Presidential Communication and Its Impact on the Mexican Stock Market: Evidence Using a Sentiment Analysis Approach

References

• Al Maadid, A., Caporale, G. M., Spagnolo, F., & Spagnolo, N. (2020). The impact of business and political news on the GCC stock markets. Research in International Business and Finance, 52, 101102. https://doi.org/10.1016/j.ribaf.2019.101102
   Web of Science ®Google Scholar
• Alam, M. D., & Uddin, G. (2009). Relationship between interest rate and stock price: empirical evidence from developed and developing countries. International Journal of Business and Management, 4(3), 43–51. https://ssrn.com/abstract=2941281 https://doi.org/10.5539/ijbm.v4n3p43
   Google Scholar
• Bachmann, R., Elstner, S., & Sims, E. R. (2013). Uncertainty and economic activity: Evidence from business survey data. American Economic Journal: Macroeconomics, 5(2), 217–249. https://doi.org/10.1257/mac.5.2.217
   Web of Science ®Google Scholar
• Baker, S., Bloom, N., Davis, S., & Kost, K. (2021). Policy News and Stock Market Volatility. University of Chicago. Baker Friedman Institute for Economics Working Paper No.2019-53, Available at https://doi.org/10.2139/ssrn.3363862
   Google Scholar
• Barsky, R. B. (1986). Why don’t the prices of stocks and bonds move together?. NBER: National Bureau of Economic Research.
   Google Scholar
• Bello, Z. (2013). The association between exchange rates and stock returns. Investment Management and Financial Innovations, 10(3), 40–45.
   Google Scholar
• Ben Ghozzi, B., & Chaibi, H. (2021). Political risks and financial markets: emerging vs developed economies. EuroMed Journal of Business, 17(4), 677–697. https://doi.org/10.1108/EMJB-11-2020-0123
   Web of Science ®Google Scholar
• Bilson, C. M., Brailsford, T. J., & Hooper, V. C. (2002). The explanatory power of political risk in emerging markets. International Review of Financial Analysis, 11(1), 1–27. https://doi.org/10.1016/S0927-538X(01)00020-8
   Google Scholar
• Brans, H., & Scholtens, B. (2020). Under his thumb the effect of President Donald Trump’s Twitter messages on the US stock market. PloS One, 15(3), e0229931. https://doi.org/10.1371/journal.pone.0229931
   PubMed Web of Science ®Google Scholar
• Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. https://doi.org/10.1016/0304-4076(86)90063-1
   Web of Science ®Google Scholar
• Born, J. A., Myers, D. H., & Clark, W. J. (2017). Trump tweets and the efficient market hypothesis. Algorithmic Finance, 6(3-4), 103–109. https://doi.org/10.3233/AF-170211
   Web of Science ®Google Scholar
• Burggraf, T., Fendel, R., & Huynh, T. L. D. (2020). Political news and stock prices: evidence from Trump’s trade war. Applied Economics Letters, 27(18), 1485–1488. https://doi.org/10.1080/13504851.2019.1690626
   Web of Science ®Google Scholar
• Canel, M. J., & Sanders, K. (1970). Para estudiar la comunicación de los gobiernos. Un análisis del estado de la cuestión. Communication & Society, 23(1), 7–48. https://doi.org/10.15581/003.23.36254
   Google Scholar
• Caporale, G. M., Spagnolo, F., & Spagnolo, N. (2016). Macro news and stock returns in the Euro area: a VAR-GARCH-in-mean analysis. International Review of Financial Analysis, 45, 180–188. https://doi.org/10.1016/j.irfa.2016.03.016
   Web of Science ®Google Scholar
• Dimic, N., Orlov, V., & Piljak, V. (2015). The political risk factor in emerging, frontier, and developed stock markets. Finance Research Letters, 15, 239–245. https://doi.org/10.1016/j.frl.2015.10.007
   Web of Science ®Google Scholar
• Davison, J. (2020). (Zero-Shot Learning in Modern NLP. State-of-the-art NLP models for text classifications without annotated data. Joe Davison Blog. https://joeddav.github.io/blog/2020/05/29/ZSL.html
   Google Scholar
• Eeckhoudt, L., Gollier, C., & Schlesinger, H. (2005). Economic and financial decisions under risk. Princeton University Press. (chapter 6, chapter 11)
   Google Scholar
• Fernandez, R., Palma Guizar, B., & Rho, C. (2021). A sentiment-based risk indicator for the Mexican financial sector (No. 2021-04). Latin American Journal of Central Banking, 2(3), 100036. https://doi.org/10.1016/j.latcb.2021.100036
   Google Scholar
• Fradejas, J. M. (2022). Cuentapalabras. Estilometría y análisis de textos en R para filólogos. http://creativecommons.org/licenses/by-nc-sa/4.0/. Creado May.2019, última revisión Dec.2022.
