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Precious & industrial metals · Research note

Twenty years of gold, silver & copper — and the ten-year theses that follow.

A backtest of the three metals ETFs in USD — and in ZAR where an observed exchange rate exists — read against the June 2026 macro, technology and financial landscape, distilled into four ten-year theses, each with stated refutation conditions.

Coverage  GLD · SLV · CPERPublished  24 June 2026 · corrected 1 October 2026
10.6%
Gold (GLD) CAGR in USD, 31 Dec 2004 – 22 Jun 2026
14.8%
Gold CAGR in rand on observed USD/ZAR, 7 Nov 2014 – 22 Jun 2026 (11.1% in USD)
R5.75 → R16.41
USD/ZAR, Dec 2004 (reconstructed, unverified) → 22 Jun 2026 (observed)
−25.2%
Gold's worst rand drawdown, month-end, 7 Nov 2014 – 22 Jun 2026 (USD: −20.5%)

Over the observed-FX window (7 Nov 2014 – 22 Jun 2026) the rand's depreciation — USD/ZAR R11.26 to R16.41, 3.3% a year — made rand-measured returns of the three dollar metals ETFs materially higher than their dollar returns. Whether it reduced drawdowns depended on timing, and the observed record is mixed: gold's worst rand drawdown was deeper than its dollar drawdown; copper's was not.

  • Gold compounded fastest of the three over the long windows — 10.6%/yr in USD over 31 Dec 2004 – 22 Jun 2026 (silver led over 7 Nov 2014 – 22 Jun 2026: 12.4% vs 11.1%) — and had the highest USD return per unit of volatility in every window measured (USD Sharpe 0.59 from GLD's 18 Nov 2004 inception; 0.42 over 30 Dec 2011 – 22 Jun 2026; 0.70 over 7 Nov 2014 – 22 Jun 2026).
  • The rand is a currency exposure, not a free addition to return — USD/ZAR rose 45.8% over 7 Nov 2014 – 22 Jun 2026, which lifted rand returns; from its R19.82 high on 25 May 2023 it fell to R16.41 by 22 Jun 2026 (−17.2%), so GLD's +113.4% in USD over that span was +76.7% in rand.
  • Rand drawdowns were not reliably smaller — over 7 Nov 2014 – 22 Jun 2026, gold's worst rand drawdown was −25.2% (month-end, Jul 2020 – Mar 2021) against −20.5% in USD; silver's was similar in both currencies (−36.1% vs −36.8%); copper's was smaller in rand (−19.2% vs −34.2%).
  • Silver is a volatility problem, not a buy-and-hold — 7.5% USD CAGR from SLV's 28 Apr 2006 inception, with 32.3% annualised volatility and a −72.2% month-end peak-to-trough fall (Apr 2011 – Mar 2020; −76.3% on daily closes).
  • CPER's weak return mostly reflects copper's own path — CPER returned +58.4% in USD over 30 Dec 2011 – 22 Jun 2026 (3.2%/yr). On monthly averages from Dec 2011 to May 2026 (approximate), the copper price rose 4.1%/yr and CPER 3.2%/yr; the gap of 1.0 percentage points a year combines futures roll, fees and basis, net of collateral income.
Methodology & data integrity

Corrected 2026-10-01 (D-514). No observed USD/ZAR series was available when this note was first prepared, and its rand series was reconstructed from anchors. Its intermediate points did not match observed USD/ZAR — implied R20.34 / R24.86 / R29.86 / R22.98 at year-ends 2018/20/22/24 against observed R14.35 / R14.69 / R17.02 / R18.86 — and have been withdrawn, together with every rand drawdown and volatility figure derived from them and the statements built on those figures. Rand path statistics are now shown only where observed FX exists (7 Nov 2014 – 22 Jun 2026). All statistics were re-measured on 1 Oct 2026 from the same vendor's data; prices still end 22 Jun 2026.

Prices: daily adjusted closes for GLD, SLV and CPER via Alpha Vantage. Windows are stated with every figure: each ETF from its first date (GLD 18 Nov 2004, SLV 28 Apr 2006, CPER 15 Nov 2011); a common window 30 Dec 2011 – 22 Jun 2026; and the observed-FX window 7 Nov 2014 – 22 Jun 2026. Figures from different windows are not comparable.

