Volatility Forecasting and Oil Shocks in Emerging Markets Using Mixed-Frequency Models: A Review

Jesús Enrique Molina Muñoz; Juliana Dussan; Paula Pérez González

doi:10.12804/revistas.urosario.edu.co/empresa/a.14259

##plugins.block.makeSubmission.linkLabel##

Previsão da volatilidade e crise do petróleo nos mercados emergentes por meio de modelos de frequência mista: revisão

DOI: https://doi.org/10.12804/revistas.urosario.edu.co/empresa/a.14259

PDF (English)

Publicado: nov 28, 2025

Edição: v. 28 n. 50 (2026)

Seção Artículo de investigación científica y tecnológica

Palavras-chave: previsão de volatilidade mercados emergentes GARCH-MIDAS choque petrolífero

Autores

Jesús Enrique Molina Muñoz
Tecnológico de Monterrey

Juliana Dussan
Universidad del Rosario

Paula Pérez González
Universidad del Rosario

Resumo

Prever a volatilidade nos mercados emergentes é desafiador por a qualidade dos dados, instabilidade estrutural e relações não lineares complexas. O modelo GARCH-MIDAS surgiu como alternativa promissora, combinando os pontos fortes do garch com dados de frequência mista, essenciais para modelar fenômenos financeiros. Embora essa abordagem seja utilizada para estudar a volatilidade, o estudo dos preços do petróleo e dos choques petrolíferos como impulsionadores dos efeitos da volatilidade nos mercados emergentes é relevante, dada a vulnerabilidade dessas economias a tais choques, sua dependência da receita do petróleo e as perturbações econômicas globais. Objetivo: explorar e analisar a literatura sobre o uso do garch-midas nos mercados emergentes. Metodologia: consistiu numa revisão sistemática da literatura, combinada com uma análise bibliométrica, realizada segundo o prisma, para garantir clareza, transparência e reprodutibilidade. Principais resultados: sugerem que os choques do petróleo têm efeitos positivos e significativos sobre a volatilidade do mercado de ações e são relevantes para os mercados emergentes. Conclusão: GARCH-MIDAS é uma ferramenta promissora para prever a volatilidade e que o estudo das crises do petróleo constitui uma área importante para pesquisas futuras.

Como Citar

Molina Muñoz, J. E., Dussan, J., & Pérez González, P. (2025). Previsão da volatilidade e crise do petróleo nos mercados emergentes por meio de modelos de frequência mista: revisão. Revista Universidad Y Empresa, 28(50), 1–24. https://doi.org/10.12804/revistas.urosario.edu.co/empresa/a.14259

Referências

Alper, A., Ercan, E., & Yılmaz, O. (2012). The impact of economic and financial uncertainty on stock market volatility in Turkey. Economic Modelling, 29(6), 2326–2336. https://doi.org/10.1016/j.econmod.2012.05.030 DOI: https://doi.org/10.1016/j.econmod.2012.05.030

Alper, C. E., Kilinç, M., & Özün, A. (2012). Estimating the impact of oil price shocks on stock market returns: Evidence from Turkey. Economic Systems, 36(2), 278–291. https://doi.org/10.1016/j.ecosys.2011.08.003

Andersen, T. G., Bollerslev, T., Diebold, F. X., & Labys, P. (2003). Modeling and forecasting realized volatility. Econometrica, 71(2), 579–625. https://doi.org/10.1111/1468-0262.00418 DOI: https://doi.org/10.1111/1468-0262.00418

Ayres, J., Izquierdo, A., & Parrado, E. (2025). 2025 Latin American and Caribbean macroeconomic report: Regional opportunities amid global shifts. Inter-American Development Bank. https://doi.org/10.18235/0013475 DOI: https://doi.org/10.18235/0013475

Baumeister, C., & Peersman, G. (2013). Time-varying effects of oil supply shocks on the us economy. American Economic Journal: Macroeconomics, 5(4), 1–28. https://doi.org/10.1257/ mac.5.4.1 DOI: https://doi.org/10.1257/mac.5.4.1

Bernanke, B. S. (1983). Irreversibility, uncertainty, and cyclical investment. The Quarterly Journal of Economics, 98(1), 85–106. https://doi.org/10.2307/1885568 DOI: https://doi.org/10.2307/1885568

Blanchard, O. J., & Galí, J. (2007). The macroeconomic effects of oil shocks: Why are the 2000s so different from the 1970s? [nber Working Paper Series, 13368]. National Bureau of Economic Research. https://doi.org/10.3386/w13368 DOI: https://doi.org/10.2139/ssrn.1008395

Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327. https://doi.org/10.1016/0304-4076(86)90063-1 DOI: https://doi.org/10.1016/0304-4076(86)90063-1

Bollerslev, T. (2023). Reprint of: Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 234, 25–37. https://doi.org/10.1016/j.jeconom.2023.02.001 DOI: https://doi.org/10.1016/j.jeconom.2023.02.001

Bollerslev, T., Engle, R. F., & Nelson, D. B. (1994). arch models. In R. F. Engle & D. L. McFadden (Eds.), Handbook of econometrics (vol. 4, pp. 2959–3038). Elsevier. https://doi.org/10.1016/ S1573-4412(05)80018-2 DOI: https://doi.org/10.1016/S1573-4412(05)80018-2

Cappiello, L., Engle, R. F., & Sheppard, K. (2006). Asymmetric dynamics in the correlations of global equity and bond returns. Journal of Financial Econometrics, 4(4), 537–572. https://doi.org/10.1093/jjfinec/nbl005 DOI: https://doi.org/10.1093/jjfinec/nbl005

Dissou, Y. (2010). Oil price shocks: Sectoral and dynamic adjustments in a small-open developed and oil-exporting economy. Energy Policy, 38(1), 562–572. https://doi.org/10.1016/j.enpol.2009.09.026 DOI: https://doi.org/10.1016/j.enpol.2009.10.008

Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics, 20(3), 339–350. https://doi.org/10.1198/073500102288618487 DOI: https://doi.org/10.1198/073500102288618487

Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. https://doi. org/10.2307/1912773 DOI: https://doi.org/10.2307/1912773

Engle, R. F. (2009). GARCH models with time-varying volatility and correlations. Journal of Business & Economic Statistics, 27(4), 505–521. https://doi.org/10.1198/jbes.2009.07132

Engle, R. F., Ghysels, E., & Sohn, B. (2013). Stock market volatility and macroeconomic fundamentals. Review of Economics and Statistics, 95(3), 776–797. https://doi.org/10.1162/rest_a_00300 DOI: https://doi.org/10.1162/REST_a_00300

Galindo, A., & Nuguer, V. (2023). Fuel-price shocks and inflation in Latin America and the Caribbean. Inter-American Development Bank. https://doi.org/10.18235/0004724 DOI: https://doi.org/10.18235/0004724

Ghani, U., Zhu, B., Ghani, M., & Khan, N. (2023). Role of oil shocks in us stock market volatility: A new insight from garch-midas perspective. Resources Policy, 85, 103933. https://doi.org/10.1016/j.resourpol.2023.103933 DOI: https://doi.org/10.1016/j.resourpol.2023.103933

Ghani, W., Rizvi, S. K. A., & Alam, M. (2023). Oil price shocks and stock market volatility: Evidence from emerging economies. Journal of International Financial Markets, Institutions and Money, 80, 102924. https://doi.org/10.1016/j.intfin.2022.102924

Hamilton, J. D. (1983). Oil and the macroeconomy since World War II. Journal of Political Economy, 91(2), 228–248. https://doi.org/10.1086/261140 DOI: https://doi.org/10.1086/261140

Hollander, H., Gupta, R., & Wohar, M. E. (2019). The impact of oil shocks in a small open economy New-Keynesian dynamic stochastic general equilibrium model for an oil-importing country: The case of South Africa. Emerging Markets Finance and Trade, 55(7), 1593–1618. https://doi.org/10.1080/1540496X.2018.1500893 DOI: https://doi.org/10.1080/1540496X.2018.1474346

Hong, D., Zhou, Y., & Zhang, X. (2023). The impact of financial market uncertainty on the volatility of stock prices in emerging markets. Emerging Markets Review. https://doi.org/10.1016/j.ememar.2023.100944

Hong, H., Li, F. W., & Xu, J. (2023). Economic policy uncertainty, oil price shocks, and stock market volatility: Evidence from global markets. Energy Economics, 118, 106512. https://doi.org/10.1016/j.eneco.2023.106512 DOI: https://doi.org/10.1016/j.eneco.2023.106512

Kilian, L. (2009). Not all oil price shocks are alike: Disentangling demand and supply shocks in the crude oil market. American Economic Review, 99(3), 1053–1069. https://doi. org/10.1257/aer.99.3.1053 DOI: https://doi.org/10.1257/aer.99.3.1053

Kilian, L., & Murphy, D. P. (2014). The role of inventories and speculative trading in the global market for crude oil. Journal of Applied Econometrics, 29(3), 454–478. https://doi.org/10.1002/jae.2322 DOI: https://doi.org/10.1002/jae.2322

