IDEAS home Printed from https://ideas.repec.org/p/pre/wpaper/201967.html
   My bibliography  Save this paper

Gold, Platinum and the Predictability of Bond Risk Premia

Author

Listed:
  • Elie Bouri

    (USEK Business School, Holy Spirit University of Kaslik, Jounieh, Lebanon)

  • Riza Demirer

    (Department of Economics and Finance, Southern Illinois University Edwardsville, Edwardsville, IL 62026-1102, USA)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

  • Mark E. Wohar

    (College of Business Administration, University of Nebraska at Omaha, 6708 Pine Street, Omaha, NE 68182, USA, and School of Business and Economics, Loughborough University, Leicestershire, LE11 3TU, UK)

Abstract

We show that the ratio of gold to platinum prices (GP) contains significant predictive information for excess U.S. government bond returns, even after controlling for a large number of financial and macro factors. Including GP in the model improves the predictive accuracy, over and above the standard macroeconomic and financial predictors, at all forecasting horizons for the shortest maturity bonds and at longer forecasting horizons for bonds with longer maturities beyond 2 years. The findings highlight the predictive information captured by commodity prices on bond market excess returns with significant investment and policy making implications.

Suggested Citation

  • Elie Bouri & Riza Demirer & Rangan Gupta & Mark E. Wohar, 2019. "Gold, Platinum and the Predictability of Bond Risk Premia," Working Papers 201967, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201967
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Balcilar, Mehmet & Gupta, Rangan & Wang, Shixuan & Wohar, Mark E., 2020. "Oil price uncertainty and movements in the US government bond risk premia," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    2. John Geweke & Susan Porter‐Hudak, 1983. "The Estimation And Application Of Long Memory Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 4(4), pages 221-238, July.
    3. Maurizio Michael Habib & Livio Stracca, 2015. "Is There a Global Safe Haven?," International Finance, Wiley Blackwell, vol. 18(3), pages 281-298, December.
    4. Hans Dewachter & Leonardo Iania & Marco Lyrio, 2014. "Information In The Yield Curve: A Macro‐Finance Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 42-64, January.
    5. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2017. "The Informational Content of the Term Spread in Forecasting the US Inflation Rate: A Nonlinear Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(2), pages 109-121, March.
    6. Hamilton, James D & Kim, Dong Heon, 2002. "A Reexamination of the Predictability of Economic Activity Using the Yield Spread," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(2), pages 340-360, May.
    7. Huang, Darien & Kilic, Mete, 2019. "Gold, platinum, and expected stock returns," Journal of Financial Economics, Elsevier, vol. 132(3), pages 50-75.
    8. Antonio Gargano & Davide Pettenuzzo & Allan Timmermann, 2019. "Bond Return Predictability: Economic Value and Links to the Macroeconomy," Management Science, INFORMS, vol. 65(2), pages 508-540, February.
    9. John Y. Campbell, 2008. "Viewpoint: Estimating the equity premium," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 41(1), pages 1-21, February.
    10. Jessica A. Wachter, 2013. "Can Time-Varying Risk of Rare Disasters Explain Aggregate Stock Market Volatility?," Journal of Finance, American Finance Association, vol. 68(3), pages 987-1035, June.
    11. Periklis Gogas & Theophilos Papadimitriou & Maria Matthaiou & Efthymia Chrysanthidou, 2015. "Yield Curve and Recession Forecasting in a Machine Learning Framework," Computational Economics, Springer;Society for Computational Economics, vol. 45(4), pages 635-645, April.
    12. John H. Cochrane & Monika Piazzesi, 2005. "Bond Risk Premia," American Economic Review, American Economic Association, vol. 95(1), pages 138-160, March.
    13. John Y. Campbell, 2007. "Estimating the Equity Premium," NBER Working Papers 13423, National Bureau of Economic Research, Inc.
    14. 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.
    15. Zhu, Xiaoneng, 2015. "Out-of-sample bond risk premium predictions: A global common factor," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 155-173.
