IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v52y2017icp260-280.html
   My bibliography  Save this article

Main driving factors of the interest rate-stock market Granger causality

Author

Listed:
  • Jammazi, Rania
  • Ferrer, Román
  • Jareño, Francisco
  • Hammoudeh, Shawkat M.

Abstract

This paper investigates the causal relationship between changes in the 10-year Treasury bond yield and the S&P 500 stock return in the United Sates with emphasis on time variation, stress factors and smooth regime transition. First, the time-varying Granger causality test proposed by Lu et al. (2014) is applied. Then a two-regime multifactor smooth transition regression model with a single transition variable representing a wide range of macroeconomic and financial variables is estimated in order to identify the key explanatory factors governing the causal relationship. The results show a significant bidirectional causal relationship over most of the study period, mainly due to the strong simultaneous interactions between the bond interest rate and the stock returns, and the causal link has strengthened since the beginning of the U.S. sub-prime crisis in the summer of 2007. Moreover, the U.S. financial stress indices seem to play a key role in explaining the dynamics of the causal relationship between the long-term interest rates and the stock returns, especially during the recent global financial crisis.

Suggested Citation

  • Jammazi, Rania & Ferrer, Román & Jareño, Francisco & Hammoudeh, Shawkat M., 2017. "Main driving factors of the interest rate-stock market Granger causality," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 260-280.
  • Handle: RePEc:eee:finana:v:52:y:2017:i:c:p:260-280
    DOI: 10.1016/j.irfa.2017.07.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521917300790
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.irfa.2017.07.008?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. Cheung, Yin-Wong & Ng, Lilian K., 1996. "A causality-in-variance test and its application to financial market prices," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 33-48.
    2. Cenedese, Gino & Mallucci, Enrico, 2016. "What moves international stock and bond markets?," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 94-113.
    3. 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.
    4. Bekaert, Geert & Engstrom, Eric & Grenadier, Steven R., 2010. "Stock and bond returns with Moody Investors," Journal of Empirical Finance, Elsevier, vol. 17(5), pages 867-894, December.
    5. Perego, Erica R. & Vermeulen, Wessel N., 2016. "Macro-economic determinants of European stock and government bond correlations: A tale of two regions," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 214-232.
    6. V. Alaganar & Ramaprasad Bhar, 2003. "An international study of causality-in-variance: Interest rate and financial sector returns," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 27(1), pages 39-55, March.
    7. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 119-136, Suppl. De.
    8. Hossein Asgharian & Charlotte Christiansen & Ai Jun Hou, 2016. "Macro-Finance Determinants of the Long-Run Stock–Bond Correlation: The DCC-MIDAS Specification," Journal of Financial Econometrics, Oxford University Press, vol. 14(3), pages 617-642.
    9. 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.
    10. Eitrheim, Oyvind & Terasvirta, Timo, 1996. "Testing the adequacy of smooth transition autoregressive models," Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September.
    11. Francisco Jareño & Román Ferrer & Stanislava Miroslavova, 2016. "US stock market sensitivity to interest and inflation rates: a quantile regression approach," Applied Economics, Taylor & Francis Journals, vol. 48(26), pages 2469-2481, June.
    12. Lynge, Morgan J. & Zumwalt, J. Kenton, 1980. "An Empirical Study of the Interest Rate Sensitivity of Commercial Bank Returns: A Multi-Index Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 15(3), pages 731-742, September.
    13. Caporale, Guglielmo Maria & Menla Ali, Faek & Spagnolo, Fabio & Spagnolo, Nicola, 2017. "International portfolio flows and exchange rate volatility in emerging Asian markets," Journal of International Money and Finance, Elsevier, vol. 76(C), pages 1-15.
    14. Flannery, Mark J & James, Christopher M, 1984. "The Effect of Interest Rate Changes on the Common Stock Returns of Financial Institutions," Journal of Finance, American Finance Association, vol. 39(4), pages 1141-1153, September.
    15. Go Tamakoshi & Shigeyuki Hamori, 2014. "Causality-in-variance and causality-in-mean between the Greek sovereign bond yields and Southern European banking sector equity returns," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 38(4), pages 627-642, October.
