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Testing for Volatility Co-movement in Bivariate Stochastic Volatility Models

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  • Chen, J.
  • Kobayashi, M.
  • McAleer, M.J.

Abstract

The paper considers the problem of volatility co-movement, namely as to whether two financial returns have perfectly correlated common volatility process, in the framework of multivariate stochastic volatility models and proposes a test which checks the volatility co-movement. The proposed test is a stochastic volatility version of the co-movement test proposed by Engle and Susmel (1993), who investigated whether international equity markets have volatility co-movement using the framework of the ARCH model. In empirical analysis we found that volatility co-movement exists among closelylinked stock markets and that volatility co-movement of the exchange rate markets tends to be found when the overall volatility level is low, which is contrasting to the often-cited finding in the financial contagion literature that financial returns have co-movement in the level during the financial crisis.

Suggested Citation

  • Chen, J. & Kobayashi, M. & McAleer, M.J., 2017. "Testing for Volatility Co-movement in Bivariate Stochastic Volatility Models," Econometric Institute Research Papers TI 2017-022/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Handle: RePEc:ems:eureir:99788
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    References listed on IDEAS

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    1. Engle, Robert F & Kozicki, Sharon, 1993. "Testing for Common Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(4), pages 369-380, October.
    2. Engle, Robert F & Kozicki, Sharon, 1993. "Testing for Common Features: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(4), pages 393-395, October.
    3. Manabu Asai & Michael McAleer & Jun Yu, 2006. "Multivariate Stochastic Volatility," Microeconomics Working Papers 22058, East Asian Bureau of Economic Research.
    4. Kristin J. Forbes & Roberto Rigobon, 2002. "No Contagion, Only Interdependence: Measuring Stock Market Comovements," Journal of Finance, American Finance Association, vol. 57(5), pages 2223-2261, October.
    5. Cipollini, A. & Kapetanios, G., 2008. "A stochastic variance factor model for large datasets and an application to S&P data," Economics Letters, Elsevier, vol. 100(1), pages 130-134, July.
    6. Masaru Chiba & Masahito Kobayashi, 2013. "Testing for a Single-Factor Stochastic Volatility in Bivariate Series," JRFM, MDPI, vol. 6(1), pages 1-31, December.
    7. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
    8. Engle, Robert F & Susmel, Raul, 1993. "Common Volatility in International Equity Markets," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 167-176, April.
    9. Watanabe, Toshiaki, 1999. "A Non-linear Filtering Approach to Stochastic Volatility Models with an Application to Daily Stock Returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(2), pages 101-121, March-Apr.
    10. Manabu Asai & Michael McAleer & Jun Yu, 2006. "Multivariate Stochastic Volatility: A Review," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 145-175.
    11. Fleming, Jeff & Kirby, Chris & Ostdiek, Barbara, 1998. "Information and volatility linkages in the stock, bond, and money markets," Journal of Financial Economics, Elsevier, vol. 49(1), pages 111-137, July.
    12. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
    13. Andrew Harvey & Esther Ruiz & Neil Shephard, 1994. "Multivariate Stochastic Variance Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(2), pages 247-264.
    14. Chesher, Andrew D, 1984. "Testing for Neglected Heterogeneity," Econometrica, Econometric Society, vol. 52(4), pages 865-872, July.
    15. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
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    Cited by:

    1. María Nieves López-García & Miguel Angel Sánchez-Granero & Juan Evangelista Trinidad-Segovia & Antonio Manuel Puertas & Francisco Javier De las Nieves, 2021. "Volatility Co-Movement in Stock Markets," Mathematics, MDPI, vol. 9(6), pages 1-19, March.

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    More about this item

    Keywords

    Lagrange multiplier test; Volatility co-movement; Stock markets; Exchange rate Markets; Financial crisis;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G01 - Financial Economics - - General - - - Financial Crises
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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