COMMERCIAL METALS Co

CMCAcero EAF · largos + reciclajeactualizado 2026-07-28
Precio
$70.47
IV prob-weighted
$37.18
Gap
-47%
TTM EBITDA≈
$1.17B
Net debt
$2.73B
Margen (percentil hist.)
66%
Twin genérico: ebitda_approx_xbrl (no Adjusted de press releases) · multiplos sectoriales NO optimizados · sin extraccion MD&A todavia (profundizacion pendiente). La señal del gap está INVERTIDA en cíclicas según el backtest de ALTO — no usar como target.

Tesis (determinista — solo hechos computados)

10 lecturas generadas desde artefactos point-in-time, a 2026-08-05; ningún dato inventado

valoracionEl mercado ha valorado este negocio a 4.85–7.39× EV/EBITDA (mediana 5.97×, 1947 días de múltiplo implícito propio, expanding sin look-ahead). [twin_manifest.intrinsic.multiples]
cicloMargen bruto actual 18.3%, percentil 66% de su historia (38 trimestres): zona media del ciclo. [truth_set_quarterly.gross_margin]
driversLa pata metal_spread anticipa la DIRECCIÓN del margen con acierto 62% (n=37, p=0.0939): señal débil — hedging/contratos absorben el spot. [sector_nowcast.json]
realizedPrecio realizado (avg_selling_price_usd_ton) vs spot: corr niveles 0.714, Δ 0.237, captura β 0.44 (n=18): el spot llega al P&L de forma parcial y con ruido trimestral — mismo cuello de botella que ALTO. [realized_model.json]
no hacerEventos: señal pre-filing → +173 bps alineados a 20d (hit 57%, n=37), pooled de la cadena NO significativo (t=1.5). La señal predice márgenes, no retornos: no operar el filing. [event_study.json]
no hacerGap precio/IV actual -47%: señal INVERTIDA en cíclicas (backtest ALTO corr −0.32) — es contexto de dónde está el ciclo, no un target de compra. [twin_manifest.intrinsic.last_gap]
evidencia66/66 métricas operativas del MD&A con cita textual verificada (27 trimestres) — pendiente de auditoría de capa 2. [mdna_operational.csv]
costeEl commodity solo explica el 6% de la varianza del cambio de margen; el 94% restante es coste unitario, mix y volumen (AR1 del residuo -0.285: revierte). [margin_decomposition.json]
costeModelos probados sobre la misma ventana: regla de signo 64%, OLS commodity 60%, OLS+coste 72%, signo+coste 76%. Gana signo+coste: añadir maquinaria de coste no mejora el baseline sin parámetros. [margin_decomposition.json]
riesgosLa empresa declara 36 factores de riesgo en su 10-K de 2025-10-16, 1 nuevos frente al de 2024-10-17. Concentracion: operacional 25, coste insumos 9, financiero 9. [risk_factors.json]

Precio vs valor (point-in-time)

¿Dónde cotiza el precio frente al rango de valor del modelo? · USD/acción · diario (submuestreo semanal)
fuente: intrinsic_daily.csv

Conclusión: el backtest muestra que “precio por debajo del IV” ha sido señal de techo de ciclo en esta cíclica (corr −0.32 a 60d) — leer este gráfico como semáforo de compra rompe la tesis.

Trimestres (últimos 16 de 38)

Truth set XBRL con fecha de primera publicación y accession por dato

TrimestreRevenueGM%EBITDA≈PublicadoAccession
2026Q2$2.48B18.3%$340.2M2026-06-290000022444-26-000041
2026Q1$2.13B18.2%$257.3M2026-03-310000022444-26-000031
2025Q4$2.12B19.2%$284.2M2026-01-080000022444-26-000010
2025Q3$2.11B18.6%$286.2M2025-10-160000022444-25-000138
2025Q2$2.02B14.8%$196.5M2025-06-240000022444-25-000098
2025Q1$1.75B12.5%$122.6M2025-03-250000022444-25-000060
2024Q4$1.91B16.1%$200.5M2025-01-060000022444-25-000013
2024Q3$2.00B16.2%$224.8M2024-10-170000022444-24-000140
2024Q2$2.08B16.4%$243.1M2024-06-250000022444-24-000089
2024Q1$1.85B16.0%n/d2024-03-260000022444-24-000069
2023Q4$2.00B19.9%$305.6M2024-01-080000022444-24-000017
2023Q3$2.21B19.2%$311.2M2023-10-120000022444-23-000126
2023Q2$2.34B20.6%$374.1M2023-06-220000022444-23-000077
2023Q1$2.02B19.6%n/d2023-03-230000022444-23-000058
2022Q4$2.23B22.8%$402.7M2023-01-090000022444-23-000014
2022Q3$2.41B21.1%$403.0M2022-10-130000022444-22-000140

