A copper stocks screener in Excel ranks copper producers, diversified miners, and royalty companies on valuation, leverage, and momentum pulled by MarketXLS formulas, and tests them against copper price scenarios. It fits the June 2026 setup, when copper demand is driven increasingly by AI data centers, electric vehicles, and power grid build-outs rather than construction in China alone. This guide walks through a complete Excel template that does exactly that, built on MarketXLS formulas and refreshed by a single ticker change.
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Why Copper Belongs On Your June 2026 Watchlist
Copper sits at the intersection of three demand stories that are all running at once.
The first is electrification. Every gigawatt of new solar generation requires roughly five thousand tonnes of copper. Wind requires more. Battery storage adds another layer. The International Energy Agency has been quietly raising its 2030 copper demand estimates for three straight years.
The second is electric vehicles. A traditional combustion vehicle uses about 20 kilograms of copper. A battery electric vehicle uses more than 80. Hybrid plug-ins fall in between. As the global EV fleet share rises, copper demand per car rises with it.
The third demand vector is the one that has only become obvious in 2025 and 2026: AI data center build-out. A single hyperscale data center campus can require thousands of tonnes of copper for power distribution, cooling, and interconnect. Hyperscalers are racing to bring capacity online, and the copper supply chain was not built to absorb a sudden new demand vector on top of two existing ones.
Supply, meanwhile, is concentrated. Chile, Peru, and the Democratic Republic of the Congo produce most of the world's copper. Permitting timelines for new mines run seven to fifteen years. Industry capex was underbuilt during the 2014 to 2020 commodity bear market, which means the supply response to higher prices is structurally lagged.
That backdrop is why the equity opportunity in copper miners is not a single trade. It is a basket trade with real dispersion across pure-plays, diversified majors, and royalty companies. A screener that surfaces the dispersion is more useful than any single stock pick.
The 12-Name Copper Universe
The template covers twelve US-listed copper-linked equities. The mix is deliberate.
| Ticker | Company | Exposure Type | Why It Is On The List |
|---|---|---|---|
| FCX | Freeport-McMoRan | Pure-play | Largest US-listed copper producer with Grasberg mine in Indonesia |
| SCCO | Southern Copper | Pure-play | Lowest cost producer in Peru and Mexico, controlled by Grupo Mexico |
| BHP | BHP Group ADR | Diversified | World's largest diversified miner with Escondida exposure |
| RIO | Rio Tinto ADR | Diversified | Kennecott and Oyu Tolgoi assets, plus iron ore ballast |
| TECK | Teck Resources Class B | Diversified | QB2 ramp-up and Highland Valley, pivoting harder to copper |
| HBM | Hudbay Minerals | Pure-play | Peru and Snow Lake assets, mid-cap pure-play |
| ERO | Ero Copper | Pure-play | Brazilian pure-play with new mine ramp |
| ANFGY | Antofagasta ADR | Pure-play | Chilean pure-play, family-controlled |
| GLNCY | Glencore ADR | Diversified | DRC and Zambia production plus the largest physical trading desk |
| VALE | Vale ADR | Diversified | Brazil iron ore giant with growing copper book |
| WPM | Wheaton Precious Metals | Royalty | Streaming exposure with built-in downside cushion |
| COPX | Global X Copper Miners ETF | ETF | Benchmark exposure across the cohort |
Pure-plays give you the cleanest copper price torque. Diversified majors dampen that torque with iron ore, coal, energy, and trading revenues. Royalty names like WPM trade beta for cushion. The ETF captures the cohort average. Owning a slice of each is how a basket-style copper trade typically gets built.
What The Excel Template Does
The workbook has ten sheets, all wired together with MarketXLS formulas.
| Sheet | What It Delivers |
|---|---|
| Cover | Title, version, and table of contents |
| How To Use | Five-minute walkthrough |
| Dashboard | KPI tiles, conditionally formatted screener, embedded charts |
| Holdings | Yellow input cells for tickers, shares, and cost basis |
| Scenario Analysis | Portfolio value under four copper price scenarios |
| Valuation Comparison | P/E, P/B, EV/EBITDA, operating margin heatmap |
| Exposure Tilt | Suggested allocation by exposure type |
| Macro Backdrop | Copper spot, copper-to-gold ratio, DXY, 10-year Treasury |
| Methodology | How the model strings together |
| Glossary | Mining terms plus the educational disclaimer |
The Holdings sheet is the only place you need to touch to make the workbook yours. Yellow cells with gold borders accept your tickers, share counts, and cost bases. Everything else updates automatically.
