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The shape of the Treasury yield curve and commodity prices

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  • Bayaa, Yasmeen
  • Qadan, Mahmoud

Abstract

We decompose the U.S. yield curve into three latent factors – the level, slope and curvature – and explore the information content of the yield curve regarding the future evolution in oil, coal, copper, ethanol, gold, heating oil, natural gas, palladium, platinum, silver and zinc prices. Using data from January 1986 to November 2021, we find that the shape of the term structure is very informative about future innovations in these commodities. Results indicate that shocks to the level, which represents long-term expectations about inflation, predict positive (negative) price (volatility) changes. Shocks to the slope and curvature, which are interpreted as part of the business cycle conditions, predict negative price changes. These results are manifested mainly in the period after the financialization era in 2004. Our findings have far-reaching implications for investors, policymakers and firms involved in the mining industry.

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  • Bayaa, Yasmeen & Qadan, Mahmoud, 2024. "The shape of the Treasury yield curve and commodity prices," International Review of Financial Analysis, Elsevier, vol. 94(C).
  • Handle: RePEc:eee:finana:v:94:y:2024:i:c:s1057521924002436
    DOI: 10.1016/j.irfa.2024.103311
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    as
    1. Kilian, Lutz, 2019. "Measuring global real economic activity: Do recent critiques hold up to scrutiny?," Economics Letters, Elsevier, vol. 178(C), pages 106-110.
    2. Chadha, Jagjit S. & Waters, Alex, 2014. "Applying a macro-finance yield curve to UK quantitative Easing," Journal of Banking & Finance, Elsevier, vol. 39(C), pages 68-86.
    3. Ciner, Cetin, 2011. "Commodity prices and inflation: Testing in the frequency domain," Research in International Business and Finance, Elsevier, vol. 25(3), pages 229-237, September.
    4. Rosa, Carlo, 2014. "The high-frequency response of energy prices to U.S. monetary policy: Understanding the empirical evidence," Energy Economics, Elsevier, vol. 45(C), pages 295-303.
    5. Anthony Garratt & Ivan Petrella, 2022. "Commodity prices and inflation risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 392-414, March.
    6. Uddin, Gazi Salah & Hernandez, Jose Areola & Shahzad, Syed Jawad Hussain & Hedström, Axel, 2018. "Multivariate dependence and spillover effects across energy commodities and diversification potentials of carbon assets," Energy Economics, Elsevier, vol. 71(C), pages 35-46.
    7. Morana, Claudio, 2013. "Oil price dynamics, macro-finance interactions and the role of financial speculation," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 206-226.
    8. Glick, Reuven & Leduc, Sylvain, 2012. "Central bank announcements of asset purchases and the impact on global financial and commodity markets," Journal of International Money and Finance, Elsevier, vol. 31(8), pages 2078-2101.
    9. Lange, Ronald H., 2013. "The Canadian macroeconomy and the yield curve: A dynamic latent factor approach," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 261-274.
    10. Julien Chevallier & Mathieu Gatumel & Florian Ielpo, 2014. "Commodity markets through the business cycle," Quantitative Finance, Taylor & Francis Journals, vol. 14(9), pages 1597-1618, September.
    11. Batten, Jonathan A. & Ciner, Cetin & Lucey, Brian M., 2010. "The macroeconomic determinants of volatility in precious metals markets," Resources Policy, Elsevier, vol. 35(2), pages 65-71, June.
    12. Semeyutin, Artur & Gozgor, Giray & Lau, Chi Keung Marco & Xu, Bing, 2021. "Effects of idiosyncratic jumps and co-jumps on oil, gold, and copper markets," Energy Economics, Elsevier, vol. 104(C).
    13. Hasse, Jean-Baptiste & Lajaunie, Quentin, 2022. "Does the yield curve signal recessions? New evidence from an international panel data analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 9-22.
    14. Dean Scrimgeour, 2015. "Commodity Price Responses to Monetary Policy Surprises," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(1), pages 88-102.
    15. Bampinas, Georgios & Panagiotidis, Theodore, 2015. "Are gold and silver a hedge against inflation? A two century perspective," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 267-276.
    16. Filippo Natoli, 2021. "Financialization Of Commodities Before And After The Great Financial Crisis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 488-511, April.
    17. Ali, Sajid & Bouri, Elie & Czudaj, Robert Lukas & Shahzad, Syed Jawad Hussain, 2020. "Revisiting the valuable roles of commodities for international stock markets," Resources Policy, Elsevier, vol. 66(C).
