Intercommodity spreads.

An intercommodity spread is a position composed of legs in two different contracts that share a structural economic relationship. The trader is long one commodity and short another related commodity. The structural relationship is what makes the spread coherent: a crude oil long paired with a gasoline short captures the refining economics, but a crude oil long paired with a silver short would capture nothing meaningful because the two contracts have no structural relationship.

The intercommodity spread differs from the calendar spread covered in Module 07. The calendar spread has two legs in the same contract at different delivery months. The intercommodity spread has two legs in different contracts, often at the same delivery month. The calendar spread captures curve dynamics within a single market. The intercommodity spread captures relative-value dynamics between two markets that share a structural relationship.

The structural relationship is the key.

The reason intercommodity spreads work as a structure is that the two underlying commodities are economically linked. The link can be direct (crude oil is the input to refined gasoline and heating oil) or indirect (gold and silver are both precious metals with overlapping but distinct demand drivers). Either way, the prices of the two commodities tend to move together in response to common factors and to diverge in response to commodity-specific factors. The spread isolates the divergence.

The institutional reading is that the spread expresses a view about which commodity will outperform relative to the other, without expressing a view about the absolute direction of either commodity. A trader who is long gold and short silver in the right ratio profits when gold outperforms silver, regardless of whether both metals rise, both fall, or one rises while the other stays flat. The view is about the relationship, not about the absolute level.

The three categories of intercommodity spreads.

The institutional intercommodity spread universe falls into three operational categories that this module covers:

• Product-and-input spreads. The crack spread (crude oil and refined products) and historically the crush spread (soybeans and processed products). These spreads have a direct industrial logic: one commodity is the raw input and the other is the processed output.
• Ratio spreads within a complex. Gold-silver, copper-gold, platinum-gold. The two commodities share a market category (precious metals, industrial metals) but have distinct drivers. The ratio is a relative-value indicator.
• Substitution spreads. Crude oil versus natural gas, heating oil versus RBOB gasoline. The two commodities can substitute for each other in some uses. The spread captures the substitution dynamic.

The crush spread mentioned briefly.

The Academy notes that the crush spread, while not in the working contract set, is the canonical agricultural intercommodity spread and deserves brief mention for historical and institutional reasons. The crush spread is long soybeans and short the soybean processed products (soybean oil and soybean meal). The position captures the processing margin: the difference between the price of the raw soybean input and the value of the processed outputs. Soybean processors use the spread to hedge their margins. Speculators use it to express views about processing capacity, demand for vegetable oil, and the protein content of animal feed markets.

The crush is not covered further in this module because the Academy's curriculum focuses on the metals, energy, and equity index complexes. The disciplined operator who pursues agricultural trading later in the operator's career can apply the institutional reading of intercommodity spreads developed in this module to the crush and other agricultural spreads. The structural logic is identical even though the specific commodities differ.

Why retail traders rarely use intercommodity spreads.

Most retail traders never engage with intercommodity spreads. The structures require knowledge of two contracts rather than one, and they require attention to the contract-size mismatch that often exists between related commodities. A trader who is comfortable with outright positions in crude oil may not be comfortable scaling that position against a gasoline position, simply because the contract sizes and tick values are different.

The disciplined operator who learns the intercommodity structures gains access to views that retail traders cannot express. A view that refining margins will compress because of weak gasoline demand cannot be expressed cleanly through outrights. The crack spread expresses it directly. A view that industrial metal demand will weaken faster than precious metal demand cannot be expressed through outrights. The copper-gold ratio expresses it. The institutional vocabulary is richer than the retail vocabulary because the institutional trader has learned the spread structures that capture the richer set of views.

The bridge from foundation to complex arc.

Modules 06, 07, and 08 together build the structural literacy that the disciplined operator will deploy across the Complex Arc that begins with Module 10. Without the structural literacy, the operator entering the energy complex would have only outright positions available. With the literacy, the same operator can express energy views through outright crude, through crude-versus-natural-gas spreads, through crack spreads, and through RBOB-HO seasonal spreads. The framework richness compounds.