Lantz, B. (2019). Machine learning with R: Expert techniques for predictive modeling (3rd ed.). Packt Publishing. https://doi.org/10.1080/10686967.2019.1648086 DOI: https://doi.org/10.1080/10686967.2019.1648086

Obstfeld, M., Milesi-Ferretti, G. M., & Arezki, R. (2016). Oil prices and the global economy: It’s complicated [imf Working Paper 16/210]. International Monetary Fund. https://doi.org/10.5089/9781475552034.001 DOI: https://doi.org/10.5089/9781475552034.001

Pan, Z., Huang, X., Liu, L., & Huang, J. (2023). Geopolitical uncertainty and crude oil volatility: Evidence from oil-importing and oil-export. Finance Research Letters, 52. https://doi.org/10.1016/j.eneco.2022.105791 DOI: https://doi.org/10.1016/j.frl.2022.103565

Perilla, J. S. (2023). Oil price shocks and macroeconomic volatility in Latin America: The role of structural dependence and policy frameworks. Resources Policy, 80, 103217. https://doi.org/10.1016/j.resourpol.2022.103217 DOI: https://doi.org/10.1016/j.resourpol.2022.103217

Pindyck, R.S. (1991). Irreversibility, uncertainty, and investment. In R.S. Pindyck & D.L. Rubinfeld (Eds.), Microeconomics (3rd ed., pp. 323-343). Prentice Hall. https://doi.org/10.3386/w3307 DOI: https://doi.org/10.3386/w3307

Ratti, R. A., & Vespignani, J. L. (2016). Oil prices and global factor macroeconomic variables. Energy Economics, 59, 198–212. https://doi.org/10.1016/j.eneco.2016.06.002 DOI: https://doi.org/10.1016/j.eneco.2016.06.002

Salisu, A. A., & Gupta, R. (2021). Oil price shocks and economic policy uncertainty in emerging economies. Energy Economics, 94, 105085. https://doi.org/10.1016/j.eneco.2020.105085 DOI: https://doi.org/10.1016/j.eneco.2020.105085

Salisu, A. A., & Gupta, R. (2021b). Oil price shocks and stock market volatility: A review of the literature. International Review of Financial Analysis, 78, 102924. https://doi. org/10.1016/j.irfa.2021.102924

Salisu, A. A., & Gupta, R. (2021c). Oil shocks and stock market volatility of the brics: A garch-midas approach. Global Finance Journal, 48. https://doi.org/10.1016/j.gfj.2020.100546 DOI: https://doi.org/10.1016/j.gfj.2020.100546

Salisu, A. A., Adediran, I. A., & Alimi, R. Y. (2022). Modelling oil price volatility and stock market returns in emerging economies: A garch-midas approach. Journal of Economic Studies, 49(4), 731-745. https://doi.org/10.1108/jes-04-2021-0205

Salisu, A. A., Cuñado, J., & Gupta, R. (2022). Geopolitical risks and historical exchange rate volatility of the brics. International Review of Economics & Finance, 77, 179-190. https://doi.org/10.1016/j.iref.2021.09.017 DOI: https://doi.org/10.1016/j.iref.2021.09.017

Tumala, M. M., Salisu, A. A., & Gambo, A. I. (2023). Disentangled oil shocks and stock market volatility in Nigeria and South Africa: A garch-midas approach. Economic Analysis and Policy, 78, 707-717. https://doi.org/10.1016/j.eap.2023.04.009 DOI: https://doi.org/10.1016/j.eap.2023.04.009

Wang, Y., & Li, X. (2023). The impact of economic policy uncertainty on the volatility of stock prices in G7 countries. Journal of International Financial Markets, Institutions and Money. https://doi.org/10.2147/rmhp.S407481 World Bank. (2023). Oil shocks: Causes, effects, and mitigation strategies. World Bank. https:// openknowledge.worldbank.org/handle/10986/39886

Yu, J., Shi, X., Guo, D., & Yang, L. (2021). Economic policy uncertainty (epu) and firm carbon emissions: Evidence using a China provincial epu index. Energy Economics, 94, 105071. https://doi.org/10.1016/j.eneco.2020.105071 DOI: https://doi.org/10.1016/j.eneco.2020.105071

Yu, J., Zhang, Y., & Wang, S. (2023). The impact of political uncertainty on the volatility of stock prices in China. Emerging Markets Finance & Trade, 59(1), 107-120. https://doi.org/10.1080/1540496X.2022.2038753

Yu, X., Song, M., & Wang, J. (2021). The impact of economic and political uncertainty on stock market volatility in China. Economic Modelling, 570, 125794. https://doi.org/10.1016/j.physa.2021.125794 DOI: https://doi.org/10.1016/j.physa.2021.125794

Estatísticas de consulta