    18. Gelos, Gaston & Ustyugova, Yulia, 2017. "Inflation responses to commodity price shocks – How and why do countries differ?," Journal of International Money and Finance, Elsevier, vol. 72(C), pages 28-47.
    19. Christie, Andrew A., 1982. "The stochastic behavior of common stock variances : Value, leverage and interest rate effects," Journal of Financial Economics, Elsevier, vol. 10(4), pages 407-432, December.
    20. Andrea Silvestrini & Andrea Zaghini, 2015. "Financial shocks and the real economy in a nonlinear world: a survey of the theoretical and empirical literature," Questioni di Economia e Finanza (Occasional Papers) 255, Bank of Italy, Economic Research and International Relations Area.
    21. Afonso, António & Martins, Manuel M.F., 2012. "Level, slope, curvature of the sovereign yield curve, and fiscal behaviour," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1789-1807.
    22. Hammoudeh, Shawkat & Nguyen, Duc Khuong & Sousa, Ricardo M., 2015. "US monetary policy and sectoral commodity prices," Journal of International Money and Finance, Elsevier, vol. 57(C), pages 61-85.
    23. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
    24. Kagraoka, Yusho, 2016. "Common dynamic factors in driving commodity prices: Implications of a generalized dynamic factor model," Economic Modelling, Elsevier, vol. 52(PB), pages 609-617.
    25. Chen, Yu-chin & Turnovsky, Stephen J. & Zivot, Eric, 2014. "Forecasting inflation using commodity price aggregates," Journal of Econometrics, Elsevier, vol. 183(1), pages 117-134.
    26. Issler, João Victor & Rodrigues, Claudia & Burjack, Rafael, 2014. "Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 310-335.
    27. Gebka, Bartosz & Wohar, Mark E., 2018. "The predictive power of the yield spread for future economic expansions: Evidence from a new approach," Economic Modelling, Elsevier, vol. 75(C), pages 181-195.
    28. Dewachter, Hans & Lyrio, Marco, 2006. "Macro Factors and the Term Structure of Interest Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(1), pages 119-140, February.
    29. Mensi, Walid & Al-Yahyaee, Khamis Hamed & Hoon Kang, Sang, 2017. "Time-varying volatility spillovers between stock and precious metal markets with portfolio implications," Resources Policy, Elsevier, vol. 53(C), pages 88-102.
    30. Umar, Zaghum & Aharon, David Y. & Esparcia, Carlos & AlWahedi, Wafa, 2022. "Spillovers between sovereign yield curve components and oil price shocks," Energy Economics, Elsevier, vol. 109(C).
    31. Hännikäinen, Jari, 2017. "When does the yield curve contain predictive power? Evidence from a data-rich environment," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1044-1064.
    32. Silvestrini, Andrea & Zaghini, Andrea, 2015. "Financial shocks and the real economy in a nonlinear world: From theory to estimation," Journal of Policy Modeling, Elsevier, vol. 37(6), pages 915-929.
    33. Daskalaki, Charoula & Skiadopoulos, George & Topaloglou, Nikolas, 2017. "Diversification benefits of commodities: A stochastic dominance efficiency approach," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 250-269.
    34. Qadan, Mahmoud & Nama, Hazar, 2018. "Investor sentiment and the price of oil," Energy Economics, Elsevier, vol. 69(C), pages 42-58.
    35. Akram, Q. Farooq, 2009. "Commodity prices, interest rates and the dollar," Energy Economics, Elsevier, vol. 31(6), pages 838-851, November.
    36. Ratti, Ronald A. & Vespignani, Joaquin L., 2016. "Oil prices and global factor macroeconomic variables," Energy Economics, Elsevier, vol. 59(C), pages 198-212.
    37. Salisu, Afees A. & Gupta, Rangan & Nel, Jacobus & Bouri, Elie, 2022. "The (Asymmetric) effect of El Niño and La Niña on gold and silver prices in a GVAR model," Resources Policy, Elsevier, vol. 78(C).
    38. Belke, Ansgar H. & Bordon, Ingo G. & Hendricks, Torben W., 2014. "Monetary policy, global liquidity and commodity price dynamics," The North American Journal of Economics and Finance, Elsevier, vol. 28(C), pages 1-16.
    39. Ruano, Fábio & Barros, Victor, 2022. "Commodities and portfolio diversification: Myth or fact?," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 281-295.
    40. Bilgin, Mehmet Huseyin & Gogolin, Fabian & Lau, Marco Chi Keung & Vigne, Samuel A., 2018. "Time-variation in the relationship between white precious metals and inflation: A cross-country analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 56(C), pages 55-70.
    41. Nguyen, Duc Khuong & Sensoy, Ahmet & Sousa, Ricardo M. & Salah Uddin, Gazi, 2020. "U.S. equity and commodity futures markets: Hedging or financialization?," Energy Economics, Elsevier, vol. 86(C).
    42. Chauvet, Marcelle & Senyuz, Zeynep, 2016. "A dynamic factor model of the yield curve components as a predictor of the economy," International Journal of Forecasting, Elsevier, vol. 32(2), pages 324-343.
    43. Qadan, Mahmoud & Shuval, Kerem & David, Or, 2023. "Uncertainty about interest rates and the real economy," The North American Journal of Economics and Finance, Elsevier, vol. 68(C).
