IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v167y2018icp36-39.html
   My bibliography  Save this article

Presidential cycles and time-varying bond–stock market correlations: Evidence from more than two centuries of data

Author

Listed:
  • Demirer, Riza
  • Gupta, Rangan

Abstract

Utilizing a DCC-GARCH model to capture time-varying correlations, we show that Democratic administrations are generally associated with lower degree of co-movement between the stock and government bond returns. The findings are in line with the documented presidential cycle effect on stock market returns and corroborate recent evidence that, when risk aversion is high, agents tend to elect the Democratic Party.

Suggested Citation

  • Demirer, Riza & Gupta, Rangan, 2018. "Presidential cycles and time-varying bond–stock market correlations: Evidence from more than two centuries of data," Economics Letters, Elsevier, vol. 167(C), pages 36-39.
    • Handle: RePEc:eee:ecolet:v:167:y:2018:i:c:p:36-39
    DOI: 10.1016/j.econlet.2018.03.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176518300909
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2018.03.006?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. Ľuboš Pástor & Pietro Veronesi, 2020. "Political Cycles and Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 128(11), pages 4011-4045.
    2. Pedro Santa‐Clara & Rossen Valkanov, 2003. "The Presidential Puzzle: Political Cycles and the Stock Market," Journal of Finance, American Finance Association, vol. 58(5), pages 1841-1872, October.
    3. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2013. "Dynamic co-movements of stock market returns, implied volatility and policy uncertainty," Economics Letters, Elsevier, vol. 120(1), pages 87-92.
    4. 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.
    5. Demirer, Rıza & Lee, Hsiang-Tai & Lien, Donald, 2015. "Does the stock market drive herd behavior in commodity futures markets?," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 32-44.
    6. Christos Kollias & Stephanos Papadamou & Vangelis Arvanitis, 2013. "Symposium - Does Terrorism Affect the Stock-Bond Covariance? Evidence from European Countries," Southern Economic Journal, John Wiley & Sons, vol. 79(4), pages 832-848, April.
    7. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    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. Chang, Kai & Ye, Zhifang & Wang, Weihong, 2019. "Volatility spillover effect and dynamic correlation between regional emissions allowances and fossil energy markets: New evidence from China’s emissions trading scheme pilots," Energy, Elsevier, vol. 185(C), pages 1314-1324.
    2. Dai, Zhifeng & Kang, Jie, 2021. "Bond yield and crude oil prices predictability," Energy Economics, Elsevier, vol. 97(C).
    3. Semei Coronado & Rangan Gupta & Saban Nazlioglu & Omar Rojas, 2023. "Time‐varying causality between bond and oil markets of the United States: Evidence from over one and half centuries of data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2239-2247, July.
    4. Çepni, Oğguzhan & Demirer, Riza & Gupta, Rangan & Pierdzioch, Christian, 2020. "Time-varying risk aversion and the predictability of bond premia," Finance Research Letters, Elsevier, vol. 34(C).
    5. Oğuzhan Çepni & Rangan Gupta & Mark E. Wohar, 2021. "Variants of consumption‐wealth ratios and predictability of U.S. government bond risk premia," International Review of Finance, International Review of Finance Ltd., vol. 21(2), pages 661-674, June.
    6. Bouri, Elie & Demirer, Riza & Gupta, Rangan & Wohar, Mark E., 2021. "Gold, platinum and the predictability of bond risk premia," Finance Research Letters, Elsevier, vol. 38(C).
    7. Çepni, Oğuzhan & Guney, I. Ethem & Gupta, Rangan & Wohar, Mark E., 2020. "The role of an aligned investor sentiment index in predicting bond risk premia of the U.S," Journal of Financial Markets, Elsevier, vol. 51(C).
    8. Oguzhan Cepni & Rangan Gupta & Mark E. Wohar, 2019. "Variants of Consumption-Wealth Ratios and Predictability of U.S. Government Bond Risk Premia: Old is still Gold," Working Papers 201912, University of Pretoria, Department of Economics.

