IDEAS home Printed from https://ideas.repec.org/a/eee/ememar/v52y2022ics1566014122000334.html
   My bibliography  Save this article

Effects of monetary policy news on financial assets: Evidence from Brazil on a bivariate VAR-GARCH model (2006–17)

Author

Listed:
  • da Silva, Tarciso Gouveia
  • de Carvalho Guillén, Osmani Teixeira
  • Morcerf, George Augusto Noronha
  • de Melo Modenesi, Andre

Abstract

The impact of news releases related to the inflation targeting regime on the financial market is analyzed by estimating a bivariate VAR GARCH-BEKK-in-mean model. We use daily data, from January 2006 to May 2017, of stock prices index (IBOVESPA), exchange rate (BRL/USD) and interbank deposit rate (DI360). We developed a positive and negative news index to measure the impact of news releases based on Caporale et al. (2016) and Caporale et al. (2018). Although the literature on the subject is vast, this paper fills relevant gaps in three ways. First, we investigate the bidirectional relationship between monetary policy related news releases and the behavior of asset prices before and after the 2008 crisis in Brazil. Second, we consider the relationship between the second moments of the variables of interest, using the conditional volatility as a proxy for uncertainty. Third, we provide a time series approach to measure the effect of macroeconomic related news releases on financial asset returns. The results indicate there are mean spread effects from news for the exchange rate and the Brazilian stock index: (i) the GARCH-in-mean parameter is statistically significant for positive and the difference of news for the DI360; (ii) monetary policy and external shocks are statiscally significant as expected with exception of the external shocks for the Brazilian stock index; and (iii) there are volatility spillovers and changes of this volatility after the crisis for stock index and DI360.