    16. 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.
    17. Periklis Gogas & Theophilos Papadimitriou & Efthymia Chrysanthidou, 2015. "Yield Curve Point Triplets in Recession Forecasting," International Finance, Wiley Blackwell, vol. 18(2), pages 207-226, June.
    18. Laborda, Ricardo & Olmo, Jose, 2014. "Investor sentiment and bond risk premia," Journal of Financial Markets, Elsevier, vol. 18(C), pages 206-233.
    19. Smith, Josephine M. & Taylor, John B., 2009. "The term structure of policy rules," Journal of Monetary Economics, Elsevier, vol. 56(7), pages 907-917, October.
    20. 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).
    21. 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.
    22. Sydney C. Ludvigson & Serena Ng, 2009. "Macro Factors in Bond Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5027-5067, December.
    23. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    24. Keim, Donald B. & Stambaugh, Robert F., 1986. "Predicting returns in the stock and bond markets," Journal of Financial Economics, Elsevier, vol. 17(2), pages 357-390, December.
    25. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
    26. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    27. Vasilios Plakandaras & Juncal Cunado & Rangan Gupta & Mark E. Wohar, 2017. "Do leading indicators forecast U.S. recessions? A nonlinear re†evaluation using historical data," International Finance, Wiley Blackwell, vol. 20(3), pages 289-316, December.
    28. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2016. "The Term Premium as a Leading Macroeconomic Indicator," Working Papers 201613, University of Pretoria, Department of Economics.
    29. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    30. Riza Demirer & Rangan Gupta, 2018. "Presidential Cycles and Time-Varying Bond-Stock Correlations: Evidence from More than Two Centuries of Data," Working Papers 201811, University of Pretoria, Department of Economics.
    31. Josephine M. Smith & John B. Taylor, 2007. "The Long and the Short End of the Term Structure of Policy Rules," NBER Working Papers 13635, National Bureau of Economic Research, Inc.
    32. Eric Ghysels & Casidhe Horan & Emanuel Moench, 2018. "Forecasting through the Rearview Mirror: Data Revisions and Bond Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 31(2), pages 678-714.
    33. Fama, Eugene F & Bliss, Robert R, 1987. "The Information in Long-Maturity Forward Rates," American Economic Review, American Economic Association, vol. 77(4), pages 680-692, September.
    34. Kateryna Anatoliyevna Kopyl & John Byong-Tek Lee, 2016. "How safe are the safe haven assets?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 30(4), pages 453-482, November.
    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. Demirer, Riza & Gabauer, David & Gupta, Rangan & Nielsen, Joshua, 2024. "Gold, platinum and the predictability of bubbles in global stock markets," Resources Policy, Elsevier, vol. 90(C).
    2. Rangan Gupta & Christian Pierdzioch & Wing-Keung Wong, 2021. "A Note on Forecasting the Historical Realized Variance of Oil-Price Movements: The Role of Gold-to-Silver and Gold-to-Platinum Price Ratios," Energies, MDPI, vol. 14(20), pages 1-12, October.
    3. Salisu, Afees A. & Pierdzioch, Christian & Gupta, Rangan & Gabauer, David, 2022. "Forecasting stock-market tail risk and connectedness in advanced economies over a century: The role of gold-to-silver and gold-to-platinum price ratios," International Review of Financial Analysis, Elsevier, vol. 83(C).
    4. Riza Demirer & David Gabauer & Rangan Gupta & Joshua Nielsen, 2023. "Gold-to-Platinum Price Ratio and the Predictability of Bubbles in Financial Markets," Working Papers 202317, University of Pretoria, Department of Economics.
    5. Jixiang, Zhang & Feng, Ma, 2024. "Video apps user engagement and stock market volatility: Evidence from China," Finance Research Letters, Elsevier, vol. 64(C).
    6. Duc Huynh, Toan Luu & Burggraf, Tobias & Wang, Mei, 2020. "Gold, platinum, and expected Bitcoin returns," Journal of Multinational Financial Management, Elsevier, vol. 56(C).
    7. Wang, Jiashun & Wang, Jiqian & Ma, Feng, 2024. "International commodity market and stock volatility predictability: Evidence from G7 countries," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 62-71.

