Seasonality & Supply Shocks: When the Calendar and the Weather Move Prices

Three lessons in, you can read a commodity like a local. You know a futures contract and its basis (lesson 1), you can build the curve from cost of carry — financing plus storage minus convenience yield (lesson 2) — and you know that a passive long quietly bleeds roll yield in contango and earns it in backwardation (lesson 3). That’s the machinery. Now we plug in the thing that actually drives the machinery: the real world.

Here’s what makes commodities weird, and weirdly tradeable. A share of Apple does not care what month it is. It does not heat a home in January or get burned in a tractor in October. Apple’s cash flows do not depend on whether a hurricane hit the Gulf of Mexico last Tuesday. Commodities do. They are physical things, consumed and produced on a rhythm set by the calendar (people heat in winter, drive in summer, harvest in autumn) and disrupted by the weather (droughts, freezes, hurricanes) and by humans behaving like humans (OPEC, wars, embargoes, recessions).

Two forces run this lesson. The first is predictable: seasonality — the part of the price swing you could circle on a calendar a year in advance. The second is the unpredictable: shocks — the part nobody circled, that lands like a brick. And the reason both matter so violently is one brutal property we’ll spend half the lesson on: in the short run, you cannot drill a new well overnight and you cannot stop driving to work overnight. Supply and demand are inelastic, and inelasticity is a multiplier that turns a 5% shortage into a 25% price spike. Let’s go.

Seasonality: prices that follow the calendar

Think about umbrella prices. If a vendor near a monsoon-prone city is smart, umbrellas get a little pricier as the rainy season approaches and demand surges, then drift back down once the skies clear. Nobody is shocked by this — the rain comes every year. That predictability is the point: it’s a repeating annual pattern, knowable in advance. Commodities have umbrella-and-monsoon dynamics all over the place.

Definition. Seasonality is a repeating, calendar-driven pattern in a commodity’s price, caused by predictable annual cycles in demand or supply. It’s the slice of the price’s behavior you could forecast from the month alone — not a guarantee about this year, but a strong tendency averaged over many years.

The three classic seasonal stories, each driven by a different calendar:

• Natural gas — winter demand peak. Gas heats homes. Cold months pull consumption (and price) up; the shoulder seasons of spring and autumn are the soft spots. Utilities inject gas into storage all summer to be ready, then withdraw it all winter.
• Gasoline — summer demand peak. Driving season (vacations, road trips) lifts demand from late spring through summer. On top of that, refiners switch to a costlier, lower-volatility summer blend for environmental reasons, so the product itself gets more expensive to make right as demand climbs.
• Grains (corn, wheat, soybeans) — autumn-harvest supply low. Here it’s supply, not demand, that’s seasonal. The harvest dumps a glut of grain onto the market in autumn, so prices tend to bottom around harvest and run highest in the lean pre-harvest months when last year’s crop is running thin.

Watch the marker sweep around the year below. Toggle each commodity and notice they peak in different months — that’s the whole idea. Seasonality isn’t one shape; it’s a different shape per commodity, set by what that commodity is for.

Let’s put fake-but-honest numbers on the gas story. Suppose a stylized natural gas price averages $3.50/MMBtu over the year, dipping in the warm shoulder months and spiking in deep winter:

The January-to-April gap here is $5.10 − $2.90 = $2.20/MMBtu, a swing of about 63% off the spring low — and you could have predicted the direction of that swing last summer just by looking at a calendar. That predictability is genuinely useful. But — and this is the trap — useful does not mean profitable.

When to use it

Seasonality is best used as context for timing and curve-reading, not as a standalone trade. It tells you why the forward curve is shaped the way it is (why winter gas contracts cost more than summer ones), which months tend to be supply-rich or demand-heavy, and when storage is being filled vs. drained. It informs when you’d rather roll or hedge. What it is not is a free lunch — the moment a pattern is obvious to everyone, it’s in the price.

Inventories: the buffer that smooths (or fails)

Inventory is the savings account of the commodity world. A household with a fat emergency fund barely notices a surprise car repair; a household living paycheck-to-paycheck gets wrecked by the same bill. Commodities are identical. When storage is comfortably full, a cold snap is met by drawing down stock — no big deal, prices barely twitch. When storage is near empty, that same cold snap has nothing to draw on, and the only way to balance the market is for price to explode until demand backs off.

Definition & metric. Inventories (a.k.a. stocks) are the quantity of a commodity sitting in storage — tanks, silos, salt caverns, tank farms. The standard gauge of adequacy is days of supply:

$\text{Days of supply} = \dfrac{\text{Inventory}}{\text{Daily consumption}}$

It answers a blunt question: if production stopped right now, how many days could we keep consuming from what’s in the tank? High days-of-supply = cushioned and calm. Low days-of-supply = exposed and twitchy.

This connects straight back to lesson 2’s convenience yield. Convenience yield is the premium of having the physical good on hand right now. When inventories are low, that premium soars — being one of the few people holding actual barrels is suddenly worth a lot — which lifts the spot price relative to futures and tips the curve into backwardation. So: low inventories → high convenience yield → backwardation → and, as we’ll see, brutal price sensitivity. Three lessons, one chain.

Let’s quantify how inventory governs sensitivity. Same 2-million-unit/day consumption, same surprise 1-day production outage, but at three different storage levels:

Notice the inventory fell from 60M to 4M — a factor of 15 — but the price reaction went from “barely a twitch” to “violent.” That’s the buffer at work: the same physical shock produces wildly different price outcomes depending on how full the savings account is. Low days of supply is the gunpowder; the shock is just the spark.