    16. Lieven Baele, 2010. "The Determinants of Stock and Bond Return Comovements," The Review of Financial Studies, Society for Financial Studies, vol. 23(6), pages 2374-2428, June.
    17. Söhnke Bartram, 2002. "The Interest Rate Exposure of Nonfinancial Corporations," Review of Finance, European Finance Association, vol. 6(1), pages 101-125.
    18. Mohamed Essaied Hamrita & Abdelkader Trifi, 2011. "The Relationship between Interest Rate, Exchange Rate and Stock Price: A Wavelet Analysis," International Journal of Economics and Financial Issues, Econjournals, vol. 1(4), pages 220-228.
    19. Lu, Feng-bin & Hong, Yong-miao & Wang, Shou-yang & Lai, Kin-keung & Liu, John, 2014. "Time-varying Granger causality tests for applications in global crude oil markets," Energy Economics, Elsevier, vol. 42(C), pages 289-298.
    20. Connolly, Robert & Stivers, Chris & Sun, Licheng, 2005. "Stock Market Uncertainty and the Stock-Bond Return Relation," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 40(1), pages 161-194, March.
    21. Elyasiani, Elyas & Mansur, Iqbal, 1998. "Sensitivity of the bank stock returns distribution to changes in the level and volatility of interest rate: A GARCH-M model," Journal of Banking & Finance, Elsevier, vol. 22(5), pages 535-563, May.
    22. Gerald R. Jensen & Jeffrey M. Mercer, 2003. "New Evidence on Optimal Asset Allocation," The Financial Review, Eastern Finance Association, vol. 38(3), pages 435-454, August.
    23. Thomas Chiang & Jiandong Li & Sheng-Yung Yang, 2015. "Dynamic stock–bond return correlations and financial market uncertainty," Review of Quantitative Finance and Accounting, Springer, vol. 45(1), pages 59-88, July.
    24. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Vega, Clara, 2007. "Real-time price discovery in global stock, bond and foreign exchange markets," Journal of International Economics, Elsevier, vol. 73(2), pages 251-277, November.
    25. Lieven Baele & Geert Bekaert & Koen Inghelbrecht, 2007. "The determinants of stock and bond return comovements," Working Paper Research 119, National Bank of Belgium.
    26. Beckmann, Joscha & Berger, Theo & Czudaj, Robert, 2015. "Does gold act as a hedge or a safe haven for stocks? A smooth transition approach," Economic Modelling, Elsevier, vol. 48(C), pages 16-24.
    27. Shamsuddin, Abul, 2014. "Are Dow Jones Islamic equity indices exposed to interest rate risk?," Economic Modelling, Elsevier, vol. 39(C), pages 273-281.
    28. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    29. Zhou, Yinggang, 2014. "Modeling the joint dynamics of risk-neutral stock index and bond yield volatilities," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 216-228.
    30. Kasman, Saadet & Vardar, Gülin & Tunç, Gökçe, 2011. "The impact of interest rate and exchange rate volatility on banks' stock returns and volatility: Evidence from Turkey," Economic Modelling, Elsevier, vol. 28(3), pages 1328-1334, May.
    31. Hong, Yongmiao, 2001. "A test for volatility spillover with application to exchange rates," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 183-224, July.
    32. Sweeney, Richard J & Warga, Arthur D, 1986. "The Pricing of Interest-Rate Risk: Evidence from the Stock Market," Journal of Finance, American Finance Association, vol. 41(2), pages 393-410, June.
    33. Harumi Ohmi & Tatsuyoshi Okimoto, 2016. "Trends in stock-bond correlations," Applied Economics, Taylor & Francis Journals, vol. 48(6), pages 536-552, February.
    34. Balcilar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat, 2014. "What drives herding in oil-rich, developing stock markets? Relative roles of own volatility and global factors," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 418-440.
    35. Chen, XiaoHua & Maringer, Dietmar, 2011. "Detecting time-variation in corporate bond index returns: A smooth transition regression model," Journal of Banking & Finance, Elsevier, vol. 35(1), pages 95-103, January.
    36. Teräsvirta, Timo, 1996. "Smooth Transition Models," SSE/EFI Working Paper Series in Economics and Finance 132, Stockholm School of Economics.
    37. Chan, Kam C. & Norrbin, Stefan C. & Lai, Pikki, 1997. "Are stock and bond prices collinear in the long run?," International Review of Economics & Finance, Elsevier, vol. 6(2), pages 193-201.
    38. 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.
    39. Matiur Rahman & Muhammad Mustafa, 1997. "Dynamic linkages and Granger causality between short-term US corporate bond and stock markets," Applied Economics Letters, Taylor & Francis Journals, vol. 4(2), pages 89-91.
    40. 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.
    41. Simon Broome & Bruce Morley, 2000. "Long-run and short-run linkages between stock prices and interest rates in the G-7," Applied Economics Letters, Taylor & Francis Journals, vol. 7(5), pages 321-323.
    Full references (including those not matched with items on IDEAS)

