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Quantiles of the Realized Stock-Bond Correlation and Links to the Macroeconomy


  • Nektarios Aslanidis

    () (Department of Economics, FCEE, University Rovira Virgili)

  • Charlotte Christiansen

    () (Aarhus University and CREATES)


This paper adopts quantile regressions to scrutinize the realized stock-bond correlation based upon high frequency returns. The paper provides in-sample and out-of-sample analysis and considers a large number of macro-?nance predictors well-know from the return predictability literature. Strong in-sample predictability is obtained from quantile models with factor-augmented predictors, particularly at the lower to median quantiles. Out-of-sample the quantile factor model works best at the median to upper quantiles.

Suggested Citation

  • Nektarios Aslanidis & Charlotte Christiansen, 2012. "Quantiles of the Realized Stock-Bond Correlation and Links to the Macroeconomy," CREATES Research Papers 2012-34, Department of Economics and Business Economics, Aarhus University.
  • Handle: RePEc:aah:create:2012-34

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    References listed on IDEAS

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    4. Aslanidis, Nektarios & Christiansen, Charlotte, 2012. "Smooth transition patterns in the realized stock–bond correlation," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 454-464.
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    Cited by:

    1. Zhenxi Chen & Jan F. Kiviet & Weihong Huang, 2015. "On the integration of China's main stock exchange with the international financial market," Economic Growth Centre Working Paper Series 1505, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.
    2. Dimic, Nebojsa & Kiviaho, Jarno & Piljak, Vanja & Äijö, Janne, 2016. "Impact of financial market uncertainty and macroeconomic factors on stock–bond correlation in emerging markets," Research in International Business and Finance, Elsevier, vol. 36(C), pages 41-51.
    3. Nektarios Aslanidis & Charlotte Christiansen, 0711. "Flight to Safety from European Stock Markets," CREATES Research Papers 2017-38, Department of Economics and Business Economics, Aarhus University.
    4. repec:eee:finana:v:52:y:2017:i:c:p:260-280 is not listed on IDEAS
    5. Scholz, Michael & Sperlich, Stefan & Nielsen, Jens Perch, 2016. "Nonparametric long term prediction of stock returns with generated bond yields," Insurance: Mathematics and Economics, Elsevier, vol. 69(C), pages 82-96.
    6. repec:eee:ecmode:v:66:y:2017:i:c:p:139-145 is not listed on IDEAS
    7. Harumi Ohmi & Tatsuyoshi Okimoto, 2016. "Trends in stock-bond correlations," Applied Economics, Taylor & Francis Journals, vol. 48(6), pages 536-552, February.
    8. Sclip, Alex & Dreassi, Alberto & Miani, Stefano & Paltrinieri, Andrea, 2016. "Dynamic correlations and volatility linkages between stocks and sukuk: Evidence from international markets," Review of Financial Economics, Elsevier, vol. 31(C), pages 34-44.

    More about this item


    Realized stock-bond correlation; Quantile regressions; Macro?nance variables; Factor analysis.;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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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