The same dynamic applies to metals (gold-silver, copper-gold, and the platinum ratio) and to equity indexes (calendar spreads across delivery months). Module 09 closes the structures arc with the micro contract selection, after which the Complex Arc applies the structures vocabulary to each specific complex. The Academy curriculum is built so that each module compounds the operator's working capability rather than just adding isolated facts.

The crack spread is the most institutional of the intercommodity spreads. The structure was developed by oil refiners to hedge their refining margins and has been adopted by speculative traders to express views about the refining sector. Understanding the crack spread requires understanding the underlying refining economics.

The refining economics.

A petroleum refinery takes crude oil as input and produces refined products as output. The primary outputs are gasoline (RBOB) and distillate fuel oil (heating oil and diesel). A simplified picture: one barrel of crude oil produces roughly half a barrel of gasoline and a smaller fraction of distillate, with the remaining production going to other refined products. The refiner pays for the crude input and sells the refined outputs. The difference between the input cost and the output value is the refining margin, called the crack spread.

The conventional crack spread, called the 3:2:1 crack, reflects the typical output mix: three barrels of crude oil produce two barrels of gasoline and one barrel of heating oil. The spread is constructed as long three crude oil contracts and short two gasoline contracts and one heating oil contract. The position captures the refining margin: it profits when refined products appreciate relative to crude and loses when they depreciate.

The contract specifications.

The three contracts in the 3:2:1 crack have different specifications that the trader must understand. CL (crude oil) is 1,000 barrels per contract and quoted in dollars per barrel. RBOB gasoline is 42,000 gallons per contract (one barrel of gasoline equals 42 gallons) and quoted in dollars per gallon. HO (heating oil and ultra-low sulfur diesel) is 42,000 gallons per contract and quoted in dollars per gallon. The trader must convert between the per-barrel crude quote and the per-gallon refined product quotes to compute the spread value.

One CL contract represents 1,000 barrels. One RBOB or HO contract represents 1,000 barrels (42,000 gallons divided by 42 gallons per barrel). So the contract sizes are aligned at the barrel level. A 3:2:1 crack is three CL contracts representing 3,000 barrels of crude, two RBOB contracts representing 2,000 barrels of gasoline, and one HO contract representing 1,000 barrels of heating oil. The barrel ratio works out cleanly.

A worked crack spread example.

What drives the crack spread.

The crack spread responds to four primary drivers. First, refined product demand: strong driving season demand widens the crack; weak demand narrows it. Second, refining capacity utilization: when refineries are running near full capacity, refined products can run scarce relative to crude, widening the crack. Third, seasonal patterns: gasoline demand peaks in summer driving season; heating oil demand peaks in winter heating season. Fourth, unexpected refinery outages: hurricanes, fires, or maintenance issues can take refining capacity offline, widening the crack as refined products become temporarily scarce.

The disciplined operator who tracks the crack spread daily develops an institutional read on the refining sector. The spread is a real-time indicator of refining margins that complements equity analysts' periodic earnings updates on refining companies. A trader who has been long the crack into a hurricane season and exits as the season ends has captured a structural pattern that has been documented for decades.

The crack spread as a listed market.

The CME lists crack spreads as their own instruments, including the 3:2:1 crack and several simpler variants (the 1:1 gasoline crack and the 1:1 heating oil crack). The listed crack spreads have their own bid-ask, their own order books, and exchange-supported execution. The disciplined operator who trades the crack uses the listed instrument rather than legging the three contracts separately.

The simpler 1:1 cracks are useful entry points for traders new to intercommodity spreads. A 1:1 gasoline crack is long one CL and short one RBOB. The position captures the gasoline-only refining margin rather than the blended 3:2:1 margin. The trader can develop institutional reading on the simpler structure before moving to the full 3:2:1.

Historical extremes of the crack spread.

The crack spread has traded in a wide range historically. During normal conditions, the 3:2:1 crack typically sits between $15 and $30 per barrel. During refining stress (hurricane damage, multiple refinery outages, surging demand), the spread can spike above $40 and occasionally above $50. During refining glut conditions (over-built capacity, weak demand, refined product oversupply), the spread can compress below $10. The disciplined operator who tracks these extremes builds the framework reference for current readings.

