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A 10 min tick volatility analysis between the Ibovespa and the S&P500

Author

Listed:
  • Paulo Sergio Ceretta

    (UFSM)

  • Alexandre Silva da Costa

    (UFSM)

  • Marcelo Brutti Righi

    (UFSM)

  • Fernanda Maria Müller

    (Federal University of Santa Maria)

Abstract

In this paper we analyze intraday data on a 10-minute interval and compared the major market index in South America, the Ibovespa and sync up with the S&P500 in New York. The main target is to determine differences of volatility, in the Brazilian index, before and after the opening bell in New York. To reach this goal, we utilize the GARCH (autoregressive general heteroskedasticity) matching up times that both markets were open, and comparing to the hours that the Brazilian index was trading alone, without the direct influence of one of the American main indexes, the S&P500. As a result, we are able to disclose that this difference in volatility exists.

Suggested Citation

  • Paulo Sergio Ceretta & Alexandre Silva da Costa & Marcelo Brutti Righi & Fernanda Maria Müller, 2013. "A 10 min tick volatility analysis between the Ibovespa and the S&P500," Economics Bulletin, AccessEcon, vol. 33(3), pages 2169-2176.
    • Handle: RePEc:ebl:ecbull:eb-13-00459
    as

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    References listed on IDEAS

    as
    1. Jose Luis Miralles-Marcelo & Jose Luis Miralles-Quiros & Maria del Mar Miralles-Quiros, 2010. "Intraday linkages between the Spanish and the US stock markets: evidence of an overreaction effect," Applied Economics, Taylor & Francis Journals, vol. 42(2), pages 223-235.
    2. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    3. Pami Dua & Divya Tuteja, 2013. "Interdependence Of International Financial Market-- The Case Of India And U.S," Working papers 223, Centre for Development Economics, Delhi School of Economics.
    4. Robert F. Engle & Magdalena E. Sokalska, 0. "Forecasting intraday volatility in the US equity market. Multiplicative component GARCH," Journal of Financial Econometrics, Oxford University Press, vol. 10(1), pages 54-83.
    5. Chan, Kalok & Chan, K C & Karolyi, G Andrew, 1991. "Intraday Volatility in the Stock Index and Stock Index Futures Markets," The Review of Financial Studies, Society for Financial Studies, vol. 4(4), pages 657-684.
    6. Andersen, Torben G. & Bollerslev, Tim, 1997. "Intraday periodicity and volatility persistence in financial markets," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 115-158, June.
    7. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-234, April.
    8. Becker, Kent G & Finnerty, Joseph E & Gupta, Manoj, 1990. "The Intertemporal Relation between the U.S. and Japanese Stock Markets," Journal of Finance, American Finance Association, vol. 45(4), pages 1297-1306, September.
    9. 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.
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    More about this item

    Keywords

    GARCH; intraday; volatility.;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G0 - Financial Economics - - General

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