IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-22-00723.html
   My bibliography  Save this article

The stance of U.S. monetary policy and the realized variance of gold-price returns

Author

Listed:
  • Christian Pierdzioch

    (Department of Economics, Helmut Schmidt University)

  • Sebastian Rohloff

    (Department of Economics, Helmut Schmidt University)

  • Roland von Campe

    (Department of Economics, Helmut Schmidt University)

Abstract

We use a quantile-regression model to study the association between the stance of U.S. monetary policy and the realized variance of gold-price. We measure the stance of monetary policy using the spread between the real interest rate and the natural real interest rate. During a hawkish policy regime, tighter monetary policy is associated with a lower realized variance at the upper quantiles its conditional distribution. During the recent dovish policy regime, in contrast, the link between tighter monetary policy and the realized variance of gold price returns at the upper quantiles of its conditional distributionis positive.

Suggested Citation

  • Christian Pierdzioch & Sebastian Rohloff & Roland von Campe, 2023. "The stance of U.S. monetary policy and the realized variance of gold-price returns," Economics Bulletin, AccessEcon, vol. 43(2), pages 719-732.
  • Handle: RePEc:ebl:ecbull:eb-22-00723
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/Pubs/EB/2023/Volume43/EB-23-V43-I2-P59.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hammoudeh, Shawkat M. & Yuan, Yuan & McAleer, Michael & Thompson, Mark A., 2010. "Precious metals-exchange rate volatility transmissions and hedging strategies," International Review of Economics & Finance, Elsevier, vol. 19(4), pages 633-647, October.
    2. Bonato, Matteo & Demirer, Riza & Gupta, Rangan & Pierdzioch, Christian, 2018. "Gold futures returns and realized moments: A forecasting experiment using a quantile-boosting approach," Resources Policy, Elsevier, vol. 57(C), pages 196-212.
    3. Thomas Laubach & John C. Williams, 2003. "Measuring the Natural Rate of Interest," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 1063-1070, November.
    4. Baur, Dirk G., 2013. "The structure and degree of dependence: A quantile regression approach," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 786-798.
    5. Huang, Darien & Kilic, Mete, 2019. "Gold, platinum, and expected stock returns," Journal of Financial Economics, Elsevier, vol. 132(3), pages 50-75.
    6. Bahloul, Walid & Balcilar, Mehmet & Cunado, Juncal & Gupta, Rangan, 2018. "The role of economic and financial uncertainties in predicting commodity futures returns and volatility: Evidence from a nonparametric causality-in-quantiles test," Journal of Multinational Financial Management, Elsevier, vol. 45(C), pages 52-71.
    7. Frankel, Jeffrey A., 2014. "Effects of speculation and interest rates in a “carry trade” model of commodity prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 88-112.
    8. 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.
    9. Hammoudeh, Shawkat & Yuan, Yuan, 2008. "Metal volatility in presence of oil and interest rate shocks," Energy Economics, Elsevier, vol. 30(2), pages 606-620, March.
    10. Francesco Bianchi & Martin Lettau & Sydney C. Ludvigson, 2022. "Monetary Policy and Asset Valuation," Journal of Finance, American Finance Association, vol. 77(2), pages 967-1017, April.
    11. Balcilar, Mehmet & Bonato, Matteo & Demirer, Riza & Gupta, Rangan, 2017. "The effect of investor sentiment on gold market return dynamics: Evidence from a nonparametric causality-in-quantiles approach," Resources Policy, Elsevier, vol. 51(C), pages 77-84.
    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. Troster, Victor & Bouri, Elie & Roubaud, David, 2019. "A quantile regression analysis of flights-to-safety with implied volatilities," Resources Policy, Elsevier, vol. 62(C), pages 482-495.
    2. Demirer, Riza & Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2019. "Time-varying risk aversion and realized gold volatility," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    3. Bakas, Dimitrios & Triantafyllou, Athanasios, 2018. "The impact of uncertainty shocks on the volatility of commodity prices," Journal of International Money and Finance, Elsevier, vol. 87(C), pages 96-111.