Hurricane Katrina in 2005 produced one of the most dramatic crack spread spikes in modern history. The destruction of Gulf Coast refining capacity caused refined product prices to spike materially while crude prices were less affected. The crack spread widened to historic highs over a period of weeks. Traders positioned ahead of the storm based on the framework reading of vulnerable infrastructure captured material returns. Traders who were short the crack going into the storm were severely damaged.

The 2020 COVID demand collapse produced the opposite pattern. Refined product demand fell sharply as transportation and economic activity collapsed. Crude prices fell, but refined product prices fell faster. The crack spread compressed materially. The disciplined operator who had a structural read on the demand collapse and positioned short the crack captured the move.

The 5:3:2 crack variant.

Beyond the 3:2:1 crack, some traders use a 5:3:2 ratio that more closely matches the actual refining yield of a typical refinery (slightly more gasoline output relative to crude input). The 5:3:2 is five CL contracts long, three RBOB short, and two HO short. The economics are similar to the 3:2:1 but the specific ratio matches some refiners' operations more precisely. The disciplined operator who is hedging actual refining operations uses the ratio that matches the specific facility's yield. The speculative trader typically uses the 3:2:1 as the standard institutional structure.

Refinery utilization as a framework input.

The EIA publishes weekly refinery utilization data as part of the petroleum status report. The data shows the percentage of refining capacity that is actively operating. When utilization is near 95% (close to the practical maximum), refineries are running at full capacity and refined products can become scarce relative to crude, widening the crack. When utilization falls toward 80% or lower (typically during maintenance season or recession), refined products become abundant relative to crude, compressing the crack.

The disciplined operator who tracks the weekly utilization data has a framework input that informs the crack spread position. Combined with seasonal patterns, demand expectations, and known maintenance schedules, the utilization data produces a coherent framework for spread direction.

The metals complex contains two intercommodity spreads worth institutional attention: the gold-silver ratio and the copper-gold ratio. Each captures a different aspect of the macro regime and provides framework signals that disciplined operators read systematically.

The gold-silver ratio.

The gold-silver ratio is the price of gold divided by the price of silver. Historically, the ratio has traded in a wide range, with extremes around 30 and 100. The long-term geological abundance ratio is approximately 17 (the earth's crust contains approximately 17 times more silver than gold), but the modern monetary ratio has averaged closer to 60 over the past several decades. The ratio's deviation from historical norms is interpreted as a relative-value signal.

A gold-silver ratio above 80 historically suggests silver is cheap relative to gold. Some traders interpret this as a buying opportunity for silver relative to gold. A gold-silver ratio below 40 suggests silver is expensive relative to gold and is sometimes interpreted as a selling signal for silver relative to gold. The disciplined operator does not trade the ratio mechanically based on these thresholds; the framework requires additional analysis of the specific drivers in the current regime. But the ratio is a useful framework input.

What the ratio signals.

The gold-silver ratio reflects two structural factors. First, silver has substantial industrial demand (electronics, solar panels, photographic film historically) while gold is dominantly a monetary metal. When industrial demand is strong, silver outperforms gold and the ratio falls. When industrial demand weakens, gold outperforms silver and the ratio rises. Second, silver is a smaller market than gold and tends to move more volatilely. The ratio therefore expands during gold rallies (silver lags) and contracts during silver rallies (silver leads).

The institutional reading is that the ratio tracks the relative balance between monetary and industrial demand for precious metals. A rising ratio suggests monetary demand dominating (gold preferred over silver because of its purer monetary role). A falling ratio suggests industrial demand dominating (silver preferred because of its industrial component). The trader who has formed a view on which demand source will dominate can express it through the ratio.

Trading the gold-silver ratio.

Trading the ratio requires a contract-size adjustment. One GC gold contract is 100 troy ounces. One SI silver contract is 5,000 troy ounces. The notional values are very different: GC at $2,000/oz is $200,000 of gold, SI at $25/oz is $125,000 of silver. A ratio trade does not pair one GC against one SI directly; it pairs them by notional value to express the ratio view cleanly.

A notional-neutral ratio position might be long one GC and short approximately 1.6 SI contracts ($200,000 of gold and approximately $200,000 of silver in notional). Since SI is sized in 5,000-ounce contracts that cannot be fractionally traded, the trader typically rounds to two SI contracts (slightly over-hedged on the silver side) or uses the micro silver contract (SIL) if available for finer sizing.