Nowcast direccional sectorial

Dirección del margen bruto vs pata de commodity (point-in-time, réplica del M10 de ALTO)

PataAcierto direccionalnp (1 cola)
metal_spread primaria (a priori)62%370.0939
steel_ppi46%370.7443
scrap_ppi41%370.9061

dirección del promedio trimestral de la pata (solo obs publicadas antes del filing, lag 14d mes+1) vs dirección del cambio de margen — regla de signo sin parámetros, réplica del M10 de ALTO

Métricas operativas del MD&A (extracción auditada)

Qwen3-4B local + verificación determinista de citas (rapidfuzz ≥85)

TrimestreMétricaValorCita textualEstado
2017Q3tons_shipped_k1000Each of these segments realized increases in tons shipped and average selling prices.rechazado
2021Q3avg_selling_price_usd_ton0Net sales in our North America segment increased in 2021 compared to 2020, primarily due to a year-over-year increase in steel products average selling prices and raw materials average selling prices,rechazado
2017Q3avg_selling_price_usd_ton1000The increase in average scrap selling price also led to an increased average selling price for our Americas Mills segmentrechazado
2025Q3scrap_cost_usd_ton0metal margin is the difference between the average selling price per ton of rebar, merchant bar and other steel products and the cost of ferrous scrap per ton utilized by our steel mills to produce threchazado
2024Q3metal_margin_usd_ton534Steel products metal margin per ton534 628auditado ✓
2024Q4metal_margin_usd_ton0The change in net earnings in the three months ended February 28, 2025, compared to the corresponding period, was due to compression in steel and downstream products metal margins in our North Americarechazado
2026Q1metal_margin_usd_ton0The change in net earnings in the three months ended May 31, 2026, compared to the corresponding period, was primarily due to expansion in steel products metal margins within our North America Steel Grechazado
2017Q4scrap_cost_usd_ton288Cost of ferrous scrap utilized 288 245 272 223auditado ✓
2021Q4metal_margin_usd_ton0The significant expansion of steel products metal margin per ton in both of our segments and raw materials margin over purchase cost per ton in our North America segment.rechazado
2021Q4scrap_cost_usd_ton0Selling prices for steel products and raw materials outpaced the rising input costs of ferrous scrap utilized in our steel mill operations and the price paid to purchase ferrous and nonferrous scrap irechazado
2022Q1avg_selling_price_usd_ton0The growth in net sales is largely attributable to rising selling prices across all major product lines in both of our segments for the three and nine months ended May 31, 2022, compared to the corresrechazado
2017Q4avg_selling_price_usd_ton571Average price (per short ton) Total sales $ 571 $ 524 $ 561 $ 511auditado ✓
2018Q1metal_margin_usd_ton303Metal margin 303 274auditado ✓
2022Q4scrap_cost_usd_ton325Cost of ferrous scrap utilized per ton325 428auditado ✓
2020Q3avg_selling_price_usd_ton618Average selling price per ton Steel products$618 $681auditado ✓
2019Q3avg_selling_price_usd_ton528Average price (per ton) Total sales $ 528 $ 560auditado ✓
2018Q3avg_selling_price_usd_ton612Average price (per short ton) Total selling price $ 612 $ 526auditado ✓
2017Q4metal_margin_usd_ton283Metal margin 283 279 289 288auditado ✓
2018Q3metal_margin_usd_ton309Metal margin 309 283auditado ✓
2018Q4metal_margin_usd_ton372Cost of ferrous scrap utilized 303 288 305 272 Metal margin 374 283 372 289auditado ✓
2020Q3metal_margin_usd_ton380Steel products metal margin per ton380 397auditado ✓
2025Q4metal_margin_usd_ton0The change in net earnings in the three months ended February 28, 2026, compared to the corresponding period, was primarily due to expansion in steel products metal margins within our North America Strechazado
2021Q1scrap_cost_usd_ton3Cost of ferrous scrap utilized per ton$3auditado ✓
2023Q1scrap_cost_usd_ton0Cost of raw materials per ton$619 $908rechazado
2025Q4avg_selling_price_usd_ton0The change in net earnings in the three months ended February 28, 2026, compared to the corresponding period, was primarily due to expansion in steel products metal margins within our North America Strechazado
2020Q1avg_selling_price_usd_ton606Average price (per ton) Total selling price$606 $670 $604 $674auditado ✓
2018Q1avg_selling_price_usd_ton314Average selling price (per short ton) Ferrous $ 314 $ 264auditado ✓
2025Q4tons_shipped_k0Net sales increased $377.6 million, or 22%, for the three months ended February 28, 2026, compared to the corresponding period.rechazado
2025Q3avg_selling_price_usd_ton0We focus on changes in average selling price per ton and tons shipped compared to the corresponding period for each of our vertically integrated product categories as these are the two variables that rechazado
2020Q3scrap_cost_usd_ton238Cost of ferrous scrap utilized per ton$238 $284auditado ✓
2023Q4metal_margin_usd_ton-1compression in steel products metal margins in both our North America Steel Group segment and Europe Steel Group segment, driven by decreases in steel products average selling prices, while the cost orechazado
2022Q4metal_margin_usd_ton695Steel products metal margin per ton695 548auditado ✓
2024Q1avg_selling_price_usd_ton-11declining steel products average selling prices per tonrechazado
2023Q3scrap_cost_usd_ton0the cost of ferrous scrap utilized per ton remained relatively flatrechazado
2025Q3metal_margin_usd_ton0changes in metal margins of our steel products and downstream products period-over-period in the North America Steel Group and Europe Steel Group segments are a consistent area of focus for our Companrechazado
2025Q1metal_margin_usd_ton400The decrease in net earnings for the three months ended May 31, 2025, compared to the corresponding period, was primarily due to compression in steel and downstream products metal margins within our Nrechazado
2019Q3tons_shipped_k1460Shipped 1,460 1,500auditado ✓
2020Q4metal_margin_usd_ton346Steel products metal margin per ton346 400auditado ✓
2020Q4scrap_cost_usd_ton266Cost of ferrous scrap utilized per ton$266 $226auditado ✓
2019Q4avg_selling_price_usd_ton226Average ferrous selling prices per ton decreased approximately 15% and 24%, respectivelyrechazado

