COVID-19 e causalidade na volatilidade do mercado acionário chileno

Autores

DOI:

https://doi.org/10.18046/j.estger.2021.159.4412

Palavras-chave:

COVID-19, causalidade de Granger, volatilidade, mercados emergentes, incerteza

Resumo

Nesta pesquisa, a causalidade no sentido de Granger unidirecional foi estudada, desde o Infectious Disease Equity Market Volatility Tracker até a volatilidade do mercado acionário chileno, que é modelado por um procedimento autorregressivo condicional. Aplicam-se três testes de causalidade e, de forma complementar, o teste de bicorrelação cruzada. Os resultados indicam que esse índice causa volatilidade no mercado com a maioria dos testes aplicados. Isso indica a relevância potencial de ter este novo indicador para os agentes que participam dos mercados financeiros, incluindo reguladores, empresas e corretoras de valores. Adicionalmente, os resultados são consistentes com a evidência sobre a capacidade preditiva do índice sobre a volatilidade do preço do petróleo e outros índices.

Downloads

Os dados de download ainda não estão disponíveis.

Referências

Alan, N. S., Engle, R. F. y Karagozoglu, A. K. (2020). Multi-regime forecasting model for the impact of COVID-19 pandemic on volatility in global equity markets. Available at SSRN 3646520. http://dx.doi.org/10.2139/ssrn.3646520

Al-Awadhi, A. M., Alsaifi, K., Al-Awadhi, A. y Alhammadi, S. (2020). Death and contagious infectious diseases: Impact of the COVID-19 virus on stock market returns. Journal of behavioral and experimental finance, 27, 100326. https://doi.org/10.1016/j.jbef.2020.100326

Amar, A. B., Bélaïd, F., Youssef, A. B., Chiao, B. y Guesmi, K. (2021). The unprecedented reaction of equity and commodity markets to COVID-19. Finance Research Letters, 38, 101853. https://doi.org/10.1016/j.frl.2020.101853

Ashraf, B. N. (2020). Stock markets’ reaction to COVID-19: Cases or fatalities? Research in International Business and Finance, 101249. https://doi.org/10.1016/j.ribaf.2020.101249

Bahrini, R. y Filfilan, A. (2020). Impact of the novel coronavirus on stock market returns: evidence from GCC countries. Quantitative Finance and Economics, 4(4), 640-652. https://doi.org/10.3934/QFE.2020029

Baker, S. R., Bloom, N. y Terry, S. J. (2020a). Using disasters to estimate the impact of uncertainty (N.o w27167). National Bureau of Economic Research. https://doi.org/10.3386/w27167

Baker, S. R., Bloom, N., Davis, S. J., Kost, K., Sammon, M. y Viratyosin, T. (2020b). The unprecedented stock market reaction to COVID-19. The Review of Asset Pricing Studies, 10(4), 742-758. https://doi.org/10.1093/rapstu/raaa008

Beck, T., Degryse, H. y Kneer, C. (2014). Is more finance better? Disentangling intermediation and size effects of financial systems. Journal of Financial Stability 10, 50-64. https://doi.org/10.1016/j.jfs.2013.03.005

Bildirici, M. E. y Turkmen, C. (2015). Nonlinear causality between oil and precious metals. Resources Policy, 46, 202-211. https://doi.org/10.1016/j.resourpol.2015.09.002

Bouri, E., Cepni, O., Gabauer, D. y Gupta, R. (2020a). Return connectedness across asset classes around the COVID-19 outbreak. International Review of Financial Analysis, 101646. https://doi.org/10.1016/j.irfa.2020.101646

Bouri, E., Demirer, R., Gupta, R. y Pierdzioch, C. (2020b). Infectious diseases, market uncertainty and oil market volatility. Energies, 13(15), 1-8. https://doi.org/10.3390/en13164090

