To the Moon: Analyzing Collective Trading Events on the Wings of Sentiment Analysis
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- John Y. Campbell, 2016.
"Restoring Rational Choice: The Challenge of Consumer Financial Regulation,"
American Economic Review, American Economic Association, vol. 106(5), pages 1-30, May.
- Campbell, John Y., 2016. "Restoring Rational Choice: The Challenge of Consumer Financial Regulation," Scholarly Articles 27413770, Harvard University Department of Economics.
- Campbell, John Y., 2016. "Restoring rational choice: The challenge of consumer financial regulation," Working Paper Series 1897, European Central Bank.
- John Y. Campbell, 2016. "Restoring Rational Choice: The Challenge of Consumer Financial Regulation," NBER Working Papers 22025, National Bureau of Economic Research, Inc.
- Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
- Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
- 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.
- Zheludev, Ilya & Smith, Robert & Aste, Tomaso, 2014. "When can social media lead financial markets?," LSE Research Online Documents on Economics 57376, London School of Economics and Political Science, LSE Library.
- Th'arsis Tuani Pinto Souza & Olga Kolchyna & Philip C. Treleaven & Tomaso Aste, 2015. "Twitter Sentiment Analysis Applied to Finance: A Case Study in the Retail Industry," Papers 1507.00784, arXiv.org, revised Jul 2015.
- Suwan (Cheng) Long & Brian Lucey & Ying Xie & Larisa Yarovaya, 2023. "“I just like the stock”: The role of Reddit sentiment in the GameStop share rally," The Financial Review, Eastern Finance Association, vol. 58(1), pages 19-37, February.
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- Svetlana Lapinova & Alexander Saichev & Maria Tarakanova, 2012. "Volatility estimation based on extremes of the bridge (in Russian)," Quantile, Quantile, issue 10, pages 73-90, December.
- Paresh Kumar Narayan & Sagarika Mishra & Seema Narayan, 2015.
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- Narayan, Paresh Kumar & Mishra, Sagarika & Narayan, Seema, 2015. "New empirical evidence on the bid-ask spread," Working Papers fe_2015_06, Deakin University, Department of Economics.
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This paper has been announced in the following NEP Reports:- NEP-BIG-2023-09-25 (Big Data)
- NEP-MST-2023-09-25 (Market Microstructure)
- NEP-PAY-2023-09-25 (Payment Systems and Financial Technology)
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