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Fluctuations of the Real Exchange Rate, Real Interest Rates, and the Dynamics of the Price of Gold in a Small Open Economy

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  • Rohloff, Sebastian
  • Pierdzioch, Christian
  • Risse, Marian
Abstract
Economic theory predicts that, in a small open economy, the dynamics of the real price of gold should be linked to real interest rates and the rate of change of the real exchange rate. Using data for Australia, we use a real-time forecasting approach to analyze whether real interest rates and the rate of change of the real exchange rate help to forecast out-ofsample the rate of change of the real price of gold. We study the economic value-added of out-of-sample forecasts using a behavioral-finance approach that takes into account that a forecaster may have an asymmetric loss function.

Suggested Citation

  • Rohloff, Sebastian & Pierdzioch, Christian & Risse, Marian, 2014. "Fluctuations of the Real Exchange Rate, Real Interest Rates, and the Dynamics of the Price of Gold in a Small Open Economy," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100429, Verein für Socialpolitik / German Economic Association.
    • Handle: RePEc:zbw:vfsc14:100429
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    Cited by:

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    4. 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.
    5. Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2022. "Oil-Price Uncertainty and International Stock Returns: Dissecting Quantile-Based Predictability and Spillover Effects Using More than a Century of Data," Energies, MDPI, vol. 15(22), pages 1-26, November.
    6. Kucher, Oleg & McCoskey, Suzanne, 2017. "The long-run relationship between precious metal prices and the business cycle," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 263-275.
    7. Le, Thai-Ha & Chang, Youngho, 2016. "Dynamics between strategic commodities and financial variables: Evidence from Japan," Resources Policy, Elsevier, vol. 50(C), pages 1-9.
    8. 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).
    9. Rangan Gupta & Christian Pierdzioch, 2023. "Do U.S. economic conditions at the state level predict the realized volatility of oil-price returns? A quantile machine-learning approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-22, December.
    10. Shahbaz, Muhammad & Balcilar, Mehmet & Abidin Ozdemir, Zeynel, 2017. "Does oil predict gold? A nonparametric causality-in-quantiles approach," Resources Policy, Elsevier, vol. 52(C), pages 257-265.
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    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • 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

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