El eslabón coste: por qué el margen no se deja predecir

ΔMargen bruto descompuesto en la parte que explica metal_spread y el residuo (coste unitario, mix y volumen), walk-forward sobre 37 trimestres

R² del commodity
7%
Residuo (coste+mix+volumen)
94%
AR(1) del residuo
-0.28
Modelo (misma ventana de test)Acierto direccionaln
Regla de signo (sin parámetros)64%25
OLS sobre el commodity60%25
OLS + momentum de coste72%25
Signo + momentum de coste mejor76%25

ΔGM = β·Δlog(pata) + ε con β y φ(AR1 de ε) reestimados walk-forward solo con trimestres ya publicados; el residuo agrupa coste unitario, mix y volumen

Realized vs spot (¿cuánto mercado llega al P&L?)

avg_selling_price_usd_ton (MD&A verificado) vs steel_ppi — el cuello de botella que ALTO identificó en el hedging/mapeo realizado

Corr. niveles
0.71
Corr. Δ trimestral
0.24
β captura Δ%spot→Δ%real
0.44
n pares
18

Backtest de eventos (señal → precio)

Long/short según la señal sectorial pre-filing, sin costes. El pooled de la cadena NO es significativo (t=1.5 a 20d) — igual que ALTO: la señal predice márgenes, no retornos.