The copper-gold ratio.

The copper-gold ratio is the price of copper divided by the price of gold. The ratio is widely watched by macro traders as an indicator of the global economic cycle. Copper is dominantly industrial (used in construction, electrical wiring, electronics manufacturing). Gold is dominantly monetary. When the ratio rises, industrial demand is outpacing monetary demand, suggesting economic expansion. When the ratio falls, monetary demand is outpacing industrial, suggesting economic contraction.

The institutional macro framework uses the copper-gold ratio as a leading indicator for interest rate trends. A rising copper-gold ratio historically correlates with rising real interest rates (economic growth pulling rates higher). A falling copper-gold ratio historically correlates with falling real rates (economic contraction pulling rates lower). The disciplined operator who is forming a view on rates can use the copper-gold ratio as a framework input.

The metals ratios as framework inputs.

The disciplined trader does not necessarily trade the metals ratios directly. The ratios are also valuable as framework inputs to other positions. A trader who has a long copper outright position based on a thesis of industrial demand recovery can check the copper-gold ratio. If the ratio is moving with the thesis (copper outperforming gold), the thesis is confirmed. If the ratio is diverging (copper falling relative to gold), the thesis may be incorrect or the move may be driven by factors other than industrial demand.

The institutional reading is that the ratios contain information beyond what either metal contains alone. The disciplined operator who tracks the ratios daily develops an institutional read on the macro regime that retail traders relying only on outright price action do not have.

The platinum-gold ratio.

The platinum-gold ratio is a third metals ratio worth institutional attention. Platinum (PL) is dominantly industrial (automotive catalytic converters, jewelry, industrial catalysts) with smaller monetary demand. Historically, platinum traded at a premium to gold for most of the 20th century, reflecting its industrial value and relative scarcity. Starting around 2015, the ratio inverted: gold traded above platinum, and the inversion has persisted.

The structural drivers of the platinum-gold inversion include declining demand for diesel vehicles (where platinum is more heavily used than in gasoline catalytic converters), the rise of palladium as a substitute in some applications, and the increased monetary demand for gold during the post-2008 monetary expansion. The ratio's historical normalcy of platinum-above-gold has not returned in the modern regime.

For traders, the platinum-gold ratio is more of an analytical input than a commonly-traded structure. The PL futures market is thinner than GC, and constructing notional-balanced ratio positions can be operationally difficult. Most disciplined operators read the ratio without taking direct positions in it, using it instead as a framework input to other metals positions.

Historical extremes of the gold-silver ratio.

The gold-silver ratio has reached several historical extremes worth noting. In 1980, during the silver corner attempt by the Hunt brothers, the ratio briefly fell below 20 as silver spiked. In 1991, during a period of weak industrial demand and depressed silver prices, the ratio approached 100. In 2020, during the COVID stress, the ratio briefly exceeded 120 before silver rallied sharply to bring the ratio back below 80.

Each historical extreme had specific drivers that the disciplined operator can study. The current regime's drivers may resemble historical patterns or may reflect new structural factors. The trader who uses the ratio as a framework input does not trade extremes mechanically; the framework requires understanding the current-regime drivers.

The metals ratios and the macro regime.

The combined reading of the metals ratios provides a useful summary of the macro regime. A regime of rising copper-gold ratio plus falling gold-silver ratio suggests strong industrial growth (copper outperforming gold, silver's industrial component outperforming gold's monetary component). A regime of falling copper-gold plus rising gold-silver suggests economic contraction (industrial demand weak, monetary demand strong).

The disciplined operator who tracks both ratios alongside the outright prices builds a multi-dimensional read on the macro regime. Combined with the curve readings from Module 04 and the calendar spread readings from Module 07, the operator has a rich framework that retail traders looking only at price action cannot match.

The energy complex contains two important intercommodity spreads beyond the crack: the crude-natural-gas spread and the RBOB-heating-oil spread. Each captures a different relative-value view within the energy sector.

The crude-natural-gas spread.