The MarketXLS Formula Stack
Every metric in the screener comes from a MarketXLS function. There is no pasted data, no static cell. Here is the formula stack that powers the Dashboard.
Price and market value
=QM_Last("FCX")
=Holdings!G12*QM_Last("FCX")
Formula documentation: QM_Last
The first formula returns the current price for Freeport-McMoRan. The second multiplies the share count on the Holdings sheet by the live price to get market value. Swap the ticker and the entire row recalculates.
Valuation multiples
=PERatio("FCX")
=PriceToBook("FCX")
=EVtoEBITDA("FCX")
Formula documentation: PERatio, PriceToBook
P/E is trailing twelve months. P/B uses current price over book value per share. EV/EBITDA is the industry standard for mining because it normalizes capital structure across MLPs, royalty companies, and operating companies. A mining cohort comparison without EV/EBITDA misses the point.
Quality and risk
=OperatingMargin("FCX")
=Beta("FCX")
=DividendYield("FCX")
Formula documentation: OperatingMargin, Beta, DividendYield
Operating margin is the quality screen for cost-curve position. Beta versus market is a risk read. Dividend yield surfaces the income kicker that diversified majors like RIO and BHP provide alongside the copper torque.
Classification
=Sector("FCX")
=Industry("FCX")
Formula documentation: Sector, Industry
Sector and Industry feed the Exposure Tilt sheet, which buckets each name into pure-play, diversified, royalty, or ETF.
How To Read The Dashboard
The Dashboard opens with six KPI tiles. Reading them left to right is the fastest way to size up the portfolio.
Portfolio Value is the sum of shares times current price across all twelve holdings. It is the headline number. Compare it to your cost basis to read the gain.
Weighted P/E is the value-weighted P/E ratio across the basket. The cohort historically trades between 10x and 25x, with diversified majors anchoring the low end and pure-play small caps stretching the high end. A value-weighted P/E above 25x suggests the cohort is pricing in a strong copper rally.
Weighted EV/EBITDA does the same exercise for EV/EBITDA. The miner cohort historical range is 5x to 12x. Below 6x is bargain territory in a commodity cycle. Above 12x means you are paying up for either growth or a high-quality royalty.
Weighted Dividend Yield captures the income side. Diversified majors like RIO, BHP, and VALE typically yield 4 percent to 8 percent. Pure-play growth names yield closer to zero. A weighted yield above 3 percent means your basket leans toward the diversified majors.
Weighted Beta is value-weighted market beta. A beta above 1.2 means the basket will move more than the market in either direction. Pure-play tilts will push beta higher.
Gain Percent compares portfolio value to total cost basis. Conditional icons turn green when the portfolio is above cost.
Below the KPI row sits the screener table itself. Conditional color scales paint each metric: green where the metric is favorable, red where it is stretched, yellow in the middle. Data bars on the Market Value column show position size relative to the largest holding. Icon sets on the Gain Percent column flag winners and laggards at a glance.
The Copper Price Scenario Sheet
The Scenario Analysis sheet runs four copper price scenarios out one year.
| Scenario | Copper Price ($/lb) | Producer Margin | Portfolio Value Change |
|---|---|---|---|
| Soft Tape | $3.50 | Margin compression on lower-grade ore | -32% |
| Range-Bound | $4.50 | Margins stable at current levels | -7% |
| Base Case | $5.25 | Producer margins expand modestly | +10% |
| Tight Supply | $7.00 | DRC and Chile disruption, EV demand spike | +42% |
The Soft Tape scenario assumes copper retreats toward 3.50 per pound on a China slowdown and a softer global manufacturing PMI. Margins compress because lower-grade ore is uneconomic at that price. Pure-play miners suffer most.
The Range-Bound scenario is roughly the consensus path. Copper holds near 4.50 per pound, margins stay steady, and the basket grinds sideways with modest dividend income.
The Base Case scenario assumes copper trades to 5.25 per pound on continued electrification and AI data center demand. Margins expand because the marginal cost producer is well below that price.
The Tight Supply scenario is the tail risk to the upside. A DRC or Chile production disruption combined with an EV demand spike could push copper to 7.00 per pound. Pure-play miners see operating margin double, and the basket value would rise sharply.