When to use it

Watch inventory data (the EIA’s weekly natural-gas and crude reports, USDA grain stocks) as a gauge of fragility, not a price prediction. The signal isn’t the absolute number — it’s the number relative to the seasonal norm and how few days of supply it represents. Low and falling days-of-supply tells you the market has lost its shock absorber and any fresh disruption will land hard (and the curve is probably in backwardation, confirming it). High and rising tells you the opposite: cushioned, sleepy, often in contango.

Inelastic supply and demand

Imagine you need exactly one specific medication to live, and the pharmacy raises the price 50%. Do you buy half as much? Of course not — you buy the same amount and grumble. Your demand is inelastic: quantity barely budges no matter what price does. Now imagine you’re a refinery that needs crude today to keep running, or a commuter who has to get to work whether gas is $3 or $5 — same thing. Short-run commodity demand is stubborn. And short-run supply is just as stubborn the other way: you cannot drill, permit, and complete a new oil well this afternoon, and a cornfield produces exactly one harvest a year no matter how high the price climbs.

Definition. Price elasticity measures how much quantity responds to price:

$\varepsilon = \dfrac{\%\,\Delta\,\text{Quantity}}{\%\,\Delta\,\text{Price}}$

If a 10% price rise cuts quantity demanded by only 2%, elasticity is 0.2 — very inelastic (less than 1, quantity barely moves). If quantity moved 15% for that same 10%, elasticity is 1.5 — elastic. Commodities in the short run live deep in inelastic territory: elasticities of 0.1–0.3 are typical. The supply and demand curves are nearly vertical — steep, stubborn walls.

Play with the curves below. Make them steep (inelastic) and shift one — watch the price jump far more than the quantity does. That steepness is the entire reason commodities are so explosive.

Here’s the arithmetic that should haunt you. Rearrange the elasticity formula to solve for the price move a quantity shock forces:

$\%\,\Delta P = \dfrac{\%\,\Delta Q}{\varepsilon}$

Now feed it a modest 5% supply drop at various elasticities:

Read the third row again. A 5% dent in supply produces a 25% price spike when demand elasticity is 0.20 — a 5× multiplier. Cut elasticity to 0.10 and the same shortfall becomes a 50% move. The size of the shock barely changed; the elasticity did all the damage. This single mechanism explains why oil can rocket 40% on a disruption that removes a few percent of world supply.

When to use it

Reach for elasticity thinking whenever you’re sizing the price impact of a quantity event — an OPEC cut of N barrels, a drought knocking out X% of a crop, a refinery outage. The mental move is always: small %ΔQ ÷ small ε = big %ΔP. It also tells you about time horizons: elasticity is low in the short run and rises over time as supply responds (new wells, more acres) and demand adapts (efficiency, substitution). So the violent first move often partly reverses as the world adjusts — which is exactly the cobweb we hit next.

Supply and demand shocks

Seasonality is the part of the swing you saw coming. Shocks are the part you didn’t. A shock is an unexpected jolt to supply or demand, and because of everything we just built — thin buffers, inelastic curves — shocks land hard and fast. Think of a sleeping person (a calm market) who gets a bucket of ice water dumped on them: the reaction is instant and disproportionate to the amount of water, because they weren’t braced for it.

Supply shocks cut the quantity available, usually with little warning:

• Weather/nature: droughts and freezes slash crop yields; hurricanes shut Gulf Coast refineries and offshore platforms; a Texas deep-freeze ices off wellheads.
• Geopolitics: OPEC+ production cuts, wars, sanctions, and embargoes pull barrels (or gas, or wheat) off the world market.
• Accidents/outages: a pipeline rupture, a refinery fire, an export terminal going offline.

Demand shocks move the buyer side, sometimes just as fast:

• Macro: a recession craters industrial demand for oil and metals; a boom (think China’s 2000s growth) does the reverse, lifting everything at once.
• Weather on the demand side: a brutal cold snap spikes heating-fuel demand; a hot summer spikes power-burn for air conditioning.

Because short-run elasticity is so low, both kinds of shock produce big, fast moves. But here’s the redemption arc: high prices eventually cure high prices. A spike is a giant signal flare telling producers “make more!” and buyers “use less!” — and over months and years they obey. New wells get drilled, more acres get planted, consumers economize. Supply catches up, often overshoots, and the price comes crashing back. That boom-bust loop has a name.

The cobweb (a.k.a. hog cycle). Because production takes time, producers set this season’s output based on last season’s high price — then they all overproduce at once, create a glut, and crash the price; the low price then scares off production, creating next year’s shortage and the next spike. High → overproduce → glut → low → underproduce → shortage → high. It spirals like a cobweb on a supply-demand chart, classically observed in hog farming, hence “hog cycle.” It’s why commodities are famously mean-reverting and cyclical rather than trending like stocks.

Putting it together

Step back and the whole lesson is one sentence: commodity prices swing on a predictable calendar (seasonality), get cushioned or exposed by storage (inventories), and explode on surprises (shocks) because short-run supply and demand are inelastic. Seasonality you can circle in advance — but it’s already in the forward curve. Inventories are the savings account that smooths the seasons until they run dry. Inelasticity is the multiplier that turns any quantity shock, seasonal or surprise, into an outsized price move. And the cobweb is why those moves eventually reverse: high prices cure high prices.

Tie it to the earlier lessons and the arc closes. Low inventories raise convenience yield (lesson 2), tip the curve into backwardation (lessons 1–2), and a backwardated curve is the one that pays roll yield to a passive long (lesson 3). The physical drama in this lesson is what sets the curve shape you learned to read in the last three.

Key Takeaways