Brooks, C. y Hinich, M. J. (1999). Cross-correlations and cross-bicorrelations in Sterling exchange rates. Journal of Empirical Finance, 6(4), 385-404.https://doi.org/10.1016/S0927-5398(99)00007-9

Brooks, C. y Hinich, M. J. (2001). Bicorrelations and cross-bicorrelations as non-linearity tests and tools for exchange rate forecasting. Journal of Forecasting, 20(3), 181-196. https://doi.org/10.1002/1099-131X(200104)20:3<181::AID-FOR781>3.0.CO;2-R

Brugger, S. y Ortiz, E. (2012). Mercados accionarios y su relación con la economía real en América Latina. Problemas del Desarrollo, 43(168), 63-93. http://www.scielo.org.mx/pdf/prode/v43n168/v43n168a4.pdf

Caporale, G. M., Gil-Alana, L. A. y Tripathy, T. (2020). Volatility persistence in the Russian stock market. Finance Research Letters, 32, 101216. https://doi.org/10.1016/j.frl.2019.06.014

Caporale, G. M., Howells, P. y Soliman, A. M. (2005). Endogenous growth models and stock market development: evidence from four countries. Review of Development Economics, 9(2), 166-176. https://doi.org/10.1111/j.1467-9361.2005.00270.x

Cascaldi-Garcia, D., Sarisoy, C., Londono-Yarce, J. M., Rogers, J. H., Datta, D., Ferreira, T. y Zer, I. (2020). What is certain about uncertainty? International Finance Discussion Papers 1294. Washington: Board of Governors of the Federal Reserve System. https://doi.org/10.17016/IFDP.2020.1294

Comisión Económica para América Latina y el Caribe (2020). Informe sobre el impacto económico en América Latina y el Caribe de la enfermedad por coronavirus (COVID-19). Recuperado el 26 de marzo de 2020, de: https://n9.cl/jyka

Comisión para el Mercado Financiero - CMF. (2020). CMF - Educa, Portal de Educación Financiera Recuperado el 15 de octubre de 2020, de: https://n9.cl/jov4h

Concha, Á. y Taborda, R. (2014). Insurance use and economic growth in Latin America. Some panel data evidence. Lecturas de economía, (81), 31-45. https://doi.org/10.17533/udea.le.n81a2

Coronado, S., Romero-Meza, R. y Venegas-Martínez, F. (2017). Non-linear multivariate dependence between the Mexican stock market index and the exchange rate: Efficiency hypothesis and political cycle in Mexico. Revista Mexicana de Economía y Finanzas, 12(1). https://doi.org/10.21919/remef.v12i1.17

Coronado, S., Fullerton, T. M. y Rojas, O. (2018a). A nonlinear empirical analysis of oil price co-movements. International Journal of Energy Economics and Policy, 8(3), 290-294.

Coronado, S., Jiménez-Rodríguez, R. y Rojas, O. (2018b). An empirical analysis of the relationships between crude oil, gold and stock markets. The Energy Journal, 39(Special Issue 1). https://doi.org/10.5547/01956574.39.SI1.scor

Coronado, S., Rojas, O., Romero-Meza, R., Serletis, A. y Chiu, L. V. (2018c). Crude oil and biofuel agricultural commodity prices. En F. Jawadi (Ed.), Uncertainty, expectations and asset price dynamics, dynamic modeling and econometrics in economics and finance (pp. 107-123). Cham: Springer. https://doi.org/10.1007/978-3-319-98714-9_5

Diks, C. y Panchenko, V. (2006). A new statistic and practical guidelines for nonparametric Granger causality testing. Journal of Economic Dynamics and Control, 30(9-10), 1647-1669. https://doi.org/10.1016/j.jedc.2005.08.008

D’Orazio, P. y Dirks, M. W. (2020). COVID-19 and financial markets: Assessing the impact of the coronavirus on the eurozone (N.o 859). Ruhr Economic Papers. https://doi.org/10.4419/86788995

