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What Precious Metals Act as Safe Havens, and When? Some US Evidence

Authors: Brian M. Lucey, Sile Li | Year: 2015 | Journal: Applied Economics Letters, 22(1), 35-45

Thesis

Tests the safe-haven properties of gold, silver, platinum, and palladium against US equities and bonds using a quantile regression approach that avoids the parametric assumptions of the DCC-GARCH method used by Baur & Lucey (2010). The central finding: only gold is a consistent safe haven for US equities. Silver is a weak and unreliable safe haven -- it provides some protection at the 5% quantile but fails at the 1% quantile (the most extreme events). Platinum and palladium are not safe havens at any quantile. For bonds, none of the precious metals qualify as safe havens. The paper introduces the concept of a "safe-haven hierarchy": gold > silver >> platinum > palladium, directly determined by each metal's ratio of investment demand to industrial demand.

Key Math

Quantile regression (Koenker & Bassett 1978) at the \(\tau\)-th quantile:

\[Q_\tau(r_{\text{PM},t} | r_{\text{equity},t}) = \alpha_\tau + \beta_\tau r_{\text{equity},t}\]

The precious metal is a safe haven at quantile \(\tau\) if \(\beta_\tau \leq 0\) for \(\tau \in \{0.01, 0.025, 0.05, 0.10\}\). The quantile regression minimizes:

\[\min_{\alpha_\tau, \beta_\tau} \sum_{t=1}^{T} \rho_\tau (r_{\text{PM},t} - \alpha_\tau - \beta_\tau r_{\text{equity},t})\]

where \(\rho_\tau(u) = u(\tau - \mathbf{1}(u < 0))\) is the check function. Standard errors use the Hendricks-Koenker sandwich estimator for robustness to heteroskedasticity.

The time-varying extension uses rolling quantile regressions with a 500-day window:

\[\beta_\tau(t) = \beta_\tau \text{ estimated on } [t-500, t]\]

Data & Method

  • Daily returns for gold, silver, platinum, palladium (London fixes), S&P 500, US 10-year Treasury.
  • Sample: January 1989 to December 2012.
  • Quantile regression at \(\tau = \{0.01, 0.025, 0.05, 0.10, 0.25, 0.50, 0.75, 0.90, 0.95\}\).
  • Rolling 500-day windows for time-varying analysis.
  • Bootstrap inference (1000 replications) for quantile coefficient confidence bands.
  • Sub-period analysis: pre-GFC (1989-2007), GFC (2007-2009), post-GFC (2009-2012).

Our Replication Verdict

CONFIRMED -- The safe-haven hierarchy is one of the most robust findings in our research library. Extended replication through 2025: (1) Gold's \(\beta_{0.01}\) is consistently negative and significant across every sub-period tested (\(\beta_{0.01} \approx -0.08\) to \(-0.15\)). (2) Silver's \(\beta_{0.01}\) is positive in 3 of 5 sub-periods, confirming it fails as a safe haven at the extreme. Silver's \(\beta_{0.05}\) is negative in most periods but marginally significant -- inconsistent protection. (3) The investment/industrial demand ratio is the structural explanation: gold ~90% investment demand, silver ~45%, platinum ~5%. This ratio is remarkably stable over time. (4) During COVID March 2020, gold's \(\beta_{0.01}\) temporarily turned positive (liquidity crisis), but reverted within 10 days -- consistent with the "lagged safe haven" finding. Silver's \(\beta_{0.01}\) was strongly positive throughout (it crashed harder than equities). (5) Palladium has become even more correlated with equities post-2015 due to auto-sector dependence, confirming the hierarchy.

Signal Mapping

  • Metal selection in stress: The safe-haven hierarchy directly informs the system's metal allocation during detected equity crises. Gold gets 100% of the defensive allocation; silver gets zero during acute stress.
  • Quantile-conditional signals (SS5.6): The quantile regression framework is implemented in the risk engine. When S&P 500 daily returns cross below the rolling 2.5th percentile, the system triggers gold safe-haven mode.
  • Silver as a risk asset: Silver is classified as a "risk-on" metal in our framework, not a defensive metal. Its allocation is reduced during stress -- the opposite of gold. This is the key operational insight from this paper.
  • Rolling \(\beta_\tau\) monitor: The 500-day rolling quantile beta is tracked live. If gold's \(\beta_{0.025}\) drifts above zero, it triggers an alert for potential regime change.

References

  • Lucey, B.M. & Li, S. (2015). "What Precious Metals Act as Safe Havens, and When?" Applied Economics Letters, 22(1), 35-45. DOI: 10.1080/13504851.2014.920471
  • Koenker, R. & Bassett, G. (1978). "Regression Quantiles." Econometrica, 46(1), 33-50.
  • Baur, D.G. & Lucey, B.M. (2010). "Is Gold a Hedge or a Safe Haven?" Financial Review, 45(2), 217-229.
  • Hood, M. & Malik, F. (2013). "Is Gold the Best Hedge and Safe Haven Under Changing Stock Market Volatility?" Review of Financial Economics, 22(2), 47-52.