jianchun & Gozgor, Giray & Lau, Chi-Keung Marco & Lu, Zhou, 2020. "The impact of Baidu Index sentiment on the volatility of China's stock markets," Finance Research Letters, Elsevier, vol. 32(C).
  49. Lyócsa, Štefan & Halousková, Martina & Haugom, Erik, 2023. "The US banking crisis in 2023: Intraday attention and price variation of banks at risk," Finance Research Letters, Elsevier, vol. 57(C).
  50. Panagiotis Papaioannou & Lucia Russo & George Papaioannou & Constantinos Siettos, 2013. "Can social microblogging be used to forecast intraday exchange rates?," Netnomics, Springer, vol. 14(1), pages 47-68, November.
  51. Shen, Shulin & Xia, Le & Shuai, Yulin & Gao, Da, 2022. "Measuring news media sentiment using big data for Chinese stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 74(C).
  52. Felix Ming Fai Wong & Zhenming Liu & Mung Chiang, 2014. "Stock Market Prediction from WSJ: Text Mining via Sparse Matrix Factorization," Papers 1406.7330, arXiv.org.
  53. Suppawong Tuarob & Poom Wettayakorn & Ponpat Phetchai & Siripong Traivijitkhun & Sunghoon Lim & Thanapon Noraset & Tipajin Thaipisutikul, 2021. "DAViS: a unified solution for data collection, analyzation, and visualization in real-time stock market prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-32, December.
  54. Zhang, Xiaotao & Li, Guoran & Li, Yishuo & Zou, Gaofeng & Wu, Ji George, 2023. "Which is more important in stock market forecasting: Attention or sentiment?," International Review of Financial Analysis, Elsevier, vol. 89(C).
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