Currency: Alpha Vantage FX_DAILY USD/ZAR, first observation 7 Nov 2014. A rand price is the dollar close times that day's USD/ZAR close; 1 ETF trading day without an FX observation (29 Dec 2014) carries the previous close. The Dec-2004 rate of R5.75 is unverified; rand figures that depend on it are labelled estimates and carry no path statistics.

Statistics: CAGR is endpoint-to-endpoint and is reported separately from path statistics. Volatility uses full calendar-month returns, annualised. Maximum drawdown is given on month-end points and, where noted, daily closes. USD Sharpe uses the 3-month US Treasury yield as the risk-free rate; a rand Sharpe ratio is withheld because no authorised South African risk-free series is available.

Two currencies, one observed window

Endpoint returns and path statistics answer different questions. Over 7 Nov 2014 – 22 Jun 2026 the rand's depreciation added roughly its own 3.3% a year to each ETF's rand CAGR. On monthly data, each ETF's USD return was negatively correlated with the change in USD/ZAR (GLD −0.35, SLV −0.44, CPER −0.50), which damped rand volatility for silver and copper but not for gold: gold's rand volatility (16.7%) exceeded its dollar volatility (15.1%).

Annualised return (CAGR): USD vs ZAR — observed-FX window, 7 Nov 2014 – 22 Jun 2026
Same window and endpoints for all three ETFs; USD/ZAR rose 3.3% a year over it. Longer windows start before observed USD/ZAR and are shown in USD only.

Observed-FX window, 7 Nov 2014 – 22 Jun 2026: USD and ZAR

GLD USDGLD ZARSLV USDSLV ZARCPER USDCPER ZAR
CAGR (endpoint)11.1%14.8%12.4%16.1%5.7%9.1%
Volatility (monthly, annualised)15.1%16.7%28.7%25.7%20.7%18.4%
Max drawdown, month-end−20.5%−25.2%−36.8%−36.1%−34.2%−19.2%
Max drawdown, daily−24.5%−30.8%−45.4%−42.6%−38.4%−27.5%
Best 12 months+83.7%+69.4%+200.2%+156.2%+86.0%+52.3%
Worst 12 months−13.4%−21.6%−25.1%−27.7%−29.1%−12.3%
USD Sharpe0.70withheld0.53withheld0.30withheld
Corr. of USD return with USD/ZAR change−0.35—−0.44—−0.50—

Alpha Vantage adjusted closes and FX_DAILY USD/ZAR, 7 Nov 2014 – 22 Jun 2026; 138 full calendar months (Dec 2014 – May 2026) for volatility, correlation and Sharpe. Rand Sharpe withheld: no authorised South African risk-free series.

USD only: each ETF from inception, and the common window

GLDSLVCPER
First date18 Nov 200428 Apr 200615 Nov 2011
CAGR from first date10.5%7.5%3.0%
Volatility from first date17.0%32.3%19.8%
Max drawdown from first date, month-end−42.9%−72.2%−50.0%
Max drawdown from first date, daily−45.6%−76.3%−54.0%
USD Sharpe from first date0.590.350.17
CAGR, 30 Dec 2011 – 22 Jun 20266.6%5.6%3.2%
Volatility, 30 Dec 2011 – 22 Jun 202615.6%29.0%19.8%
USD Sharpe, 30 Dec 2011 – 22 Jun 20260.420.310.18

Rand returns for these windows are withheld: each starts before the first observed USD/ZAR (7 Nov 2014). The one long-run rand figure on this page — gold at an estimated 16.2%/yr over 31 Dec 2004 – 22 Jun 2026 — rests on the unverified Dec-2004 rate of R5.75 and is an estimate.

