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Macro-Finance Determinants of the Long-Run Stock-Bond Correlation: The DCC-MIDAS Specification

Author

Listed:
  • Hossein Asgharian

    () (Lund University)

  • Charlotte Christiansen

    () (Aarhus University and CREATES)

  • Ai Jun Hou

    () (Stockholm University)

Abstract

We investigate the long-run stock-bond correlation using a novel model that combines the dynamic conditional correlation model with the mixed-data sampling approach. The long-run correlation is affected by both macro-finance variables (historical and forecasts) and the lagged realized correlation itself. Macro-finance variables and the lagged realized correlation are simultaneously significant in forecasting the long-run stock-bond correlation. The behavior of the long-run stock-bond correlation is very different when estimated taking the macro-finance variables into account. Supporting the flight-to-quality phenomenon for the total stock-bond correlation, the long-run correlation tends to be small/negative when the economy is weak.

Suggested Citation

  • Hossein Asgharian & Charlotte Christiansen & Ai Jun Hou, 2014. "Macro-Finance Determinants of the Long-Run Stock-Bond Correlation: The DCC-MIDAS Specification," CREATES Research Papers 2014-13, Department of Economics and Business Economics, Aarhus University.
  • Handle: RePEc:aah:create:2014-13
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Conrad, Christian & Stuermer, Karin, 2017. "On the economic determinants of optimal stock-bond portfolios: international evidence," Working Papers 0636, University of Heidelberg, Department of Economics.
    2. Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun, 2015. "Effects of macroeconomic uncertainty on the stock and bond markets," Finance Research Letters, Elsevier, vol. 13(C), pages 10-16.
    3. repec:eee:ecolet:v:159:y:2017:i:c:p:119-122 is not listed on IDEAS
    4. Petar Sabtchevsky & Paul Whelan & Andrea Vedolin & Philippe Mueller, 2017. "Variance Risk Premia on Stocks and Bonds," 2017 Meeting Papers 1161, Society for Economic Dynamics.
    5. Hossein Asgharian & Charlotte Christiansen & Ai Jun Hou, 2803. "Economic Policy Uncertainty and Long-Run Stock Market Volatility and Correlation," CREATES Research Papers 2018-12, Department of Economics and Business Economics, Aarhus University.
    6. repec:eee:finana:v:52:y:2017:i:c:p:260-280 is not listed on IDEAS
    7. Refk Selmi & Christos Kollias & Stephanos Papadamou & Rangan Gupta, 2017. "A Copula-Based Quantile-on-Quantile Regression Approach to Modeling Dependence Structure between Stock and Bond Returns: Evidence from Historical Data of India, South Africa, UK and US," Working Papers 201747, University of Pretoria, Department of Economics.
    8. Yoseph Yilma Getachew, 2016. "Credit Constraints, Growth and Inequality Dynamics," Working Papers 201672, University of Pretoria, Department of Economics.
    9. John Cotter & Mark Hallam & Kamil Yilmaz, 2017. "Mixed-frequency macro-financial spillovers," Working Papers 201704, Geary Institute, University College Dublin.
    10. Hossein Asgharian & Charlotte Christiansen & Rangan Gupta & Ai Jun Hou, 2016. "Effects of Economic Policy Uncertainty Shocks on the Long-Run US-UK Stock Market Correlation," CREATES Research Papers 2016-29, Department of Economics and Business Economics, Aarhus University.
    11. Alessandra Amendola & Vincenzo Candila & Antonio Scognamillo, 2017. "On the influence of US monetary policy on crude oil price volatility," Empirical Economics, Springer, vol. 52(1), pages 155-178, February.
    12. Bucci, Andrea, 2017. "Forecasting realized volatility: a review," MPRA Paper 83232, University Library of Munich, Germany.
    13. Conrad, Christian & Loch, Karin, 2016. "Macroeconomic expectations and the time-varying stock-bond correlation: international evidence," Annual Conference 2016 (Augsburg): Demographic Change 145530, Verein für Socialpolitik / German Economic Association.
    14. Skintzi, Vasiliki, 2017. "Determinants of stock-bond market comovement in the Eurozone under model uncertainty," MPRA Paper 78278, University Library of Munich, Germany.

    More about this item

    Keywords

    DCC-MIDAS model; Long-run correlation; Macro-finance variables; Stock-bond correlation;

    JEL classification:

    • 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
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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