    4. El Hedi Arouri, Mohamed & Lahiani, Amine & Nguyen, Duc Khuong, 2015. "World gold prices and stock returns in China: Insights for hedging and diversification strategies," Economic Modelling, Elsevier, vol. 44(C), pages 273-282.
    5. Gupta, Rangan & Majumdar, Anandamayee & Pierdzioch, Christian & Wohar, Mark E., 2017. "Do terror attacks predict gold returns? Evidence from a quantile-predictive-regression approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 276-284.
    6. Karanasos, Menelaos & Menla Ali, Faek & Margaronis, Zannis & Nath, Rajat, 2018. "Modelling time varying volatility spillovers and conditional correlations across commodity metal futures," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 246-256.
    7. Ma, Richie Ruchuan & Xiong, Tao, 2021. "Price explosiveness in nonferrous metal futures markets," Economic Modelling, Elsevier, vol. 94(C), pages 75-90.
    8. Balcilar, Mehmet & Ozdemir, Zeynel Abidin, 2019. "The volatility effect on precious metals price returns in a stochastic volatility in mean model with time-varying parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    9. Gil-Alana, Luis A. & Chang, Shinhye & Balcilar, Mehmet & Aye, Goodness C. & Gupta, Rangan, 2015. "Persistence of precious metal prices: A fractional integration approach with structural breaks," Resources Policy, Elsevier, vol. 44(C), pages 57-64.
    10. Berna Kirkulak-Uludag & Zorikto Lkhamazhapov, 2017. "Volatility Dynamics of Precious Metals: Evidence from Russia," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 67(4), pages 300-317, August.
    11. Reboredo, Juan C. & Ugolini, Andrea, 2015. "Downside/upside price spillovers between precious metals: A vine copula approach," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 84-102.
    12. Bosch, David & Pradkhan, Elina, 2015. "The impact of speculation on precious metals futures markets," Resources Policy, Elsevier, vol. 44(C), pages 118-134.
    13. Shawkat Hammoudeh & Duc Khuong Nguyen & Ricardo M. Sousa, 2014. "US Monetary Policy and Commodity Sector Prices," Working Papers 2014-438, Department of Research, Ipag Business School.
    14. Agnello, Luca & Castro, Vitor & Hammoudeh, Shawkat & Sousa, Ricardo M., 2017. "Spillovers from the oil sector to the housing market cycle," Energy Economics, Elsevier, vol. 61(C), pages 209-220.
    15. Kirkulak-Uludag, Berna & Lkhamazhapov, Zorikto, 2016. "The volatility dynamics of spot and futures gold prices: Evidence from Russia," Research in International Business and Finance, Elsevier, vol. 38(C), pages 474-484.
    16. Umar, Zaghum & Nasreen, Samia & Solarin, Sakiru Adebola & Tiwari, Aviral Kumar, 2019. "Exploring the time and frequency domain connectedness of oil prices and metal prices," Resources Policy, Elsevier, vol. 64(C).
    17. Antonakakis, Nikolaos & Kizys, Renatas, 2015. "Dynamic spillovers between commodity and currency markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 303-319.
    18. Rangan Gupta & Sayar Karmakar & Christian Pierdzioch, 2024. "Safe Havens, Machine Learning, and the Sources of Geopolitical Risk: A Forecasting Analysis Using Over a Century of Data," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 487-513, July.
    19. Vigne, Samuel A. & Lucey, Brian M. & O’Connor, Fergal A. & Yarovaya, Larisa, 2017. "The financial economics of white precious metals — A survey," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 292-308.
    20. Arouri, Mohamed El Hedi & Hammoudeh, Shawkat & Lahiani, Amine & Nguyen, Duc Khuong, 2012. "Long memory and structural breaks in modeling the return and volatility dynamics of precious metals," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(2), pages 207-218.

    More about this item

    Keywords

    Monetary policy; Gold; Realized variance; Quantile regression;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

    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:ebl:ecbull:eb-22-00723. 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: John P. Conley (email available below). General contact details of provider: .

    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.