Duarte, J. B. D. y Pérez-Iñigo, J. M. M. (2014). Comprobación de la eficiencia débil en los principales mercados financieros latinoamericanos. Estudios Gerenciales, 30(133), 365-375.https://doi.org/10.1016/j.estger.2014.05.005

Edwards, S. y Susmel, R. (1999). Contagion and volatility in the 1990s (N.o 153). Universidad del CEMA. Recuperado el 2 de octubre de 2020, de: https://ucema.edu.ar/publicaciones/download/documentos/153.pdf

El-Khatib, R. y Samet, A. (2020). Impact of COVID-19 on Emerging Markets. Available at SSRN 3685013. http://dx.doi.org/10.2139/ssrn.3685013

Emenogu, N. G., Adenomon, M. O. y Nweze, N. O. (2020). On the volatility of daily stock returns of Total Nigeria Plc: evidence from GARCH models, value-at-risk and backtesting. Financial Innovation, 6(1), 1-25. https://doi.org/10.1186/s40854-020-00178-1

Enisan, A. A. y Olufisayo, A. O. (2009). Stock market development and economic growth: Evidence from seven sub-Sahara African countries. Journal of economics and business, 61(2), 162-171. https://doi.org/10.1016/j.jeconbus.2008.05.001

Forbes Staff (2020). Mercados globales caen tras contagio de Trump. Forbes, Colombia. Recuperado el 2 de octubre de 2020, de: https://n9.cl/g9ov

Gherghina, S. C., Armeanu, D. Ș. y Joldeș, C. C. (2020). Stock market reactions to Covid-19 pandemic outbreak: Quantitative evidence from ARDL bounds tests and Granger causality analysis. International Journal of Environmental Research and Public Health, 17(18), 6729. https://doi.org/10.3390/ijerph17186729

Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424. https://doi.org/10.2307/1912791

Gormsen, N. J. y Koijen, R. S. (2020). The corona virus, the stock market’s response, and growth expectations. Working Paper N.° 2020-22. https://bfi.uchicago.edu/wp-content/uploads/BFI_WP_202022.pdf

Hristu-Varsakelis, D. y Kyrtsou, C. (2010). Testing for granger causality in the presence of chaotic dynamics. Brussels Economic Review, 53(2), 323-327. https://doi.org/10.1016/j.frl.2020.101528

Im, T. L., San, P. W., On, C. K., Alfred, R. y Anthony, P. (2014). Impact of financial news headline and content to market sentiment. International Journal of Machine Learning and Computing, 4(3), 237- 242. https://doi.org/10.7763/IJMLC.2014.V4.418

Kyrtsou, C. y Labys, W. C. (2006). Evidence for chaotic dependence between US inflation and commodity prices. Journal of Macroeconomics, 28(1), 256-266. https://doi.org/10.1016/j.jmacro.2005.10.019

Kyrtsou, C. y Terraza, M. (2003). Is it possible to study chaotic and arch behaviour jointly? Application of a noisy mackey-glass equation with heteroskedastic errors to the Paris stock exchange returns series. Computational Economics, 21(3), 257-276. https://doi.org/10.1023/A:1023939610962

Lanteri, L. N. (2011). Desarrollo del mercado accionario y crecimiento económico. Alguna evidencia para la Argentina. Ensayos de Economía, 21(38), 117-145.

Lei, L., Shang, Y., Chen, Y. y Wei, Y. (2019). Does the financial crisis change the economic risk perception of crude oil traders? A MIDAS quantile regression approach. Finance Research Letters, 30, 341- 351. https://doi.org/10.1016/j.frl.2018.10.016

Li, Y., Liang, C., Ma, F. y Wang, J. (2020). The role of the IDEMV in predicting European stock market volatility during the COVID-19 pandemic. Finance Research Letters, 36, 101749. https://doi.org/https://doi.org/10.1016/j.frl.2020.101749

Mackey, M. y Glass, L. (1977). Oscillation and chaos in physiological control systems. Science, 197(4300), 287-289. https://doi.org/10.1126/science.267326

Marfatia, H. A. (2020). Investors’ risk perceptions in the US and global stock market integration. Research in International Business and Finance, 52, 101169. https://doi.org/10.1016/j.ribaf.2019.101169

Masson, M. P. R. (1998). Contagion: Monsoonal effects, spillovers, and jumps between multiple equilibria (No. 98-142). International Monetary Fund.