   Google Scholar
• Ge, Q., Kurov, A., & Wolfe, M. H. (2018). Stock market reactions to presidential statements: Evidence from company-specific tweets.
   Google Scholar
• Gitman, L. J., & Zutter, C. J. (2012). Principles of Managerial Finance. (13th ed.) Pearson.
   Google Scholar
• Gjerstad, P., Meyn, P. F., Molnár, P., & Næss, T. D. (2021). Do President Trump’s tweets affect financial markets? Decision Support Systems, 147, 113577. https://doi.org/10.1016/j.dss.2021.113577
   Web of Science ®Google Scholar
• Glosten, L. R., Jagannathan, R., & Runkle, D. E. (1993). On the relation between the expected value and the volatility of the nominal excess return on stocks. The Journal of Finance, 48(5), 1779–1801. https://doi.org/10.1111/j.1540-6261.1993.tb05128.x
   Web of Science ®Google Scholar
• Hamrita, M. E., & Trifi, A. (2011). The relationship between interest rate, exchange rate and stock price: A wavelet analysis. International Journal of Economics and Financial Issues, 1(4), 220–228.
   Google Scholar
• Harvey, C.H. (2004). Country risk components, the cost of capital, and returns in emerging markets. In Wilkin S. (ed.) Country and political risk: practical insights for global finance, Risk Books, London, pp. 71–102.
   Google Scholar
• Hassani, H., Beneki, C., Unger, S., Mazinani, M. T., & Yeganegi, M. R. (2020). Text mining in big data analytics. Big Data and Cognitive Computing, 4(1), 1. https://doi.org/10.3390/bdcc4010001
   Google Scholar
• Hu, M., & Liu, B. (2004). Mining and summarizing customer reviews [Paper presentation]. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD-2004), Seattle, Washington (pp. 168–177). https://emilhvitfeldt.github.io/textdata/reference/lexicon_bing.html https://doi.org/10.1145/1014052.1014073
   Google Scholar
• Kaufmann, D., Kraay, A., & Mastruzzi, M. (2011). The worldwide governance indicators: methodology and analytical issues. Hague Journal on the Rule of Law, 3(02), 220–246. https://doi.org/10.1017/S1876404511200046
   Web of Science ®Google Scholar
• Lehkonen, H., & Heimonen, K. (2015). Democracy, political risks and stock market performance. Journal of International Money and Finance, 59, 77–99. https://doi.org/10.1016/j.jimonfin.2015.06.002
   Web of Science ®Google Scholar
• Madura, J. (2015). Financial Markets and Institutions (11th ed.). Cengage Learning. (Chapter 10, Chapter 11)
   Google Scholar
• Mazzoleni, G. (2014). Comunicación Política. Alianza editorial.
   Google Scholar
• Mc Nair, B. (2018). An introduction to political communication (6th ed.). Routledge Taylor & Francis Group.
