IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v33y2020ics1544612318307323.html
   My bibliography  Save this article

Impact of US unconventional monetary policy on dynamic stock-bond correlations: Portfolio rebalancing and signalling channel effects

Author

Listed:
  • Gokmenoglu, Korhan K.
  • Hadood, Abobaker Al.Al.

Abstract

This paper investigates the impacts of both the portfolio rebalancing and signalling channel effects associated with US unconventional monetary policy on the dynamic correlation between the stock and bond markets at different levels of stock-bond market correlation distributions. The empirical results reveal that the portfolio rebalancing channel has a strong and predominantly negative effect on the dynamic stock-bond market correlations. In contrast, the signalling channel positively affects the dynamic stock-bond market correlations. The results also provide evidence of an asymmetric effect at the lower quantiles. These findings hence provide valuable information for policymakers, traders and portfolio managers.

Suggested Citation

  • Gokmenoglu, Korhan K. & Hadood, Abobaker Al.Al., 2020. "Impact of US unconventional monetary policy on dynamic stock-bond correlations: Portfolio rebalancing and signalling channel effects," Finance Research Letters, Elsevier, vol. 33(C).
    • Handle: RePEc:eee:finlet:v:33:y:2020:i:c:s1544612318307323
    DOI: 10.1016/j.frl.2019.05.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612318307323
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2019.05.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Aslanidis, Nektarios & Christiansen, Charlotte, 2014. "Quantiles of the realized stock–bond correlation and links to the macroeconomy," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 321-331.
    2. Lorenzo Cappiello & Robert F. Engle & Kevin Sheppard, 2006. "Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 537-572.
    3. Suk-Joong Kim & Fari Moshirian & Eliza Wu, 2018. "Evolution of International Stock and Bond Market Integration: Influence of the European Monetary Union," World Scientific Book Chapters, in: Information Spillovers and Market Integration in International Finance Empirical Analyses, chapter 12, pages 391-428, World Scientific Publishing Co. Pte. Ltd..
    4. Dongho Song, 2017. "Bond Market Exposures to Macroeconomic and Monetary Policy Risks," Review of Financial Studies, Society for Financial Studies, vol. 30(8), pages 2761-2817.
    5. Lutz, Chandler, 2015. "The impact of conventional and unconventional monetary policy on investor sentiment," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 89-105.
    6. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    7. Viceira, Luis M., 2012. "Bond risk, bond return volatility, and the term structure of interest rates," International Journal of Forecasting, Elsevier, vol. 28(1), pages 97-117.
    8. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    9. Don H. Kim & Jonathan H. Wright, 2005. "An arbitrage-free three-factor term structure model and the recent behavior of long-term yields and distant-horizon forward rates," Finance and Economics Discussion Series 2005-33, Board of Governors of the Federal Reserve System (U.S.).
    10. Skintzi, Vasiliki D., 2019. "Determinants of stock-bond market comovement in the Eurozone under model uncertainty," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 20-28.
    11. Lloyd, S. P., 2017. "Unconventional Monetary Policy and the Interest Rate Channel: Signalling and Portfolio Rebalancing," Cambridge Working Papers in Economics 1735, Faculty of Economics, University of Cambridge.
    12. Unknown, 2005. "Forward," 2005 Conference: Slovenia in the EU - Challenges for Agriculture, Food Science and Rural Affairs, November 10-11, 2005, Moravske Toplice, Slovenia 183804, Slovenian Association of Agricultural Economists (DAES).
    13. 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.
    14. Koenker, Roger & Bassett, Gilbert, Jr, 1982. "Robust Tests for Heteroscedasticity Based on Regression Quantiles," Econometrica, Econometric Society, vol. 50(1), pages 43-61, January.
    15. Kurov, Alexander, 2010. "Investor sentiment and the stock market's reaction to monetary policy," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 139-149, January.
    16. Boubaker, Sabri & Gounopoulos, Dimitrios & Nguyen, Duc Khuong & Paltalidis, Nikos, 2017. "Assessing the effects of unconventional monetary policy and low interest rates on pension fund risk incentives," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 35-52.
    17. Kryzanowski, Lawrence & Zhang, Jie & Zhong, Rui, 2017. "Cross-financial-market correlations and quantitative easing," Finance Research Letters, Elsevier, vol. 20(C), pages 13-21.
    18. Jawadi, Fredj & Sousa, Ricardo M. & Traverso, Raffaella, 2017. "On The Macroeconomic And Wealth Effects Of Unconventional Monetary Policy," Macroeconomic Dynamics, Cambridge University Press, vol. 21(5), pages 1189-1204, July.
    19. Yang, Jian & Zhou, Yinggang & Wang, Zijun, 2009. "The stock-bond correlation and macroeconomic conditions: One and a half centuries of evidence," Journal of Banking & Finance, Elsevier, vol. 33(4), pages 670-680, April.