Moser, T. (2003). What is international financial contagion? International Finance, 6(2), 157-178. https://doi.org/10.1111/1468-2362.00113

Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica: Journal of the Econometric Society, 347- 370. https://doi.org/10.2307/2938260

Organización Panamericana Mundial de la Salud (2020). Coronavirus. Recuperado el 15 de septiembre de 2020, de: https://n9.cl/g59c

Ramelli, S. y Wagner, A. F. (2020). Feverish stock price reactions to COVID-19. The Review of Corporate Finance Studies, 9(3), 622-655. http://dx.doi.org/10.2139/ssrn.3550274

Rastogi, S., Don, J. y V, N. (2018). Volatility estimation using GARCH family of models: Comparison with option pricing. Pacific Business Review International, 10(8), 54-60.

Reyes-García, N. J., Venegas-Martínez, F. y Cruz-Aké, S. (2018). Un análisis comparativo entre GARCH-M, EGARCH y PJ-RS-EV para modelar la volatilidad de Índice de precios y cotizaciones de la Bolsa Mexicana de Valores. Panorama Económico, 14(27), 63-96. https://doi.org/10.29201/pe-ipn.v14i27.210

Romero-Meza, R., Bonilla, C. A. y Hinich, M. J. (2007). Nonlinear event detection in the Chilean stock market. Applied Economics Letters, 14(13), 987-991. https://doi.org/10.1080/13504850600706024

Romero-Meza, R., Coronado, S. y Serletis, A. (2014). Oil and the economy: A cross bicorrelation perspective. Journal of Economic Asymmetries, 11, 91-95. https://doi.org/10.1016/j.jeca.2014.08.003

Topcu, M. y Gulal, O. S. (2020). The impact of COVID-19 on emerging stock markets. Finance Research Letters, 101691. https://doi.org/10.1016/j.frl.2020.101691

Valenzuela, G. y Rodríguez, A. (2015). Interdependencia de mercados y transmisión de volatilidad en Latinoamérica. Innovar: Revista de ciencias administrativas y sociales, 25(55), 157-170. https://doi.org/10.15446/innovar.v25n55.47231

Van de Kauter, M., Breesch, D. y Hoste, V. (2015). Fine-grained analysis of explicit and implicit sentiment in financial news articles. Expert Systems with applications, 42(11), 4999-5010. https://doi.org/10.1016/j.eswa.2015.02.007

Walker, E. (1998). Mercado accionario y crecimiento económico en Chile. Cuadernos de Economía, 35(104), 49-72.

Wei, Y., Bai, L., Yang, K. y Wei, G. (2020) Are industry-level indicators more helpful to forecast industrial stock volatility? Evidence from Chinese manufacturing purchasing managers index. Journal of Forecasting, 40(1), 17-39. https://doi.org/10.1002/for.2696

Zaremba, A., Kizys, R., Aharon, D. Y. y Demir, E. (2020). Infected markets: Novel coronavirus, government interventions, and stock return volatility around the globe. Finance Research Letters, 101597. https://doi.org/10.1016/j.frl.2020.101597

Zhang, D., Hu, M. y Ji, Q. (2020). Financial markets under the global pandemic of COVID-19. Finance Research Letters, 36, 101528. https://doi.org/https://doi.org/10.1016/j.frl.2020.101528

Publicado

2021-04-13

Como Citar

COVID-19 e causalidade na volatilidade do mercado acionário chileno . (2021). Estudios Gerenciales, 37(159), 242-250. https://doi.org/10.18046/j.estger.2021.159.4412