The producer beta to copper at the operating margin level is in the 1.0 to 1.4 range for pure-plays. Diversified majors run closer to 0.4 to 0.6 because iron ore and energy revenues offset. Royalty companies have built-in caps and floors. The Scenario sheet bakes these betas into the implied portfolio value column.
Valuation Comparison: Where The Cohort Trades
The Valuation Comparison sheet is the cohort heatmap. It shows P/E, P/B, EV/EBITDA, operating margin, and beta side by side for every name in the basket.
A few patterns tend to repeat through the cycle.
SCCO consistently shows the highest operating margin in the cohort. That is structural. SCCO controls some of the lowest-cost copper mines in the world, and the company is family-controlled with a long history of dividend distribution. The market rewards that with a premium P/B multiple.
VALE shows the lowest P/E by a wide margin most months. VALE is dominated by iron ore, not copper, so when iron ore demand from China softens, VALE re-rates downward. Copper exposure inside VALE is a quieter story.
WPM trades at the highest EV/EBITDA in the cohort. Royalty businesses earn that multiple because they have low cost of revenue and high free cash flow conversion. The trade-off is the capped upside.
FCX and BHP often trade between the cohort extremes. Both are blue-chip names with index inclusion and ETF flow demand. They are the "buy a basket without overthinking it" choices.
A median cohort P/E line at the bottom of the sheet anchors the comparison. Use it to spot which names trade meaningfully above or below their peers and ask why.
Exposure Tilt: Pure-Play, Diversified, Royalty, or Balanced
The Exposure Tilt sheet shows four allocation recipes.
The Pure-Play tilt overweights FCX, SCCO, HBM, ERO, and ANFGY. This is the recipe for maximum copper price torque. The basket will move sharply with copper, in both directions.
The Diversified tilt overweights BHP, RIO, GLNCY, and VALE. The basket trades more like a global mining ETF, with copper exposure but ballast from iron ore, coal, and trading revenues.
The Royalty tilt overweights WPM. The basket sees less copper torque but more downside cushion. This is the conservative version of the trade.
The Balanced tilt spreads exposure roughly equally across all four types. It is the starter recipe for an investor who wants copper exposure without picking a tilt theme.
Below the tilt table sits a per-ticker target weight table for the Pure-Play tilt. The Cap Allocation column multiplies a 100,000 dollar starter portfolio by the target weight. The Shares column divides the dollar allocation by the live price from QM_Last to give an approximate share count.
The yellow input cells on the Holdings sheet override any of this. The Tilt control on the Holdings sheet picks which recipe flows through.
Macro Backdrop: The Inputs That Move Copper Equities
The Macro Backdrop sheet keeps the commodity and macro inputs that drive copper equity prices.
LME copper spot is the direct revenue driver for every producer in the basket. The sheet tracks both the pound-based US pricing and the tonne-based institutional reference.
WTI crude shows up in producer cost curves through diesel, explosives, and energy-intensive milling. A rising WTI eats into operating margin if copper prices stay flat.
Gold spot anchors the copper-to-gold ratio. A rising copper-to-gold ratio historically aligns with rising 10-year Treasury yields and a growth-on macro regime. A falling ratio flags risk-off.
The 10-year Treasury yield matters because mining capex is long-cycle. Higher discount rates make new mine builds harder to underwrite. This is one reason the supply response to higher copper prices has been so slow.
The DXY dollar index trades inversely with industrial metals priced in dollars. A weakening dollar usually translates to a copper price tailwind, all else equal.
Macro inputs can be hand-entered or pulled with QM_Last on the appropriate futures symbol where available. See the MarketXLS function reference for the exact symbol format.
Building This From Scratch In MarketXLS
If you prefer to recreate the workbook from a blank sheet, here is the build order.
Start with the Holdings tab. Type your ticker in column C. Add the share count and cost basis. Use cell references for everything downstream.
Build the screener row by row. The seven-formula stack covers most of the work:
=QM_Last(C12)
=DividendYield(C12)
=PERatio(C12)
=PriceToBook(C12)
=EVtoEBITDA(C12)
=OperatingMargin(C12)
=Beta(C12)
Formula documentation: QM_Last, DividendYield, PERatio, PriceToBook, OperatingMargin, Beta
Wrap each formula in IFERROR to keep the sheet clean when a ticker temporarily lacks data.
Add the conditional color scales. Green-to-red bands work well for valuation multiples. Reverse the band for operating margin (red on low, green on high). Use data bars on the market value column to show position size visually.
