02:54 1. Test whether high prices can cure themselves — the wheat-vs-copper check
The repeatable method
- Ask how fast supply can respond to a price rise: next season (crops) or a decade (mines needing discovery, development, permits)?
- Check the discovery pipeline: exploration spend vs number and size of major discoveries, and how much found resource is stuck in feasibility.
- Map where the remaining resource sits — geographic concentration adds permitting and political risk that slows supply further.
Here: wheat supply responds next year; copper "you need to find it… develop it… get permits" (
03:12); only six major discoveries (~9 Mt) in 2020–25, ~500 Mt in feasibility (
03:40); Latin America ~55% of major discovered copper (
04:12).
Watch for
- A pickup in major discoveries or feasibility-to-production conversions; permitting shocks in Latin America.
04:39 2. Decompose each "copper stock" by actual commodity exposure before comparing
The repeatable method
- Break each candidate's EBITDA into commodities (and non-mining arms like trading).
- Use the mix to explain relative stock performance — a lagging name may just be the other commodity's weakness.
- Note partial substitutes (aluminium for copper) as diversification rather than dilution.
Here: FCX ~pure copper,
BHP ~54%,
RIO ~36% + ~20% aluminium,
GLEN ~30% + trading and coal,
VALE ~23% / ~80% iron ore (
05:00) — Vale's lag since 2024 is weak iron ore vs strong copper (
02:01).
Watch for
- Copper share rising as projects ramp (Vale doubling copper output); iron-ore price moves driving the diversified names.
07:02 3. Strip boom years out of multi-year profitability averages
The repeatable method
- Compute a seven-year average ROI/ROE for each name, then locate which years drive it.
- If a single commodity boom inflates the average, discount it — "the past is not indicative necessarily of the future."
- Re-think forward profitability from the commodity each company will be most exposed to next, plus logistics (distance to the main buyer).
Here: BHP,
VALE,
RIO lead the seven-year averages only because 2021–22 were exceptional iron-ore years (
07:39); Australian producers sit close to Asian demand while Vale ships bulky ore from South America (
08:13).
Watch for
- Profitability at current copper prices vs the historical average — he expects it to "look much different."
08:56 4. Screen leverage with a simple rule — then adjust for businesses that carry inventory-financing debt
The repeatable method
- Apply a rule of thumb: debt-to-equity ≤50% and interest coverage ≥5×.
- For an outlier, ask why: trading/marketing businesses borrow against liquid inventories and receivables, so use net debt, not gross.
- Confirm with the credit rating and note how far each sits above the BBB− investment-grade cutoff.
Here: GLEN fails the gross screen but gross debt ~$45bn vs net ~$10bn — "also a safe balance sheet player" (
09:44); BHP/Rio single-A, Glencore/Vale BBB+/BBB,
FCX BBB− "right above the speculative grade cutoff" (
10:15).
Watch for
- Leverage creeping up with copper growth capex; any downgrade toward the junk line (Freeport first).
10:36 5. Rank on quality first; use valuation to decide when, not which
The repeatable method
- Score each name on asset quality (tier-one), through-cycle profitability, credit rating, exposure to the thesis commodity and shareholder-return policy.
- Rank by that score — not by cheapness; the cheapest name often carries the structural problems (legacy liabilities, the wrong commodity).
- Only then check valuation (forward FCF yield, scenario DCF) to decide whether today is an entry.
Here: "I used to be more valuation focused but I realized that I have to just focus much more on quality. So… BHP is my number one" (
10:36);
VALE is cheapest but carries Samarco/Brumadinho liabilities and iron-ore dependence (
13:34).
Watch for
- The quality leaders' premium narrowing vs the cheaper names.
01:00 6. Match a business model to your macro regime — volatility beneficiaries in a fragmented world
The repeatable method
- State your macro regime view (here: a more fragmented, geopolitically volatile world).
- Look in past shocks (war outbreaks) for which names spiked most relative to peers — that reveals built-in volatility exposure.
- Favour the business model that earns from the regime itself (trading/marketing), not just from the commodity price.
Here: GLEN spiked hardest in 2022 (Ukraine) and 2026 (Iran) because "higher war and geopolitical volatility results in higher earnings" (
01:26); "the trader plus commodity player like Glencore could benefit" (
12:32).
Watch for
- Glencore marketing EBIT in volatile quarters; the October Australian listing's effect on liquidity and multiple.
11:24 7. When the story is priced in, pre-rank the list and wait for the crash
The repeatable method
- If a widely known thesis has every name at fair value or a premium, don't compromise on price — "optimism is priced in."
- Keep the ranked list ready; treat broad sell-offs and recessions (when cyclicals fall hardest) as the entry.
- Size up aggressively on the top-ranked name when it comes ("load the truck").
Here: "none of these looks cheap" (
05:46); for
BHP "if there is a recession… this could crash. I could maybe load the truck" (
11:24); "I want them to basically crash and then I can pick my favorites" (
16:09).
Watch for
- Sector drawdowns (miners fell ~5% in a day just before recording); recession signals from his macro framework.
Methods distilled from the public YouTube video "5 Copper Stocks: Which Is Best? | Copper Series" (Peter Lukacs Research). Not investment advice.