The crude-natural-gas spread is long crude oil (CL) and short natural gas (NG), or the reverse. The two commodities are both energy sources but serve different demand bases. Crude is dominantly transportation fuel (after refining). Natural gas is dominantly electrical generation and industrial process fuel. The relative pricing of the two reflects substitution possibilities and the relative growth of their primary demand drivers.

The historical relationship between crude and natural gas has shifted materially over the past two decades. Prior to 2010, the two prices tracked relatively closely on a BTU-equivalent basis (the energy content per unit). The shale gas revolution of the 2010s caused natural gas prices to fall materially relative to crude on a BTU basis, creating a structural divergence that has persisted. The institutional reading is that the BTU-equivalent ratio is no longer the right framework; the modern framework uses the relative growth rates of each sector's demand drivers.

Trading the crude-natural-gas spread requires contract-size attention. One CL contract is 1,000 barrels at $74/barrel for $74,000 notional. One NG contract is 10,000 MMBtu at $3.50/MMBtu for $35,000 notional. A notional-neutral position pairs roughly one CL with two NG, but the trader should also consider the BTU equivalence: one barrel of crude contains approximately 5.8 MMBtu of energy, so one CL represents 5,800 MMBtu of crude energy and one NG represents 10,000 MMBtu of natural gas energy.

What the crude-gas spread signals.

The crude-gas spread responds to several distinct drivers. First, the transportation-demand cycle (peaking in summer driving season) supports crude relative to gas. Second, the electrical-generation-demand cycle (peaking in summer cooling and winter heating) supports gas relative to crude. Third, structural production shifts (new shale plays, OPEC supply decisions, LNG export capacity) shift the long-term relationship. Fourth, geopolitical events affecting one commodity disproportionately can produce sharp spread moves.

The disciplined operator who tracks the spread daily notices when it deviates materially from its recent range. The deviations often anticipate larger moves in one or both commodities. The spread is therefore a framework input even for traders who do not directly trade it.

The RBOB-heating-oil spread.

The RBOB-heating-oil spread is long gasoline and short heating oil, or the reverse. Both are refined products derived from crude oil. The two products have distinct demand bases: gasoline is transportation fuel peaking in summer, heating oil is space heating and diesel fuel peaking in winter. The relative pricing reflects the seasonal balance and the refining mix.

Refiners can adjust their output mix to favor gasoline or heating oil within a limited range, depending on the relative prices. When gasoline prices rise relative to heating oil, refiners shift toward more gasoline production. When heating oil prices rise relative to gasoline, refiners shift the other direction. The spread captures the relative scarcity of each product and the refining response.

The seasonal pattern of the RBOB-HO spread.

The RBOB-HO spread has a strong seasonal pattern that disciplined operators have traded for decades. Heading into summer driving season, gasoline demand strengthens and RBOB rallies relative to HO. Heading into winter heating season, distillate demand strengthens and HO rallies relative to RBOB. The transitions between seasons produce predictable shifts in the spread.

A trader who is long RBOB and short HO entering the spring driving season captures the seasonal pattern. The trader who reverses to long HO and short RBOB entering the autumn heating season captures the opposite seasonal pattern. The Academy notes that this seasonal trade is well-documented and the easy entry points are heavily arbitraged. The framework discipline is to look for less-known patterns or to use the seasonal pattern as a framework input rather than a standalone trade.

Natural gas seasonal patterns.

Natural gas has its own seasonal pattern that informs both calendar and intercommodity spread positioning. The winter heating demand cycle dominates natural gas pricing. Storage levels build during summer (when production exceeds demand) and draw during winter (when demand exceeds production). The price differential between summer and winter contracts reflects the cost of storing gas across the seasons.

For intercommodity purposes, the natural gas seasonal interacts with crude oil pricing through several channels. First, natural gas can substitute for distillate fuel oil in some industrial uses, creating a HO-NG relationship during heating season. Second, natural gas liquids (a byproduct of natural gas production) affect refined product pricing. Third, the relative cost of natural gas versus refined products affects industrial fuel choices.

The disciplined operator who tracks the energy complex as a whole notices these cross-relationships. A view about natural gas pricing has implications for refined product pricing that the operator can incorporate into the framework. The retail trader who treats each commodity in isolation misses these structural connections.

The shoulder seasons and intercommodity spreads.