    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. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2019. "Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility," CESifo Working Paper Series 8000, CESifo.
    2. Rangan Gupta & Mark E. Wohar, 2018. "Presidential Cycles in the United States and the Dollar-Pound Exchange Rate: Evidence from over Two Centuries of Data," Working Papers 201874, University of Pretoria, Department of Economics.
    3. Mokni, Khaled & Ajmi, Ahdi Noomen & Bouri, Elie & Vo, Xuan Vinh, 2020. "Economic policy uncertainty and the Bitcoin-US stock nexus," Journal of Multinational Financial Management, Elsevier, vol. 57.
    4. Rangan Gupta & Mark E. Wohar, 2019. "Presidential Cycles In The Usa And The Dollar-Pound Exchange Rate: Evidence From Over Two Centuries," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(2), pages 151-163, June.
    5. Liow, Kim Hiang & Liao, Wen-Chi & Huang, Yuting, 2018. "Dynamics of international spillovers and interaction: Evidence from financial market stress and economic policy uncertainty," Economic Modelling, Elsevier, vol. 68(C), pages 96-116.
    6. Nini Johana Marín-Rodríguez & Juan David González-Ruiz & Sergio Botero Botero, 2022. "Dynamic Co-Movements among Oil Prices and Financial Assets: A Scientometric Analysis," Sustainability, MDPI, vol. 14(19), pages 1-26, October.
    7. Karanasos, M. & Yfanti, S., 2021. "On the Economic fundamentals behind the Dynamic Equicorrelations among Asset classes: Global evidence from Equities, Real estate, and Commodities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    8. 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.
    9. Li, Jianglong & Xie, Chunping & Long, Houyin, 2019. "The roles of inter-fuel substitution and inter-market contagion in driving energy prices: Evidences from China’s coal market," Energy Economics, Elsevier, vol. 84(C).
    10. Borgschulte, Mark & Cho, Heepyung & Lubotsky, Darren, 2022. "Partisanship and survey refusal," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 332-357.
    11. Gala, Vito D. & Pagliardi, Giovanni & Zenios, Stavros A., 2023. "Global political risk and international stock returns," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 78-102.
    12. Bathia, Deven & Demirer, Riza & Gupta, Rangan & Kotzé, Kevin, 2021. "Unemployment fluctuations and currency returns in the United Kingdom: Evidence from over one and a half century of data," Journal of Multinational Financial Management, Elsevier, vol. 61(C).
    13. Ranajit Kumar Bairagi, 2022. "Dynamic Impacts of Economic Policy Uncertainty on Australian Stock Market: An Intercontinental Evidence," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 21(1), pages 64-91, March.
    14. Guo, Jin, 2018. "Co-movement of international copper prices, China's economic activity, and stock returns: Structural breaks and volatility dynamics," Global Finance Journal, Elsevier, vol. 36(C), pages 62-77.
    15. Martin Hoesli & Kustrim Reka, 2013. "Volatility Spillovers, Comovements and Contagion in Securitized Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 47(1), pages 1-35, July.
    16. Shi, Yujie & Wang, Liming & Ke, Jian, 2021. "Does the US-China trade war affect co-movements between US and Chinese stock markets?," Research in International Business and Finance, Elsevier, vol. 58(C).
    17. Afees A. Salisu & Kazeem Isah, 2017. "Modeling the spillovers between stock market and money market in Nigeria," Working Papers 023, Centre for Econometric and Allied Research, University of Ibadan.
    18. Ribeiro Scarcioffolo, Alexandre & Etienne, Xiaoli L., 2018. "Does Economic Policy Uncertainty Affect Energy Market Volatility and Vice-Versa?," 2018 Annual Meeting, August 5-7, Washington, D.C. 273976, Agricultural and Applied Economics Association.
    19. Cui, Jinxin & Maghyereh, Aktham, 2023. "Higher-order moment risk connectedness and optimal investment strategies between international oil and commodity futures markets: Insights from the COVID-19 pandemic and Russia-Ukraine conflict," International Review of Financial Analysis, Elsevier, vol. 86(C).
    20. Dorine Boumans & Klaus Gründler & Niklas Potrafke & Fabian Ruthardt, 2021. "The Global Economic Impact of Politicians: Evidence from an International Survey RCT," CESifo Working Paper Series 8833, CESifo.

    More about this item

    Keywords

    Conditional correlation; GARCH; Bond and stock returns comovement; US presidential cycles;
    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
    • 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
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • 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:ecolet:v:167:y:2018:i:c:p:36-39. 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/ecolet .

    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.