Have hashtags and cashtags caused a slight reaction to stock returns in financial statements? Has the information content of the financial statements been lost? Case study: S & P500 companies

Document Type : Research Paper


Department of Accounting, Neyshabur Branch, Islamic Azad University, Neyshabur, Iran


The present study examines the effect of conventional hashtags \& cashtags at social networks on the stock returns of S\&P500 companies. In the first step, by creating an optimization portfolio that consists of S\&P 500 companies (Fundamental analysis) abnormal stock returns have been tested. (similar to the 1989 study, Jane A. OU and Stephen H. Penman). Then, in the second step of the research, the effect of reduction free float of companies on abnormal stock returns has been tested. Next, the reduction of the explanatory power of EPS and BV information content as representatives of financial statements (income statement and balance sheet) on stock returns has been tested, and finally, in the fourth step, the effect of conventional hashtags \& cashtags in social networks at the site Stocktwits.com has been tested. The findings of this research showed that: although Jane A. OU and Stephen H. Penman 1989 rejected the hypothesis of a semi-strong efficient market in the companies surveyed, at this study and of course in the S \& P500 companies, the hypothesis of a semi-strong efficient market was confirmed. The effect of declining free float has led to abnormal returns on the S \& P500 companies. The explanatory power of EPS and BV information content on stock returns have diminished over time, which has been due to the hashtags \& cashtags content of financial statements on social networks. In other words, news about the status of companies is rapidly affecting stock returns through virtual networks.


[1] R. Ball and P. Brown, An empirical evaluation of accounting income numbers, J. Account. Res. (1968) 159–178.
[2] I. Bernardo, R. Henriques and V. Lobo, Social market: Stock market and twitter correlation, Int. Conf. Intell.
Decision Technol. (2017) 341–356.
[3] I. Bordino, S. Battiston, G. Caldarelli, M. Cristelli, A. Ukkonen and I. Weber, Web search queries can predict
stock market volumes, PLoS One 7 (2012) 40014.
[4] K. Chan, Y.C. Chan and W.-M. Fong, Free Float and Market Liquidity: Evidence From Hong Kong Government’s
Intervention, Department of Finance, Hong Kong University of Scinces and Technology, 2002.
[5] N.-F. Chen, R. Roll and S.A. Ross, Economic forces and the stock market, J. Bus. (1986) 383–403.
[6] V. Fiala, S. Kapounek and O. Vesel´y, Impact of social media on the stock market: Evidence from tweets, Eur. J.
Bus. Sci. Technol. 1 (2015) 24–35.[7] G.A. Feltham and J. A. Ohlson, Valuation and clean surplus accounting for operating and financial activities,
Contemp. Account. Res. 11 (1995) 689-–732.
[8] R.M. Greenwood, Float Manipulation and Stock Prices, Division of Research, Harvard Business School, 2006.
[9] K. Guo, Y. Sun and X. Qian, Can investor sentiment be used to predict the stock price? Dynamic analysis based
on China stock market, Phys. A: Statist. Mech. Appl. 469 (2017) 390–396.
[10] J.A. Ohlson, Earnings, book values, and dividends in equity valuation, Contemp. Account. Res. 11 (1995) 661–687.
[11] N. Oliveira, P. Cortez and N. Areal, On the predictability of stock market behavior using stocktwits sentiment and
posting volume, Portuguese Conf. Artific. Intell. (2013) 355–365.
[12] J.A. Ou and S.H. Penman, Financial statement analysis and the prediction of stock returns, J. Account. Econ.
11 (1989) 295–329.
[13] S.H. Penman and J.A. Ohlson, Book rate-of-return and prediction of earnings changes: An empirical investigation,
J. Account. Res. 20(2) (1982).
[14] J. Pi˜neiro-Chousa, M. Vizca´─▒no-Gonz´alez and A. M. P´erez-Pico, Influence of social media over the stock market,
Psych. Market. 34 (2017) 101–108.
[15] M. Reed, A study of social network effects on the stock market, J. Behav. Finance 17 (2016) 342–351.
[16] E. J. Ruiz, V. Hristidis, C. Castillo, A. Gionis and A. Jaimes, Correlating financial time series with micro-blogging
activity, Proc. Fifth ACM Int. Conf. Web Search Data Min. (2012) 513–522.
[17] T.O. Sprenger, A. Tumasjan, P.G. Sandner and I.M. Welpe, Tweets and trades: The information content of stock
microblogs, Eur. Financ. Manag. 20 (2014) 926–957.
[18] R. Tumarkin and R.F. Whitelaw, News or noise? Internet postings and stock prices, Financ. Anal. J. 57 (2001)
[19] F. Wang and Y. Xu, What determines Chinese stock returns?, Financ. Anal. J. 60 (2004) 65–77.
[20] P. D. Wysocki, Cheap Talk on the Web: The Determinants of Postings on Stock Message Boards, University of
Michigan Business School Working Paper, 1998.
Volume 13, Issue 1
March 2022
Pages 3029-3057
  • Receive Date: 23 June 2021
  • Revise Date: 23 July 2021
  • Accept Date: 02 August 2021