Pessimism and uncertainty of the news and investor’s behavior in Brazil

Main Article Content

Fernando Caio Galdi
Arthur Martins Gonçalves

Abstract

How investors impound qualitative information released by the media into prices, especially in a less efficient market such as Brazil, helps understand the types of news most sensitive to investors. This study investigates the relationship between the content of the daily editions of specialized financial media in Brazil, captured by a metric of textual tone, and returns and volatility of market indices. Our database contains 1,237 daily editions of the newspaper “Valor Econômico,” between 01/02/2012 and 12/30/2016. The results indicate that the market put more weight on the words “uncertainty” and “negative” in the news. “Uncertainty" has negative relation to current market-returns and weak evidence that news with “negative” terms have positive associations with current market-volatility. The evidences obtained point to the existence of informative content in the news published by the specialized media in Brazil, especially with the words “negative” and “uncertainty.”

Downloads

Download data is not yet available.

 

 

 

 

Metrics

Metrics Loading ...

Article Details

How to Cite
GALDI, F. C.; GONÇALVES, A. M. Pessimism and uncertainty of the news and investor’s behavior in Brazil. RAE - Revista de Administracao de Empresas , [S. l.], v. 58, n. 2, p. 130–148, 2018. DOI: 10.1590/S0034-759020180203. Disponível em: https://periodicos.fgv.br/rae/article/view/74642. Acesso em: 4 dec. 2023.
Section
Articles

References

Amihud, Y. (2002). Illiquidity and stock returns: Cross-section and timeseries effects. Journal of Financial Markets, 5(1), 31-56. doi:10.1016/ S1386-4181(01)00024-6

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.

Associação Nacional de Jornais. (2017, Junho 10). Os maiores jornais do Brasil de circulação paga, por ano. Recuperado de http://www.anj. org.br/maiores-jornais-do-brasil/

Barberis, N., Shleifer, A., & Vishny, R. (1998). A model of investor sentiment. Journal of Financial Economics, 49(3), 307-343. doi:10.1016/S0304-405X(98)00027-0

BM&FBovespa. (2015a). Índice Bovespa (Ibovespa). Composição/ Carteira do índice. Recuperado de http://www.bmfbovespa.com.br/ indices/ResumoIndice.aspx?Indice=Ibovespa&Idioma=pt-br

BM&FBovespa. (2015b). Índice Brasil Amplo (IBrA). Composição/ Carteira do índice. Recuperado de http://www.bmfbovespa.com.br/ indices/ResumoCarteiraTeorica.aspx?Indice=IBrA&idioma=pt-brr

BM&FBovespa. (2015c). Índice Brasil Amplo (IBrA). Estatísticas históricas. Recuperado de http://www.bmfbovespa.com.br/indices/ResumoEvolucaoDiaria.aspx?Indice=IBrA&idioma=pt-br

Bogle, S. A., & Potter, W. D. (2015). SentAMaL: A sentiment analysis machine learning stock predictive model. Proceedings on the International Conference on Artificial Intelligence (ICAI). The Steering Committee of the World Congress in Computer Science, Computer Engineering and Applied Computing. Las Vegas, USA: WorldComp.

Boussaidi, R. (2013). Representativeness heuristic, investor sentiment and overreaction to accounting earnings: The case of the Tunisian stock market. Procedia-Social and Behavioral Sciences, 81, 9-21. doi:10.1016/j.sbspro.2013.06.380

Bushman, R. M., Williams, C. D., & Wittenberg-Moerman, R. (2016). The informational role of the media in private lending. Journal of Accounting Research, 55(1), 115-152. doi:10.1111/1475-679X.12131

Cambria, E. (2016). Affective computing and sentiment analysis. IEEE Intelligent Systems, 31(2), 102-107. doi:10.1109/MIS.2016.31

Carhart, M. M. (1997). On persistence in mutual fund performance. The Journal of Finance, 52(1), 57-82. doi:10.1111/j.1540-6261.1997.tb03808.x

Chen, K. T., Lu, H-M., Chen, T-J., Li, S-H., Lian, J-S., & Chen, H. (2011). Giving context to accounting numbers: The role of news coverage. Decision Support Systems, 50(4), 673-679. doi:10.1016/j. dss.2010.08.025

Cochrane, J. H., & Culp, C. L. (2003). Equilibrium asset pricing and discount factors: Overview and implications for derivatives valuation and risk management. In P. Field (Ed.), The Growth of Risk Management: A history (pp. 57-92). London, UK: Risk Books.

Davolos, L. C., Rogers, P., Silva, W. M. Da, & Oliveira, M. A. (2013). O que determina o preço das ações? Exame empírico do mercado brasileiro pré-subprime (1994-2007). REA-Revista Eletrônica de Administração, 12(1), 48-67.

Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3-56. doi:10.1016/0304-405X(93)90023-5

Fang, L., & Peress, J. (2009). Media coverage and the cross-section of stock returns. The Journal of Finance, 64(5), 2023-2052. doi:10.1111/j.1540-6261.2009.01493.x

Instituto de Pesquisa Econômica Aplicada. (2015). Índice de ações Ibovespa – Fechamento. Recuperado de http://www.ipeadata.gov.br/

Liu, B., & Zhang, L. (2012). A survey of opinion mining and sentiment analysis. In C. Aggarwal & C. Zhai (Eds.) Mining text data (pp. 415- 463). Boston, USA: Springer.

Loughran, T., & McDonald, B. (2011). When is a liability not a liability? Textual analysis, dictionaries, and 10-Ks. The Journal of Finance, 66(1), 35-65. doi:10.1111/j.1540-6261.2010.01625.x

Mitra, G., & Mitra, L. (Eds.). (2011). The handbook of news analytics in finance. Hoboken, USA: John Wiley & Sons.

Nascimento, P., Osiek, B. A., & Xexéo, G. (2015). Análise de sentimento de Tweets com foco em notícias. Revista Eletrônica de Sistemas de Informação, 14(2), 1-14. doi:10.21529/RESI.2015.1402002

Pagliarussi, M. S., Aguiar, M. O., & Galdi, F. C. (2016). Sentiment analysis in annual reports from Brazilian companies listed at the BM&FBovespa. BASE-Revista de Administração e Contabilidade da Unisinos, 13(1), 53-64.

Porshnev, A., Redkin, I., & Shevchenko, A. (2013). Machine learning in prediction of stock market indicators based on historical data and data from twitter sentiment analysis. 13th IEEE International Conference on Data Mining Workshops. Washington, USA: IEEE.

Rogers, J. L., Skinner, D. J., & Zechman, S. L. (2015). The role of the media in disseminating insider-trading activity (Working Paper, No. 13-34). University of Colorado, Boulder, USA.

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. doi:10.1111/j.1540-6261.2007.01232.x

Tetlock, P. C., Saar-Tsechansky, M., & Mackskassy, S. (2008). More than words: Quantifying language to measure firms’ fundamentals. The Journal of Finance, 63(3), 1437-1467. doi:10.1111/j.1540- 6261.2008.01362.x

Tripathy, A., Agrawal, A., & Rath, S. K. (2016). Classification of sentiment reviews using n-gram machine learning approach. Expert Systems with Applications, 57, 117-126. doi:10.1016/j.eswa.2016.03.028

Valor Econômico. (2012, Maio 15). Edição impressa. Recuperado de http://www.valor.com.br/impresso/

Valor Econômico. (2013, Maio 15). Edição impressa. Recuperado de http://www.valor.com.br/impresso/