Build the KPI tiles last. SUMPRODUCT does most of the heavy lifting:
=SUMPRODUCT(I11:I22,N11:N22)/SUM(N11:N22)
That formula returns the value-weighted P/E across rows 11 to 22. The same pattern works for EV/EBITDA, dividend yield, and beta.
The full template handles all of this for you. Download links are below.
Download The Templates
Download the templates:
- - Pre-filled with current data
- - Live-updating formulas
The static version is a snapshot dated 2026-06-02 with sample values you can compare against the live workbook. Each cell carries a comment showing the MarketXLS formula that would populate it.
The formula version has no static data outside of the input cells. Every price, valuation multiple, and margin metric calls a MarketXLS function. Open it on a machine with the MarketXLS add-in for Excel installed and it will refresh in seconds.
Frequently Asked Questions
What is a copper stocks screener?
A copper stocks screener is a spreadsheet or tool that ranks copper-linked equities across valuation, quality, and momentum metrics so you can compare them side by side. The MarketXLS version uses live data from QuoteMedia and refreshes on every recalculation.
Why use Excel for a copper stocks screener instead of a web app?
Excel gives you something most web screeners do not: full control over the math, the weights, and the cohort. You can add tickers, change the scenarios, and re-tilt the basket without waiting on someone else's product roadmap. With MarketXLS the data feed is the same one institutional screeners use, but the analysis lives in your workbook.
Which copper stocks have the highest beta to copper price?
Pure-play producers like FCX, SCCO, HBM, and ERO carry the highest beta to copper at the operating margin level, typically in the 1.0 to 1.4 range. Diversified majors like BHP, RIO, and GLNCY have lower copper beta because iron ore, coal, and energy revenues offset. Royalty companies like WPM have the lowest beta because royalty contracts cap upside in exchange for downside protection.
How does the AI data center build-out affect copper demand?
A single hyperscale data center campus can require thousands of tonnes of copper for power distribution, cooling, and interconnect. AI capex announcements from hyperscalers have been adding new copper demand on top of the existing electrification and EV demand vectors. Industry analysts have been revising 2030 copper demand estimates higher to reflect this.
What MarketXLS formulas do I need to build this screener?
The core formulas are QM_Last for live price, PERatio for trailing P/E, PriceToBook for P/B, EVtoEBITDA for the mining standard valuation multiple, DividendYield for income, OperatingMargin for quality, and Beta for risk. Sector and Industry feed the classification. The MarketXLS Excel Functions reference has the full list with parameters.
How often should I refresh a copper stocks screener?
Daily refresh is enough for valuation and price data. The Macro Backdrop sheet benefits from a weekly update of copper spot, gold spot, and the DXY index. Earnings quality screens like operating margin update on a quarter cadence as new financials are filed.
Can this template be used for other commodity stocks?
Yes. The same structure works for gold miners, silver miners, lithium producers, uranium miners, or oil and gas producers. Swap the tickers on the Holdings sheet, adjust the scenario sheet for the new commodity price band, and the rest of the workbook reflows. The MarketXLS formula stack is commodity-agnostic.
The Bottom Line
Copper stocks have moved from a niche cyclical trade to a structural growth story driven by electrification, EVs, and AI infrastructure demand. The supply side cannot respond quickly because new mines take a decade to build. That asymmetry is what makes the basket trade interesting heading into the second half of 2026.
A copper stocks screener in Excel gives you the levers you need. You can swap tickers, run price scenarios, tilt the basket, and watch how the valuation multiples shift across pure-play producers, diversified majors, and royalty names. With MarketXLS the data is live, the math is yours, and the workbook updates with a single recalculation.
Download the templates above and start with the Dashboard sheet. Read the KPI tiles, walk the conditional color scales, and check where your basket sits in the cohort. Use the Scenario sheet to stress-test the position size you actually want to carry. Use the Exposure Tilt sheet to think about whether you want pure-play torque or diversified ballast.
If you want a guided tour of how MarketXLS pulls all of this together inside Excel, book a demo and we will walk you through the workflow. Or explore the rest of the MarketXLS feature set to see what other screeners and dashboards you can build for the rest of your watchlist.
This workbook is provided for educational and informational purposes only and is not investment advice. Past performance does not guarantee future results. All projections and scenarios are hypothetical. Consult a licensed financial advisor before making any investment decision.