   Google Scholar
• Mohammad, M., & Turney, P. (2011). NRC Word emotion association lexicon. (versión 0.92). Public released:10-Jul-2011, última actualización: Agosto-2022. https://saifmohammad.com/
   Google Scholar
• Monterrey, M., & Sánchez, A. (2011). Persistencia de la rentabilidad. Un estudio de sus factores determinantes. Spanish Journal of Finance and Accounting/Revista Española de Financiación y Contabilidad, 40(150), 287–317. https://doi.org/10.1080/02102412.2011.10779704
   Google Scholar
• Nesset, I. Q., Bøgeberg, I., Kjærland, F., & Molden, L. H. (2019). How underlying dimensions of political risk affect excess return in emerging and developed markets. Journal of Emerging Market Finance, 18(1), 80–105. https://doi.org/10.1177/0972652719831540
   Web of Science ®Google Scholar
• Nguyen, M. (2022). Presidential Fiscal News and Cross-section of Stock. Returns. Presidential Fiscal News and Cross-Section of Stock Returns, (December 24, 2022). https://doi.org/10.2139/ssrn.4311379
   Google Scholar
• Nguyen, V. (2019). Dynamics between exchange rates and stock prices: evidence from developed and emerging markets. The International Journal of Business and Finance Research, 13(1), 73–84. https://ssrn.com/abstract=3340191
   Google Scholar
• Nuntachit, N., & Sugunnasil, P. (2022). Do We Need a Specific Corpus and Multiple High-Performance GPUs for Training the BERT Model? An Experiment on COVID-19 Dataset. Machine Learning and Knowledge Extraction, 4(3), 641–664. https://doi.org/10.3390/make4030030
   Google Scholar
• Paramati, S., & Gupta, R. (2013). An empirical relationship between exchange rates, interest rates and stock returns. SSRN Electronic Journal, (56), 168–181. https://doi.org/10.2139/ssrn.2336043
   Google Scholar
• Perloff, R. M. (2014). The dynamics of political communication. Routledge Taylor & Francis Group.
   Google Scholar
• Rehman, M. A., Shah, S. G. M., Cioca, L. I., & Artene, A. (2021). Accentuating the Impacts of Political News on the Stock Price, Working Capital and Performance: An Empirical Review of Emerging Economy. Journal of Economic Forecasting, XXVI(2), 24. 55.
   Google Scholar
• Schwert, G. W. (1989). Business cycles, financial crises and stock returns volatility [Paper presentation]. In Carnegie-Rochester Conference Series on Public Policy, North Holland., vol.31, 83–125 https://doi.org/10.1016/0167-2231(89)90006-7
   Google Scholar
• Sottilotta, C. E. (2013). Political risk: concepts, definitions, challenges. School of Government Luiss Guido Carli, Working paper series.
   Google Scholar
• Soultanaeva, A. (2008). Impact of political news on the Baltic State stock market. Umeå University. department of economics. ISSN-0348-1018;735, URN:urn:nbn:se:umu:diva-39502
   Google Scholar
• Subaşı, F. Ö. (2008). The effect of sovereign rating changes on stock returns and exchange rates. International Research Journal of Finance and Economics, 20, 46–54.
   Google Scholar
• Suleman, M. T. (2012). Stock market reaction to good and bad political news. Asian Journal of Finance & Accounting, 4(1), 299–312. https://doi.org/10.5296/ajfa.v4i1.1705
   Google Scholar
• 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. https://doi.org/10.1111/j.1540-6261.2007.01232.x
   Web of Science ®Google Scholar
• Wang, P., Wang, P., & Liu, A. (2005). Stock return volatility and trading volume: Evidence from the Chinese Stock Market. Journal of Chinese Economic and Business Studies, 3(1), 39–54. https://doi.org/10.1080/14765280500040518
   Google Scholar
• Williams, C. D. (2015). Asymmetric responses to earnings news: A case for ambiguity. The Accounting Review, 90(2), 785–817. https://doi.org/10.2308/accr-50866
   Web of Science ®Google Scholar
• Wintoki, M. B., Linck, J. S., & Netter, J. M. (2012). Endogeneity and the dynamics of internal corporate governance. Journal of Financial Economics, 105(3), 581–606. https://doi.org/10.1016/j.jfineco.2012.03.005
   Web of Science ®Google Scholar
• Wolf, T., Debut, L., Sanh, V., Chaumond, J., Delangue, C., Moi, A., Cistac, P., Rault, T., Louf, R., Funtowicz, M., Davison, J., Shleifer, S., Von Platen, P., Ma, C., Jernite, Y., Plu, J., Xu, C., Le Scao, T., Gugger, S., … Rush, A. (2020)., October). Transformers: State-of the-art natural language processing [Paper presentation]. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: system Demonstrations, In (pp. 38–45). https://doi.org/10.18653/v1/2020.emnlp-demos.6
   Google Scholar
• Yin, W., Hay, J., & Roth, D. (2019). Benchmarking zero-shot text classification: Datasets, evaluation, and entailment approach. arXiv preprint arXiv:1909.00161
   Google Scholar