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Can gold hedge against uncertainty in the cryptocurrency and energy markets?

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  • Qin, Meng
  • Shao, Xuefeng
  • Hu, Chengming
  • Su, Chi Wei

Abstract

Studying gold's ability to shield against uncertainties in energy and cryptocurrency markets could aid investors in refining investment portfolios. A novel wavelet quantile correlation methodology is developed to dissect the relationships between the cryptocurrency policy uncertainty index (CPUI) and gold price (GP), energy-related uncertainty index (ERUI) and GP across various quantiles and time horizons. We find that CPUI mainly correlates positively with GP across most quantiles. Gold offers stronger hedging against cryptocurrency policy uncertainty over medium- to long-term horizons than short-term. ERUI's mixed correlations with GP suggest that gold's ability to hedge against energy-related uncertainty is not permanent. By comparison, CPUI has a stronger link with GP than ERUI, indicating gold's more significant hedging potential during cryptocurrency policy uncertainties. During COVID-19, CPUI positively correlated with GP in the short term but negatively in the medium run, confirming gold's short-term hedging against cryptocurrency policy uncertainty. However, EPUI generally negatively correlates with GP, showing limited hedging capacity against energy-related uncertainty. During the Russia-Ukraine conflict, CPUI and ERUI strongly positively correlated with GP, highlighting gold's safe haven role against these uncertainties. Considering these results, valuable insights are furnished for investors and governments to respond flexibly to changes in financial markets.

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  • Qin, Meng & Shao, Xuefeng & Hu, Chengming & Su, Chi Wei, 2025. "Can gold hedge against uncertainty in the cryptocurrency and energy markets?," Technological Forecasting and Social Change, Elsevier, vol. 214(C).
    • Handle: RePEc:eee:tefoso:v:214:y:2025:i:c:s0040162525000812
    DOI: 10.1016/j.techfore.2025.124050
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    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • 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

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