Growth of $100 in gold (GLD), 31 Dec 2004 = 100, USD, month-end — log scale
$100 became $878 by 22 Jun 2026. The rand line published on 24 Jun 2026 has been withdrawn; the chart below shows gold in rand on observed USD/ZAR.
Gold (GLD) in USD and ZAR on observed USD/ZAR, 7 Nov 2014 = 100 — log scale
Month-end points, 7 Nov 2014 – 22 Jun 2026. The gap between the lines is the observed change in USD/ZAR; it narrowed after the rand's May 2023 low.
Five findings that drive the theses

1 · Gold had the highest USD return per unit of volatility of the three ETFs in each window measured (USD Sharpe 0.59 from inception, 0.42 over 30 Dec 2011 – 22 Jun 2026, 0.70 over 7 Nov 2014 – 22 Jun 2026).

2 · The rand was a return contribution over this window; drawdown effects depended on timing. USD/ZAR rose 3.3% a year over 7 Nov 2014 – 22 Jun 2026, but gold's worst rand drawdown (−25.2%, Jul 2020 – Mar 2021, month-end) came while the rand was strengthening.

3 · Silver is the highest-torque metal — in both directions. Best 12 months +200.2% (to Feb 2026) and worst −40.5% (to Nov 2013) in USD from SLV's inception; in the theses below it is a sized, tactical expression.

4 · Copper-the-metal ≠ copper-the-ETF, but the gap is modest. The copper price rose 4.1%/yr and CPER 3.2%/yr (monthly averages, Dec 2011 – May 2026, approximate); CPER's weak return mostly reflects copper's own path. Producers carry a different exposure — operating leverage, costs and jurisdiction risk — not the futures index.

5 · Diversification is real. GLD and CPER monthly USD returns correlated 0.32 over 30 Dec 2011 – 22 Jun 2026 (0.26 over 7 Nov 2014 – 22 Jun 2026): the monetary and industrial legs moved partly independently.

The decade ahead

The theses


Each thesis follows the MCH macro-lens discipline: a single testable claim, the indicators that confirm or refute it, the mechanism and its counter, US-listed expression vehicles, review triggers, and a kill switch. Probabilities are explicit and sum to 100%. US-listed comparatives only.

01
Monetary · The reserve metal

Fiscal dominance & de-dollarisation drive a structural gold bull

Claim. Gold sustains a real (above-US-CPI) uptrend through 2035 as central-bank reserve diversification and deficit monetisation override the headwind of higher-for-longer policy rates. The claim is stated in USD real terms; any rand outcome also depends on a USD/ZAR path this note does not forecast.
Conviction split
Base 60%
Up 20%
Down 20%
Regime indicators
IndicatorConfirms thesisRefutes thesis
Central-bank net gold buying>800 t/yr sustainedTurns net selling
US deficit / GDPHolds >6%Falls below 3%
10-yr TIPS real yieldDrifts below 1.5%Holds >2.5%
Gold share of global reservesRising vs USTsReverses to Treasuries
Mechanism
Post-2022 reserve weaponisation pushed non-aligned central banks (China, India, Türkiye, Gulf, CEE) to swap Treasuries for gold — a price-insensitive, structural bid. With debt >$37tn and 6%+ deficits, the Fed cannot durably hold real rates high without crushing debt service, so the market discounts eventual financial repression. Gold prices that discount.
Counter-mechanism
If Warsh genuinely restores positive real rates and fiscal consolidation narrows the deficit, the opportunity cost of a zero-yield asset rises and gold de-rates — the 2011–15 analogue, when GLD fell 42.9% in USD (month-end, Aug 2011 – Dec 2015; 45.6% on daily closes).
Expression vehicles · US-listed
TickerWhy this vehicle
GLD / IAUPhysical core; purest, most liquid exposure
GDXSenior miners — operating leverage to the gold price
GDXJJuniors — higher torque, higher idiosyncratic risk
NEM · AEMBest-in-class operators; dividend + execution quality
WPM · FNV · RGLDRoyalty / streaming — gold-price margin without operating risk
▲ Confirmation triggers
  • CB buying accelerates >1,000 t/yr
  • 10-yr real yield breaks below 1.0%
  • A sovereign-credit or debt-ceiling event
▼ Refutation triggers
  • Real yields hold >2.5% for two quarters
  • Deficit/GDP falls below 3%
  • Central banks turn net sellers
Kill switch

If 10-yr TIPS real yields hold above 2.5% for two consecutive quarters while the federal deficit narrows below 3% of GDP, the debasement thesis is broken and the gold overweight comes off.