The shoulder seasons (the transitions between summer and winter, typically March through May and September through November) produce some of the most active intercommodity spread movements. The RBOB-HO spread, the crack spread, and the natural gas calendar spreads all shift during these transition periods as demand bases rotate from one season to the next.

The disciplined operator who is preparing for a shoulder-season position reviews the framework reading in the weeks leading up to the transition. The current curve, the inventory levels, the weather forecasts, and the structural factors all inform whether the seasonal transition is expected to follow the historical pattern or to deviate. A standard transition supports trading the historical seasonal pattern. A non-standard transition (unusually warm winter, unexpected refinery maintenance, a geopolitical disruption) may produce different outcomes from the historical pattern.

The execution of intercommodity spreads is more complex than calendar spreads because the two legs are in different contracts with potentially different specifications. The disciplined trader who understands these complexities executes spreads cleanly. The trader who does not pays unnecessary friction costs.

Contract-size mismatch.

Many intercommodity spreads pair contracts with different sizes. The crack spread pairs CL (1,000 barrels) with RBOB and HO (42,000 gallons, also 1,000 barrels equivalent). The barrel ratio is aligned, but the per-tick values are different because RBOB and HO are quoted in dollars per gallon while CL is quoted in dollars per barrel. A trader who has not internalized the per-tick calculation can size positions incorrectly.

The gold-silver ratio pairs GC (100 oz) with SI (5,000 oz). The notional values differ substantially. The trader who pairs one GC with one SI has a contract-count-balanced position but a materially notional-unbalanced position. The disciplined operator sizes by notional or by a documented ratio framework, not by contract count alone.

Listed exchange-traded intercommodity spreads.

The CME lists several intercommodity spreads as their own instruments. The 3:2:1 crack is listed. The 1:1 crack variants are listed. Selected metals spreads are listed. Listed intercommodity spreads provide the same execution benefits as listed calendar spreads: single-order execution, narrower bid-ask than the sum of leg bid-asks, and guaranteed leg ratios.

For intercommodity spreads not listed as their own instruments, the trader must leg the position by entering the two legs separately. This is acceptable for intercommodity spreads (more so than for calendar spreads) because the listed spread markets are less universally available. The trader who legs an intercommodity spread should do so during liquid trading hours, with attention to the relative-leg pricing, and ideally using limit orders on both legs at framework-identified prices.

SPAN margin treatment for intercommodity spreads.

SPAN provides favorable margin treatment for intercommodity spreads when the two contracts have a documented correlation relationship recognized by the clearing house. The crack spread receives meaningful margin offset because of the structural relationship between crude and refined products. The gold-silver and copper-gold ratios receive smaller offsets because the correlation is less direct. The crude-natural-gas spread receives little to no offset because the two contracts have weaker documented correlation in recent regimes.

The trader should check the broker's reported SPAN margin on the actual spread structure rather than assuming favorable treatment. A spread that the trader expects to be margined as a unit may be margined as two outright positions if the clearing house does not recognize the specific pairing. The capital efficiency expected may not materialize, and the position sizing should reflect the actual margin requirement.

Working the spread P/L.

The P/L on an intercommodity spread requires careful tracking because the two legs have different per-tick values. A move of one cent in RBOB is $4.20 per contract (one cent × 42,000 gallons / 100 cents per dollar). A move of one cent in CL is $10 per contract. A trader who is short two RBOB and long three CL must track the per-leg P/L correctly to know the spread P/L.

The disciplined operator uses spreadsheet tracking or platform-supported spread P/L displays rather than manual leg-by-leg calculation. The errors that accumulate from manual tracking compound over time and can produce material discrepancies between the operator's perceived P/L and the actual P/L. The institutional discipline is to verify the spread P/L through the broker's reported figures and to reconcile any discrepancies promptly.

Stops on intercommodity spreads.

Stops on intercommodity spreads should be set on the spread price itself, not on either leg. A stop "close if RBOB falls to $2.00" is wrong for a long-RBOB short-HO spread: if HO falls $0.30 simultaneously with the RBOB move, the spread is unchanged but the stop on RBOB alone would close the position incorrectly. The correct stop is "close if the spread falls to a defined threshold," which captures the structural view the spread is expressing.