Suggested Citation

  • da Silva, Tarciso Gouveia & de Carvalho Guillén, Osmani Teixeira & Morcerf, George Augusto Noronha & de Melo Modenesi, Andre, 2022. "Effects of monetary policy news on financial assets: Evidence from Brazil on a bivariate VAR-GARCH model (2006–17)," Emerging Markets Review, Elsevier, vol. 52(C).
  • Handle: RePEc:eee:ememar:v:52:y:2022:i:c:s1566014122000334
    DOI: 10.1016/j.ememar.2022.100916
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1566014122000334
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ememar.2022.100916?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    2. Guglielmo Maria Caporale & Fabio Spagnolo & Nicola Spagnolo, 2018. "Macro news and bond yield spreads in the euro area," The European Journal of Finance, Taylor & Francis Journals, vol. 24(2), pages 114-134, January.
    3. Pearce, Douglas K & Roley, V Vance, 1985. "Stock Prices and Economic News," The Journal of Business, University of Chicago Press, vol. 58(1), pages 49-67, January.
    4. Rangel, José Gonzalo, 2011. "Macroeconomic news, announcements, and stock market jump intensity dynamics," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1263-1276, May.
    5. Birz, Gene & Lott Jr., John R., 2011. "The effect of macroeconomic news on stock returns: New evidence from newspaper coverage," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2791-2800, November.
    6. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Clara Vega, 2003. "Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange," American Economic Review, American Economic Association, vol. 93(1), pages 38-62, March.
    7. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    8. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    9. Kim, Bong-Han & Kim, Hyeongwoo & Lee, Bong-Soo, 2015. "Spillover effects of the U.S. financial crisis on financial markets in emerging Asian countries," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 192-210.
    10. Robert F. Engle & Kevin Sheppard, 2001. "Theoretical and Empirical properties of Dynamic Conditional Correlation Multivariate GARCH," NBER Working Papers 8554, National Bureau of Economic Research, Inc.
    11. Tse, Y. K., 2000. "A test for constant correlations in a multivariate GARCH model," Journal of Econometrics, Elsevier, vol. 98(1), pages 107-127, September.
    12. Balduzzi, Pierluigi & Elton, Edwin J. & Green, T. Clifton, 2001. "Economic News and Bond Prices: Evidence from the U.S. Treasury Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 36(4), pages 523-543, December.
    13. Caporale, Guglielmo Maria & Spagnolo, Fabio & Spagnolo, Nicola, 2016. "Macro news and stock returns in the Euro area: A VAR-GARCH-in-mean analysis," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 180-188.
    14. John H. Boyd & Jian Hu & Ravi Jagannathan, 2005. "The Stock Market's Reaction to Unemployment News: Why Bad News Is Usually Good for Stocks," Journal of Finance, American Finance Association, vol. 60(2), pages 649-672, April.
    15. Janot, Marcio Magalhães & Macedo, Leonardo Peixoto, 2016. "Efeitos das intervenções cambiais sobre a taxa de câmbio futura no Brasil," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 70(4), December.
    16. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Vega, Clara, 2007. "Real-time price discovery in global stock, bond and foreign exchange markets," Journal of International Economics, Elsevier, vol. 73(2), pages 251-277, November.
    17. Annastiina Silvennoinen & Timo Ter�svirta, 2015. "Modeling Conditional Correlations of Asset Returns: A Smooth Transition Approach," Econometric Reviews, Taylor & Francis Journals, vol. 34(1-2), pages 174-197, February.
    18. Bekiros, Stelios D., 2014. "Contagion, decoupling and the spillover effects of the US financial crisis: Evidence from the BRIC markets," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 58-69.
    19. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    20. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    21. Marcio Magalhães Janot & Leonardo Peixoto Macedo, 2016. "Efeitos das Intervenções Cambiais sobre a Taxa de Câmbio Futura no Brasil," Working Papers Series 413, Central Bank of Brazil, Research Department.
    22. Gabriele Galati & Corrinne Ho, 2003. "Macroeconomic News and the Euro/Dollar Exchange Rate," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 32(3), pages 371-398, November.
    23. Longin, Francois & Solnik, Bruno, 1995. "Is the correlation in international equity returns constant: 1960-1990?," Journal of International Money and Finance, Elsevier, vol. 14(1), pages 3-26, February.
    24. Merton, Robert C, 1973. "An Intertemporal Capital Asset Pricing Model," Econometrica, Econometric Society, vol. 41(5), pages 867-887, September.
    25. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 817-844.
    26. Mark J. Flannery & Aris A. Protopapadakis, 2002. "Macroeconomic Factors Do Influence Aggregate Stock Returns," Review of Financial Studies, Society for Financial Studies, vol. 15(3), pages 751-782.
    27. Bera, Anil K. & Kim, Sangwhan, 2002. "Testing constancy of correlation and other specifications of the BGARCH model with an application to international equity returns," Journal of Empirical Finance, Elsevier, vol. 9(2), pages 171-195, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tarciso Gouveia da Silva & Osmani Teixeira de Carvalho Guillén & George Augusto Noronha Morcerf & Andre de Melo Modenesi, 2020. "Effects of Monetary Policy News on Financial Assets: evidence from Brazil on a bivariate VAR-GARCH model (2006-17)," Working Papers Series 536, Central Bank of Brazil, Research Department.
    2. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    3. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    4. BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Volatility Forecasting," PIER Working Paper Archive 05-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    6. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    7. Caporale, Guglielmo Maria & Spagnolo, Fabio & Spagnolo, Nicola, 2016. "Macro news and stock returns in the Euro area: A VAR-GARCH-in-mean analysis," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 180-188.
    8. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    9. Adams, Zeno & Füss, Roland & Glück, Thorsten, 2017. "Are correlations constant? Empirical and theoretical results on popular correlation models in finance," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 9-24.
    10. M. Fatih Oztek & Nadir Ocal, 2012. "Integration of China Stock Markets with International Stock Markets: An application of Smooth Transition Conditional Correlation with Double Transition Functions," ERC Working Papers 1209, ERC - Economic Research Center, Middle East Technical University, revised Dec 2012.
    11. Brenner, Menachem & Pasquariello, Paolo & Subrahmanyam, Marti, 2009. "On the Volatility and Comovement of U.S. Financial Markets around Macroeconomic News Announcements," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(6), pages 1265-1289, December.
    12. Akhtaruzzaman, Md & Shamsuddin, Abul & Easton, Steve, 2014. "Dynamic correlation analysis of spill-over effects of interest rate risk and return on Australian and US financial firms," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 378-396.
    13. Kuper, Gerard H. & Lestano, 2007. "Dynamic conditional correlation analysis of financial market interdependence: An application to Thailand and Indonesia," Journal of Asian Economics, Elsevier, vol. 18(4), pages 670-684, August.
    14. Rangel, José Gonzalo, 2011. "Macroeconomic news, announcements, and stock market jump intensity dynamics," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1263-1276, May.
    15. Marçal, Emerson Fernandes & Pereira, Pedro L. Valls, 2008. "Testing the Hypothesis of Contagion Using Multivariate Volatility Models," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 28(2), November.
    16. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    17. Guglielmo Maria Caporale & Fabio Spagnolo & Nicola Spagnolo, 2017. "Macro News and Commodity Returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 22(1), pages 68-80, January.
    18. Marçal, Emerson F. & Valls Pereira, Pedro L., 2008. "Testando A Hipótese De Contágio A Partir De Modelos Multivariados De Volatilidade [Testing the contagion hypotheses using multivariate volatility models]," MPRA Paper 10356, University Library of Munich, Germany.
    19. Y. K. Tse, 2002. "Residual-based diagnostics for conditional heteroscedasticity models," Econometrics Journal, Royal Economic Society, vol. 5(2), pages 358-374, June.
    20. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008.

    More about this item

    Keywords

    Bivariate VAR-GARCH; Brazil; News;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ememar:v:52:y:2022:i:c:s1566014122000334. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620356 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.