Aligns with the standing MCH "USD devaluation" macro book (gold miners + royalty/streaming as primary expression).

02
Industrial · The bottleneck metal

The electrification supercycle makes copper the binding constraint

Claim. A structural refined-copper deficit drives copper to new real highs over the decade. On the backtest, CPER trailed the copper price by about 1.0 percentage points a year (monthly averages, Dec 2011 – May 2026, approximate); producers offer a different exposure, with operating leverage and company-specific risk.
Conviction split
Base 55%
Up 25%
Down 20%
Regime indicators
IndicatorConfirms thesisRefutes thesis
Refined-copper balanceDeficit wideningSwings to surplus
LME+COMEX+SHFE inventoriesDrawing downBuilding for 2+ quarters
Copper vs ~$9,000/t incentive priceSustained aboveHolds below
Data-centre power under constructionRisingStalls / cancellations
Mechanism
AI data centres use 27–33 t of copper per MW, and the grid to feed them needs 3–4× more again. Hyperscalers are now outbidding grid suppliers on transformer units. On supply, the IEA sees existing+planned mines covering only ~70% of 2035 demand; new ore is lower-grade, deeper and slower to permit. Price must rise to ration demand.
Counter-mechanism
Much of the 2025 rally is expectation-driven; US tariff front-running swelled visible inventory. If the AI build stalls on power/permitting (12 GW announced, 5 GW building) or China demand stays soft, no true deficit bites until ~2029 and copper caps ~$10–11k.
Expression vehicles · US-listed
TickerWhy this vehicle
FCXFreeport — purest large-cap copper leverage, US-listed
SCCOSouthern Copper — low-cost, high-margin (Peru risk)
TECKTeck — diversified copper-transition story
COPXGlobal X Copper Miners — basket exposure
CPERCopper futures index; trailed the copper price by about 1.0 percentage points a year over the backtest (approximate)
▲ Confirmation triggers
  • Exchange inventories draw below ~3 weeks of use
  • Major Chile/Peru/DRC mine disruption
  • Copper holds above $12k
▼ Refutation triggers
  • Hyperscaler capex guidance cut
  • Data-centre power approvals stall further
  • China grid/property demand contracts
Kill switch

If visible exchange inventories build for two consecutive quarters while copper trades below the ~$9,000/t incentive price, the deficit is not yet live — cut the copper-producer overweight to a watch position.

03
Infrastructure · AI's real constraint

The bottleneck is electrons, not chips — the power and the grid

Claim. Through 2030 the binding constraint on AI is electrical capacity and equipment, not GPUs. The durable compounders are the owners and builders of generation, transmission and data-centre power, where order books are visible years out.
Conviction split
Base 60%
Up 25%
Down 15%
Regime indicators
IndicatorConfirms thesisRefutes thesis
Transformer / switchgear lead timesLengthening past 5 yrsNormalising
Hyperscaler forward capex guidanceRisingCut >20% YoY
Power-equipment book-to-bill>1.0 and risingFalls below 1.0
Data-centre interconnection queueGrowingClears / reform floods supply
Mechanism
Electrical equipment is <10% of data-centre cost but 100% of the bottleneck. Transformer lead times have blown out from ~2 years to ~5. Of 12 GW announced for 2026, only ~5 GW is building — the gate is power. The winners locked in PPAs and equipment orders 3–4 years ago; this is a multi-year, supply-constrained order book.
Counter-mechanism
An AI-capex air-pocket — a DeepSeek-style efficiency shock that collapses compute intensity, or model-economics disappointment — would deflate the entire chain fast. Policy mismatch (accelerating AI while throttling renewables) could also raise power costs.
Expression vehicles · US-listed
TickerWhy this vehicle
GEVGE Vernova — grid equipment + gas + nuclear; cleanest pure-play
ETNEaton — electrical distribution & data-centre power
VRTVertiv — data-centre power & thermal management
PWRQuanta — transmission & grid construction
CEG · VSTIndependent power / nuclear baseload for AI load
CCJCameco — uranium fuel for the nuclear leg
▲ Confirmation triggers
  • Transformer lead times extend past 5 yrs
  • New multi-GW PPAs & nuclear restarts/SMRs
  • Backlogs and book-to-bill keep climbing
▼ Refutation triggers
  • Hyperscaler capex guidance cut
  • A step-change in compute efficiency
  • Interconnection reform that floods supply
Kill switch