Some platforms support spread stops directly. Others require the trader to monitor the spread and manually close both legs when the threshold is reached. The disciplined operator uses platform-supported spread stops when available and monitors manually when not. The discipline of stop-on-spread is the same institutional practice covered for calendar spreads in Module 07.

Building the spread monitoring infrastructure.

A trader who runs multiple intercommodity spread positions simultaneously needs monitoring infrastructure that tracks each spread's price, the change from previous close, the position P/L, and the framework status. Manual tracking through individual leg prices does not scale beyond two or three positions. The disciplined operator either uses platform-provided spread tools (when available) or builds a spreadsheet that pulls leg prices and computes spread metrics automatically.

The institutional desk typically has dedicated software that displays all active spreads in a single view, with framework alerts when spread prices reach defined thresholds. The retail trader who is building toward institutional discipline can replicate much of this functionality through a well-structured spreadsheet with automated price feeds. The Academy notes that several broker platforms now offer spread-specific monitoring views as part of their standard software.

Position-level versus portfolio-level risk for spread books.

A book of multiple intercommodity spreads requires risk monitoring at both the individual position level and the portfolio level. Individual position risk is the per-spread stop and target framework that has been covered throughout this module. Portfolio risk emerges when multiple spreads have correlated exposures: a book that is short two crack spreads, short the gold-silver ratio, and short the RBOB-HO spread might have aggregate risk-off exposure that the trader has not consciously sized.

The disciplined operator reviews the spread book daily, asking what the aggregate exposure represents. If the spreads are diversified across uncorrelated views, the aggregate risk is well-distributed. If the spreads cluster around a single macro view, the aggregate exposure may be larger than intended. Module 15 covers portfolio-level risk policy in detail. The point in Module 08 is that the disciplined operator should begin tracking aggregate spread exposure as soon as multiple spread positions are active.

The intercommodity spread is the right structure for relative-value views across commodities that share a structural relationship. The structure is the wrong choice for views that are not naturally relative-value. This section catalogs the decision framework.

When intercommodity is right.

The intercommodity spread is the appropriate structure in four operational situations. First, when the trader's view is specifically about the relationship between two commodities. A view that "refining margins will compress because gasoline demand is weak" is naturally a crack spread short. A view that "industrial metal demand will weaken faster than precious metal demand" is naturally a copper-gold ratio short.

Second, when the trader wants to express a sector view while reducing macro directional exposure. A trader who is bearish on energy generally but uncertain about timing might prefer a crack spread short (which captures the refining-specific deterioration) over a CL outright short (which captures the broader directional move plus the refining deterioration plus other factors).

Third, when the trader wants to express a seasonal pattern. The RBOB-HO seasonal trade and the natural gas calendar seasonals (covered in Module 07 as calendar spreads but also relevant as intercommodity context) are classic seasonal structures. The disciplined trader uses the documented historical pattern as one input, combined with current-conditions analysis, to size the position.

Fourth, when the capital efficiency of the spread matters relative to outright positions. SPAN-favored intercommodity spreads use materially less capital than the equivalent outright positions. For traders who are running multiple positions simultaneously, the capital efficiency may be the binding constraint that determines whether the trade is sized to material P/L.

When intercommodity is wrong.

The intercommodity spread is the wrong structure in four operational situations. First, when the trader's view is purely about one commodity. A view that "crude will rally because of OPEC supply cuts" is a CL outright long, not a spread. The spread would dilute the directional view by adding the offsetting position in a related commodity.

Second, when the two contracts in the proposed spread do not have a real structural relationship. A trader who pairs ES and CL because both "feel correlated" is constructing a spread without structural foundation. The position is two outrights, not a spread. The SPAN margin treatment will reflect this: no offset will be granted, and the capital efficiency disappears.

Third, when the spread is illiquid. Some intercommodity spreads exist only as theoretical constructs without listed markets and without meaningful institutional flow. A trader who attempts to trade these spreads faces execution challenges that erode any framework edge. The disciplined operator trades only spreads with adequate liquidity.

Fourth, when the holding period is too short for the spread structure to work. Intercommodity spreads typically move more slowly than outrights because both legs absorb most macro moves. A trader who needs material P/L within hours or a day finds the spread too slow. The outright captures the move more directly.