    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. 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).
    2. Balcilar, Mehmet & Gupta, Rangan & Wang, Shixuan & Wohar, Mark E., 2020. "Oil price uncertainty and movements in the US government bond risk premia," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    3. Oguzhan Cepni & Rangan Gupta & I. Ethem Güney & M. Yilmaz, 2020. "Forecasting local currency bond risk premia of emerging markets: The role of cross‐country macrofinancial linkages," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 966-985, September.
    4. 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.
    5. 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).
    6. 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.
    7. Daniel Borup & Jonas N. Eriksen & Mads M. Kjær & Martin Thyrsgaard, 2024. "Predicting Bond Return Predictability," Management Science, INFORMS, vol. 70(2), pages 931-951, February.
    8. Dai, Zhifeng & Kang, Jie, 2021. "Bond yield and crude oil prices predictability," Energy Economics, Elsevier, vol. 97(C).
    9. Bouri, Elie & Gupta, Rangan & Majumdar, Anandamayee & Subramaniam, Sowmya, 2021. "Time-varying risk aversion and forecastability of the US term structure of interest rates," Finance Research Letters, Elsevier, vol. 42(C).
    10. Zhang, Han & Fan, Xiaoyun & Guo, Bin & Zhang, Wei, 2019. "Reexamining time-varying bond risk premia in the post-financial crisis era," Journal of Economic Dynamics and Control, Elsevier, vol. 109(C).
    11. Cepni, Oguzhan & Gupta, Rangan & Karahan, Cenk C. & Lucey, Brian, 2022. "Oil price shocks and yield curve dynamics in emerging markets," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 613-623.
    12. Qi Liu & Libin Tao & Weixing Wu & Jianfeng Yu, 2017. "Short- and Long-Run Business Conditions and Expected Returns," Management Science, INFORMS, vol. 63(12), pages 4137-4157, December.
    13. Hai Lin & Chunchi Wu & Guofu Zhou, 2018. "Forecasting Corporate Bond Returns with a Large Set of Predictors: An Iterated Combination Approach," Management Science, INFORMS, vol. 64(9), pages 4218-4238, September.
    14. Tom Engsted & Stig V. Møller & Magnus Sander, 2013. "Bond return predictability in expansions and recessions," CREATES Research Papers 2013-13, Department of Economics and Business Economics, Aarhus University.
    15. Corradi, Valentina & Fosten, Jack & Gutknecht, Daniel, 2024. "Predictive ability tests with possibly overlapping models," Journal of Econometrics, Elsevier, vol. 241(1).
    16. Jessica A. Wachter, 2010. "Asset Allocation," Annual Review of Financial Economics, Annual Reviews, vol. 2(1), pages 175-206, December.
    17. De Rezende, Rafael B., 2015. "Risks in macroeconomic fundamentals and excess bond returns predictability," Working Paper Series 295, Sveriges Riksbank (Central Bank of Sweden).
    18. 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.
    19. Plakandaras, Vasilios & Gogas, Periklis & Papadimitriou, Theophilos & Gupta, Rangan, 2019. "A re-evaluation of the term spread as a leading indicator," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 476-492.
    20. Zhu, Xiaoneng, 2015. "Out-of-sample bond risk premium predictions: A global common factor," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 155-173.

    More about this item

    Keywords

    Bond Premia; Predictability; Gold-Platinum Price Ratio; Out-of-Sample Forecasts;
    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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:pre:wpaper:201967. 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: Rangan Gupta (email available below). General contact details of provider: https://edirc.repec.org/data/decupza.html .

    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.