    20. Alexis Flageollet & Hamza Bahaji, 2016. "Monetary Policy and Risk-Based Asset Allocation," Open Economies Review, Springer, vol. 27(5), pages 851-870, November.
    21. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bahcivan, Hulusi & Karahan, Cenk C., 2022. "High frequency correlation dynamics and day-of-the-week effect: A score-driven approach in an emerging market stock exchange," International Review of Financial Analysis, Elsevier, vol. 80(C).
    2. Chen, Hsuan-Chi & Yeh, Chia-Wei, 2021. "Global financial crisis and COVID-19: Industrial reactions," Finance Research Letters, Elsevier, vol. 42(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohammad Alomari & Abdel Razzaq Al rababa’a & Ghaith El-Nader & Ahmad Alkhataybeh, 2021. "Who’s behind the wheel? The role of social and media news in driving the stock–bond correlation," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 959-1007, October.
    2. 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.
    3. Dimic, Nebojsa & Piljak, Vanja & Swinkels, Laurens & Vulanovic, Milos, 2021. "The structure and degree of dependence in government bond markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    4. Skintzi, Vasiliki D., 2019. "Determinants of stock-bond market comovement in the Eurozone under model uncertainty," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 20-28.
    5. 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.
    6. Allard, Anne-Florence & Iania, Leonardo & Smedts, Kristien, 2020. "Stock-bond return correlations: Moving away from “one-frequency-fits-all” by extending the DCC-MIDAS approach," International Review of Financial Analysis, Elsevier, vol. 71(C).
    7. Gupta, Rangan & Kollias, Christos & Papadamou, Stephanos & Wohar, Mark E., 2018. "News implied volatility and the stock-bond nexus: Evidence from historical data for the USA and the UK markets," Journal of Multinational Financial Management, Elsevier, vol. 47, pages 76-90.
    8. Harumi Ohmi & Tatsuyoshi Okimoto, 2016. "Trends in stock-bond correlations," Applied Economics, Taylor & Francis Journals, vol. 48(6), pages 536-552, February.
    9. Piljak, Vanja, 2013. "Bond markets co-movement dynamics and macroeconomic factors: Evidence from emerging and frontier markets," Emerging Markets Review, Elsevier, vol. 17(C), pages 29-43.
    10. Long, Xiangdong & Su, Liangjun & Ullah, Aman, 2011. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 109-125.
    11. Ngene, Geoffrey M. & Lee Kim, Yea & Wang, Jinghua, 2019. "Who poisons the pool? Time-varying asymmetric and nonlinear causal inference between low-risk and high-risk bonds markets," Economic Modelling, Elsevier, vol. 81(C), pages 136-147.
    12. Garcia, René & Tsafack, Georges, 2011. "Dependence structure and extreme comovements in international equity and bond markets," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1954-1970, August.
    13. 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.
    14. Ngene, Geoffrey M., 2021. "What drives dynamic connectedness of the U.S equity sectors during different business cycles?," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    15. Ermolov, Andrey, 2022. "Time-varying risk of nominal bonds: How important are macroeconomic shocks?," Journal of Financial Economics, Elsevier, vol. 145(1), pages 1-28.
    16. Juan Andres Rodriguez-Nieto & Andre V. Mollick, 2021. "The US financial crisis, market volatility, credit risk and stock returns in the Americas," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(2), pages 225-254, June.
    17. Al Rababa’a, Abdel Razzaq & Alomari, Mohammad & McMillan, David, 2021. "Multiscale stock-bond correlation: Implications for risk management," Research in International Business and Finance, Elsevier, vol. 58(C).
    18. Alex Sclip & Alberto Dreassi & Stefano Miani & Andrea Paltrinieri, 2016. "Dynamic correlations and volatility linkages between stocks and sukuk: Evidence from international markets," Review of Financial Economics, John Wiley & Sons, vol. 31(1), pages 34-44, November.
    19. Urom, Christian & Anochiwa, Lasbrey & Yuni, Denis & Idume, Gabriel, 2019. "Asymmetric linkages among precious metals, global equity and bond yields: The role of volatility and business cycle factors," The Journal of Economic Asymmetries, Elsevier, vol. 20(C).
    20. Lucey, Brian M. & Vigne, Samuel A. & Ballester, Laura & Barbopoulos, Leonidas & Brzeszczynski, Janusz & Carchano, Oscar & Dimic, Nebojsa & Fernandez, Viviana & Gogolin, Fabian & González-Urteaga, Ana , 2018. "Future directions in international financial integration research - A crowdsourced perspective," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 35-49.

    More about this item

    Keywords

    Dynamic stock-bond market correlations; Portfolio rebalancing and signalling channels; Quantile regression;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • N20 - Economic History - - Financial Markets and Institutions - - - General, International, or Comparative
    • 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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:33:y:2020:i:c:s1544612318307323. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.