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Modelling conditional correlations of asset returns: A smooth transition approach

Author

Listed:
  • Annastiina Silvennoinen

    () (School of Economics and Finance)

  • Timo Teräsvirta

    () (Aarhus University, School of Economics and Management and CREATES)

Abstract

In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM-test is derived to test the constancy of correlations and LM- and Wald tests to test the hypothesis of partially constant correlations. Analytical expressions for the test statistics and the required derivatives are provided to make computations feasible. An empirical example based on daily return series of five frequently traded stocks in the S&P 500 stock index completes the paper.

Suggested Citation

  • Annastiina Silvennoinen & Timo Teräsvirta, 2012. "Modelling conditional correlations of asset returns: A smooth transition approach," CREATES Research Papers 2012-09, Department of Economics and Business Economics, Aarhus University.
  • Handle: RePEc:aah:create:2012-09
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    References listed on IDEAS

    as
    1. 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.
    2. Susan Thorp & George Milunovich, 2007. "Symmetric Versus Asymmetric Conditional Covariance Forecasts: Does It Pay To Switch?," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 30(3), pages 355-377.
    3. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, vol. 19(02), pages 280-310, April.
    4. 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.
    5. 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.
    6. Harrison Hong & Jeremy C. Stein, 2003. "Differences of Opinion, Short-Sales Constraints, and Market Crashes," Review of Financial Studies, Society for Financial Studies, vol. 16(2), pages 487-525.
    7. repec:cor:louvrp:-1847 is not listed on IDEAS
    8. Meitz, Mika & Saikkonen, Pentti, 2011. "Parameter Estimation In Nonlinear Ar–Garch Models," Econometric Theory, Cambridge University Press, vol. 27(06), pages 1236-1278, December.
    9. Pelletier, Denis, 2006. "Regime switching for dynamic correlations," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 445-473.
    10. Berben, Robert-Paul & Jansen, W. Jos, 2005. "Comovement in international equity markets: A sectoral view," Journal of International Money and Finance, Elsevier, vol. 24(5), pages 832-857, September.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Luc Bauwens & Christian M. Hafner & Diane Pierret, 2013. "Multivariate Volatility Modeling Of Electricity Futures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 743-761, August.
    2. BAUWENS, Luc & otranto, EDOARDO, 2013. "Modeling the dependence of conditional correlations on volatility," CORE Discussion Papers 2013014, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. OHASHI Kazuhiko & OKIMOTO Tatsuyoshi, 2013. "Increasing Trends in the Excess Comovement of Commodity Prices," Discussion papers 13048, Research Institute of Economy, Trade and Industry (RIETI).
    4. Annastiina Silvennoinen & Susan Thorp, 2016. "Crude Oil and Agricultural Futures: An Analysis of Correlation Dynamics," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(6), pages 522-544, June.
    5. Heejoon Han & Dennis Kristensen, 2014. "Asymptotic Theory for the QMLE in GARCH-X Models With Stationary and Nonstationary Covariates," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 416-429, July.
    6. De Santis, Roberto A. & Stein, Michael, 2016. "Correlation changes between the risk-free rate and sovereign yields of euro area countries," Working Paper Series 1979, European Central Bank.
    7. Silvennoinen, Annastiina & Thorp, Susan, 2013. "Financialization, crisis and commodity correlation dynamics," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 42-65.
    8. repec:oup:jfinec:v:15:y:2017:i:2:p:247-285. is not listed on IDEAS
    9. Annastiina Silvennoinen & Timo Teräsvirta, 3108. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," CREATES Research Papers 2017-28, Department of Economics and Business Economics, Aarhus University.
    10. E. Otranto, 2015. "Adding Flexibility to Markov Switching Models," Working Paper CRENoS 201509, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    11. 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.
    12. Kryzanowski, Lawrence & Zhang, Jie & Zhong, Rui, 2017. "Cross-financial-market correlations and quantitative easing," Finance Research Letters, Elsevier, vol. 20(C), pages 13-21.
    13. L. Bauwens & E. Otrando, 2018. "Nonlinearities and Regimes in Conditional Correlations with Different Dynamics," Working Paper CRENoS 201803, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    14. Ohashi, Kazuhiko & Okimoto, Tatsuyoshi, 2016. "Increasing trends in the excess comovement of commodity prices," Journal of Commodity Markets, Elsevier, vol. 1(1), pages 48-64.
    15. repec:qut:auncer:2013_03 is not listed on IDEAS

    More about this item

    Keywords

    GARCH; Constant conditional correlation; Dynamic conditional correlation; Return comovement; Variable correlation GARCH model; Volatility model evaluation;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G1 - Financial Economics - - General Financial Markets

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