If the top-four hyperscalers collectively cut forward capex guidance by more than 20% year-on-year, the demand pillar is breaking and the infrastructure overweight comes off.

Dovetails with the standing MCH "AI supply-side infrastructure" book (TSM · CEG · GEV).

04
Hybrid · The torque trade

Silver is the highest-torque expression of both themes — a sizing problem, not a hold

Claim. Silver outperforms gold in the cyclical up-leg as the gold:silver ratio mean-reverts — it is monetary and industrial (solar, electronics) — but its −72.2% month-end drawdown (Apr 2011 – Mar 2020) and 32.3% annualised volatility (SLV in USD from 28 Apr 2006) make it a tactical, position-sized expression in this framework.
Conviction split
Base 50%
Up 30%
Down 20%
Regime indicators
IndicatorConfirms thesisRefutes thesis
Gold:silver ratio vs long-run meanElevated (silver cheap)Compressed / expanding
Solar / PV installation growthRisingThrifting / demand shock
Gold's primary trendLeading higherRolls over
Silver market balanceDeficit wideningSurplus
Mechanism
Silver carries ~50% industrial demand (PV now the largest, fastest-growing slice) on top of a monetary bid that activates in precious-metal bull markets. The float is small, so investment flows amplify it — the backtest shows a best 12-month USD return of +200.2% (Feb 2025 – Feb 2026).
Counter-mechanism
Silver is not a reserve asset — central banks don’t buy it — so it lacks gold’s structural, price-insensitive bid. A demand shock or a gold top removes both legs at once; the reflexivity that powers the up-leg savages the down-leg.
Expression vehicles · US-listed
TickerWhy this vehicle
SLV / PSLVPhysical silver exposure
SIL · SILJSilver miners — extreme operating torque
Long SLV / short GLDExpress the ratio view directly, hedging precious-metals beta
SLV call spreadsDefined-risk upside; the long-only tail was −72.2% (month-end)
▲ Confirmation triggers
  • Gold:silver ratio compresses from elevated levels
  • PV demand surprises to the upside
  • Silver deficit widens
▼ Refutation triggers
  • Gold rolls over
  • Ratio expands (silver lagging)
  • Industrial demand disappoints
Kill switch

If gold itself breaks its primary uptrend — the monetary leg fails — silver’s dual-identity case collapses and the position comes off immediately. Silver does not hold value without gold leading.

Disclaimer. MCH Analysis is a general investment-research publication of MCH Advisory (Pty) Ltd. It is not personal financial advice and does not take your circumstances into account. MCH is not a licensed financial services provider or a registered investment adviser. Past performance, whether actual or simulated, does not predict future results.

Data & sources. Price history: Alpha Vantage (daily adjusted closes for GLD, SLV, CPER; FX_DAILY USD/ZAR from 7 Nov 2014; COPPER monthly). Risk-free rate: 3-month US Treasury yield, MCH research warehouse. Statistics re-measured 1 Oct 2026 by scripts/research/metals-fx-recompute.mjs. Macro: US Federal Reserve / FOMC, Trading Economics, CNBC. Commodities: Wood Mackenzie & IEA critical-minerals outlooks; JPMorgan, Goldman Sachs, Bank of America copper research; industry reporting on AI power. All third-party figures paraphrased.

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MCH Analysis is a general investment-research publication of MCH Advisory (Pty) Ltd. It is not personal financial advice and does not take your circumstances into account. MCH is not a licensed financial services provider or a registered investment adviser. Past performance, whether actual or simulated, does not predict future results. Subscriber Agreement | Privacy and Cookie Notice | Research Governance Policies