    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. 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).
    2. 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.
    3. 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.
    4. Román Ferrer & Syed Jawad Hussain Shahzad & Adrián Maizonada, 2019. "Nonlinear and extreme dependence between long-term sovereign bond yields and the stock market: A quantile-on-quantile analysis," Economics Bulletin, AccessEcon, vol. 39(2), pages 969-981.
    5. Harumi Ohmi & Tatsuyoshi Okimoto, 2016. "Trends in stock-bond correlations," Applied Economics, Taylor & Francis Journals, vol. 48(6), pages 536-552, February.
    6. 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.
    7. 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.
    8. Ferrer, Román & Bolós, Vicente J. & Benítez, Rafael, 2016. "Interest rate changes and stock returns: A European multi-country study with wavelets," International Review of Economics & Finance, Elsevier, vol. 44(C), pages 1-12.
    9. Zaghum Umar & Syed Jawad Hussain Shahzad & Román Ferrer & Francisco Jareño, 2018. "Does Shariah compliance make interest rate sensitivity of Islamic equities lower? An industry level analysis under different market states," Applied Economics, Taylor & Francis Journals, vol. 50(42), pages 4500-4521, September.
    10. 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.
    11. 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.
    12. Lin, Fu-Lai & Yang, Sheng-Yung & Marsh, Terry & Chen, Yu-Fen, 2018. "Stock and bond return relations and stock market uncertainty: Evidence from wavelet analysis," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 285-294.
    13. 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).
    14. Nguyen, Hoang & Javed, Farrukh, 2023. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 272-292.
    15. Thomas C. Chiang & Lanjun Lao & Qingfeng Xue, 2016. "Comovements between Chinese and global stock markets: evidence from aggregate and sectoral data," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1003-1042, November.
    16. Fang, Libing & Yu, Honghai & Li, Lei, 2017. "The effect of economic policy uncertainty on the long-term correlation between U.S. stock and bond markets," Economic Modelling, Elsevier, vol. 66(C), pages 139-145.
    17. Laura Ferrando & Román Ferrer & Francisco Jareño, 2017. "Interest Rate Sensitivity of Spanish Industries: A Quantile Regression Approach," Manchester School, University of Manchester, vol. 85(2), pages 212-242, March.
    18. Fang, Libing & Yu, Honghai & Huang, Yingbo, 2018. "The role of investor sentiment in the long-term correlation between U.S. stock and bond markets," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 127-139.
    19. Thomas Chiang & Jiandong Li & Sheng-Yung Yang, 2015. "Dynamic stock–bond return correlations and financial market uncertainty," Review of Quantitative Finance and Accounting, Springer, vol. 45(1), pages 59-88, July.
    20. 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.

    More about this item

    Keywords

    Interest rates; Stock returns; Smooth transition regressions; Time-varying Granger causality; Financial stress indices;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:finana:v:52:y:2017:i:c:p:260-280. 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/inca/620166 .

    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.