Choosing among the intercommodity structures.

When an intercommodity spread is appropriate, the disciplined trader chooses the specific structure based on the view's economic content. A view about refining margins is the crack spread. A view about industrial-versus-monetary demand is the copper-gold ratio. A view about gasoline-versus-distillate demand is the RBOB-HO spread. A view about precious metal categories is the gold-silver ratio. Each spread captures a specific economic relationship, and the choice depends on which relationship the framework is articulating.

This is one of the operational benefits of having the multiple structures in the working vocabulary. The trader who knows only the crack spread expresses every refining-related view through that single structure even when other structures might better capture nuanced views. The trader who knows all the major intercommodity structures can match the structure to the specific economic content of the view.

The intercommodity spread in the trader's complete position book.

The disciplined trader's position book typically contains a small number of intercommodity spreads (perhaps two to five at any time) representing specific relative-value views. These positions complement the outright positions (from Module 06) and the calendar spreads (from Module 07) to produce a mixed-structure book. The mix reflects the trader's full set of current views, expressed in the structures that best capture each view.

Most retail traders never use intercommodity spreads. This is the structural gap the Academy is built to close. The disciplined operator who completes the Structures Arc has the working vocabulary to express the full range of institutional views. The retail trader operating only with outrights is permanently constrained to a subset of views, regardless of how skilled the directional reading becomes.

The Commitments of Traders report as input.

The CFTC publishes the weekly Commitments of Traders report, which discloses the positioning of different categories of market participants in each major futures contract. The report is published Friday afternoon for positions held as of the prior Tuesday. The data is publicly available and is one of the institutional inputs for spread positioning decisions.

For intercommodity spreads, the COT data is most useful when read across multiple contracts simultaneously. A trader who is considering a long crack spread can read the COT positioning in crude oil, RBOB, and HO to see whether commercial participants (refiners hedging margins) are net long the crack or net short. Disciplined operators frequently align with commercial positioning when the framework supports it and avoid positioning sharply against commercials when the framework is uncertain. Module 13 covers the full COT framework as part of the systems work; the point in Module 08 is that the positioning data is one of the institutional inputs that distinguishes the framework-driven trader from the chart-only trader.

Position sizing for intercommodity spreads.

Intercommodity spreads typically require larger absolute position sizes than equivalent outright positions to produce comparable dollar P/L. The reason is structural: the spread captures only the relative move between two legs, which is smaller in magnitude than the absolute move of either leg. A trader who has been sizing outrights at one or two contracts may find that intercommodity spreads need three to five contract pairs (or the equivalent in notional) to produce material P/L.

The capital efficiency of SPAN-favored spreads supports this scaling. A trader who would post $13,000 of margin for an outright position can often run three to five times that notional exposure in spreads for the same capital. The disciplined operator who has understood the capital efficiency from Module 07 applies the same framework to intercommodity spreads in Module 08, sizing positions to capture the framework view at appropriate scale.

The discipline of waiting for the right setup.

Intercommodity spreads are not always available as profitable setups. The framework view may not be clear. The spread may be at a typical level with no edge to either side. The seasonal pattern may already be priced in by the institutional crowd. The disciplined operator who has the spread vocabulary uses it selectively, taking positions only when the framework supports a specific view with conviction.

This is one of the operational benefits of having the structures vocabulary. The trader is not forced to take a position every day. The trader can wait for setups in any of the available structures: outright, calendar spread, intercommodity spread. The setup that emerges first with the strongest framework support is the setup the operator takes. The trader with only outrights is searching for setups in a narrower space and may take inferior setups to remain active. The trader with the full structures vocabulary has a richer setup search and can wait for higher-quality opportunities.

Looking ahead to Module 09.

Module 09 closes the Structures Arc with the micro-versus-standard contract selection. The micro contracts (MES, MNQ, MGC, MCL, and others) are scaled-down versions of the standard contracts. The disciplined operator chooses between micros and standards based on capital, risk policy, and framework specifics. The decision is structural in nature: the same view can be expressed through either contract size with different capital deployment and different per-trade P/L profiles. Module 09 covers the operational framework for this choice.