    44. Gruber, Joseph W. & Vigfusson, Robert J., 2018. "Interest Rates And The Volatility And Correlation Of Commodity Prices," Macroeconomic Dynamics, Cambridge University Press, vol. 22(3), pages 600-619, April.
    45. Adams, Zeno & Collot, Solène & Kartsakli, Maria, 2020. "Have commodities become a financial asset? Evidence from ten years of Financialization," Energy Economics, Elsevier, vol. 89(C).
    46. Corbet, Shaen & Dunne, John James & Larkin, Charles, 2019. "Quantitative easing announcements and high-frequency stock market volatility: Evidence from the United States," Research in International Business and Finance, Elsevier, vol. 48(C), pages 321-334.
    47. Arturo Estrella & Anthony P. Rodrigues & Sebastian Schich, 2003. "How Stable is the Predictive Power of the Yield Curve? Evidence from Germany and the United States," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 629-644, August.
    48. Mensi, Walid & Rehman, Mobeen Ur & Al-Yahyaee, Khamis Hamed, 2020. "Time-frequency co-movements between oil prices and interest rates: Evidence from a wavelet-based approach," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    49. Bianchi, Robert J. & Fan, John Hua & Todorova, Neda, 2020. "Financialization and de-financialization of commodity futures: A quantile regression approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    50. Amatov, Aitbek & Dorfman, Jeffrey H., 2017. "The Effects On Commodity Prices Of Extraordinary Monetary Policy," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 49(1), pages 83-96, February.
    51. Idilbi-Bayaa, Yasmeen & Qadan, Mahmoud, 2022. "What the current yield curve says, and what the future prices of energy do," Resources Policy, Elsevier, vol. 75(C).
    52. Argyropoulos, Efthymios & Tzavalis, Elias, 2016. "Forecasting economic activity from yield curve factors," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 293-311.
    53. Bessler, Wolfgang & Wolff, Dominik, 2015. "Do commodities add value in multi-asset portfolios? An out-of-sample analysis for different investment strategies," Journal of Banking & Finance, Elsevier, vol. 60(C), pages 1-20.
    54. Agnello, Luca & Castro, Vítor & Hammoudeh, Shawkat & Sousa, Ricardo M., 2020. "Global factors, uncertainty, weather conditions and energy prices: On the drivers of the duration of commodity price cycle phases," Energy Economics, Elsevier, vol. 90(C).
    55. Peel, David A. & Taylor, Mark P., 1998. "The slope of the yield curve and real economic activity: tracing the transmission mechanism," Economics Letters, Elsevier, vol. 59(3), pages 353-360, June.
    56. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
    57. Aguiar-Conraria, Luís & Martins, Manuel M.F. & Soares, Maria Joana, 2012. "The yield curve and the macro-economy across time and frequencies," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1950-1970.
    58. Liu, Lu & Zhang, Xiang, 2019. "Financialization and commodity excess spillovers," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 195-216.
    59. Diebold, Francis X. & Rudebusch, Glenn D. & Borag[caron]an Aruoba, S., 2006. "The macroeconomy and the yield curve: a dynamic latent factor approach," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 309-338.
    60. Wang, Yu Shan & Chueh, Yen Ling, 2013. "Dynamic transmission effects between the interest rate, the US dollar, and gold and crude oil prices," Economic Modelling, Elsevier, vol. 30(C), pages 792-798.
    61. Dai, Zhifeng & Kang, Jie, 2021. "Bond yield and crude oil prices predictability," Energy Economics, Elsevier, vol. 97(C).
    62. Salisu, Afees A. & Ndako, Umar B. & Oloko, Tirimisiyu F., 2019. "Assessing the inflation hedging of gold and palladium in OECD countries," Resources Policy, Elsevier, vol. 62(C), pages 357-377.
    63. Mahmod Qadan & Joseph Yagil, 2015. "International co-movements of real and financial economic variables," Applied Economics, Taylor & Francis Journals, vol. 47(31), pages 3347-3366, July.
    64. Bianchi, Francesco & Mumtaz, Haroon & Surico, Paolo, 2009. "The great moderation of the term structure of UK interest rates," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 856-871, September.
    65. Valadkhani, Abbas & Nguyen, Jeremy & Chiah, Mardy, 2022. "When is gold an effective hedge against inflation?," Resources Policy, Elsevier, vol. 79(C).
    66. Anari, Ali & Kolari, James, 2016. "Dynamics of interest and inflation rates," Journal of Empirical Finance, Elsevier, vol. 39(PA), pages 129-144.
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    More about this item

    Keywords

    Coal; Copper; Crude oil; Energy prices; Ethanol; Gold; Heating oil; Interest rates; Natural gas; Palladium; Platinum; Silver; Term structure; Zinc;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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