1d tras filing
+25 bps
hit 51% · n=37
5d tras filing
-24 bps
hit 51% · n=37
20d tras filing
+173 bps
hit 57% · n=37

Riesgos declarados (Item 1A)

36 factores del 10-K de 2025-10-16, verbatim del documento. 1 son nuevos frente al de 2024-10-17.

operacional 25coste insumos 9financiero 9regulatorio 6precio commodity 5geopolitico 5demanda competencia 3laboral 2clima agua 2ciberseguridad 1
  • Scrap and other inputs for our business are subject to significant price fluctuations and limited availability, which may adversely affect our business, results of operations and financial condition.
  • We rely on the availability of large amounts of electricity and natural gas. Disruptions in delivery or substantial increases in energy costs, including crude oil prices, could adversely affect our business, results of operations and financial condition.
  • We may encounter labor disputes and shortages for skilled labor and/or qualified employees in operational positions, which could adversely impact our operations.
  • The loss of, or inability to hire, key employees may adversely affect our ability to successfully manage our operations and meet our strategic objectives.
  • Our business, financial condition and results of operations may be adversely impacted by the effects of inflation.
  • We may have difficulty competing with companies that have a lower cost structure or access to greater financial resources.
  • Operating and startup risks, as well as market risks associated with the commissioning of our micro mills, could prevent us from realizing anticipated benefits and could result in a loss of all or a substantial part of our investments.
  • Our mills require continual capital investments that we may not be able to sustain.
  • Unexpected equipment failures may lead to production curtailments or shutdowns, which may adversely affect our business, results of operations and financial condition.
  • We are vulnerable to the economic conditions in the regions in which our operations are concentrated.
  • Information technology interruptions and breaches in data security could adversely impact our business, results of operations and financial condition.
  • Increasing attention to ESG matters, including any targets or other ESG, environmental justice or regulatory initiatives, could result in additional costs or risks or adverse impacts on our business.
  • We are subject to litigation, potential liability claims and contract disputes, and may become subject to additional litigation, claims and disputes in the future, any of which could adversely affect our business, results of operations and financial condition.
  • Potential limitations on our ability to access credit, or the ability of our customers and suppliers to access credit, may adversely affect our business, results of operations and financial condition
  • Geopolitical conditions, including political turmoil and volatility, regional conflicts, terrorism and war have caused disruptions in the global economy, energy supplies and raw materials, which may continue to negatively impact our business and operations.
  • The potential impact of our customers' non-compliance with existing commercial contracts and commitments, due to insolvency or for any other reason, may adversely affect our business, results of operations and financial condition.
  • The agreements governing our notes and our other debt contain financial covenants and impose restrictions on our business.
  • We may not be able to successfully identify, consummate or integrate acquisitions, and acquisitions may adversely affect our financial leverage.
  • Goodwill or other indefinite-lived intangible asset impairment charges in the future could have a material adverse effect on our business, results of operations and financial condition.
  • Impairment of long-lived assets in the future could have a material adverse effect on our business, results of operations and financial condition.
  • Competition from other materials may have a material adverse effect on our business, results of operations and financial condition.
  • Our operations present significant risk of injury or death.
  • Our business, financial condition, results of operations, cash flows, liquidity and stock price may be adversely affected by global public health epidemics.
  • Fluctuations in the value of the U.S. dollar relative to other currencies may adversely affect our business, results of operations and financial condition.
  • Operating internationally carries risks and uncertainties which could adversely affect our business, results of operations and financial condition.

11 más en risk_factors.json

encabezados en negrita/cursiva del HTML que aparecen dentro del Item 1A y van seguidos de ≥300 caracteres de cuerpo (así se descartan los encabezados de grupo); categorías por mapa fijo de palabras clave; 'nuevo' = ausente del 10-K anterior. Sin LLM. Caveat: algún encabezado de grupo puede sobrevivir si su primer subtítulo no venía resaltado en el HTML. · accession 0000022444-25-000138

Profundización pendiente (vs cockpit de ALTO)

Gap bridge driver a driver: sin datos
Requiere un modelo de drivers propio de la empresa, como el que ALTO tiene con el crush del etanol.
se necesita: modelo operativo por empresa (volumen × precio × coste unitario)