12. Agriculture
Teaching rewrite of agricultural and soft commodities: grains, oilseeds, palm oil, sugar, coffee, cocoa, and ethanol — plus price drivers, the Commitments of Traders report, the 2010 cocoa squeeze, and OTC hedging structures. Original wording; worked numbers recomputed. Prices are teaching values. Not investment advice.
Introduction
Agriculture splits into two groups:
| Agricultural (grains, oilseeds) | Softs | |
|---|---|---|
| Examples | Wheat, corn, soybeans | Coffee, sugar, cocoa, cotton |
| Where grown | Widely, incl. developed countries | Concentrated in a few, often developing, countries |
| Supply response | Fast — farmers add acreage when prices rise | Slower and prone to local shocks |
Unlike oil or metals, crops are replanted every season (or within a few years for tree crops), so supply responds quickly — but weather can wipe out a harvest at any time.
This lesson covers:
- The balance sheet: supply, demand, ending stocks, stocks-to-use
- Grains and oilseeds: wheat, corn, palm oil, the soybean complex
- Softs: sugar, coffee, cocoa; ethanol
- Price drivers: the “three Fs” (food, feed, fuel), weather and ENSO, policy, investors, emerging markets
- COT reports and the 2010 “Chocfinger” cocoa squeeze
- Exchange contracts and spreads (crush), and OTC structures: swaps, spread options, accumulators, TARNs
12.1 Definitions: the balance sheet
| Term | Meaning |
|---|---|
| Supply | Beginning stocks (carry-in) + production + imports |
| Demand (use) | Domestic use + exports |
| Ending stocks (carry-over / carry-out) | Supply − use, carried into the next year |
| Stocks-to-use ratio | Ending stocks ÷ total use |
A stocks-to-use ratio of roughly 20–40% is “normal”; lower means a tight market and more volatile prices.
The source defines carry-over as “previous year’s stocks + current production + imports” — that is total supply. Carry-over is what is left after use: supply minus demand.
Worked example: a wheat balance sheet (million t)
| Item | Value |
|---|---|
| Beginning stocks | 280 |
| Production | 764 |
| Imports (world: ≈ exports, so net 0) | — |
| Total supply | 1,044 |
| Use | 754 |
| Ending stocks | 290 |
| Stocks-to-use | 290 ÷ 754 ≈ 38.5% |
(2020 production and consumption as quoted; stocks illustrative.) Production and consumption rarely match, so stock changes drive prices.
12.2 Grains and oilseeds
Wheat: the supply chain
flowchart LR
F[Farmers<br/>on-farm silos] --> E[Merchants / elevators<br/>store, clean, blend]
I[Imports] --> E
E --> M[Flour mills]
M --> B[Bakeries, pasta,<br/>food manufacturers]
M --> AF[Mill feeds → animal feed]
B --> R[Retail & restaurants]
R --> C[Consumers]
Merchants consolidate many farms. Global grain trading is dominated by the ABCDs: Archer Daniels Midland, Bunge, Cargill, Louis Dreyfus (with COFCO and others now significant).
US wheat classes (spring/winter = when sown):
| Class | Uses |
|---|---|
| Hard Red Winter | Bread flour, Asian noodles, rolls, flatbreads |
| Hard Red Spring | “Aristocrat” — premium bread, bagels, pizza |
| Soft Red Winter | Cookies, crackers, pastries (the Chicago futures grade) |
| Durum | Pasta, couscous |
| Hard White / Soft White | Bread, noodles / cakes, pastries |
Production 2020: ~764 Mt — EU 26%, China 23%, India 17%, Russia 15%, US 8% (of the largest producers). Consumption: ~754 Mt — EU 21%, China 20%, India 16%, US 5%.
Corn (maize)
Mainly animal feed, plus sweeteners and ethanol — so oil prices matter. 2020 production ~1,111 Mt vs consumption ~1,135 Mt. US ≈ 34% of output, China 24%, Brazil 7%, EU 6%. About 40% of the US crop goes into fuel ethanol.
Palm oil
The world’s major edible oil (competing with soybean and rapeseed oil): ~70% food (cooking oil, margarine, shortening), ~30% industrial (cosmetics, cleaners, candles, biodiesel).
- Grows only within about 10° of the Equator → Indonesia and Malaysia ≈ 85% of output
- Main importers: India, the EU, China
- Commercial variety: Tenera (a Dura × Pisifera hybrid)
- Nursery 12–18 months, first harvest ~30 months after planting, peak yield in years 8–15, life 25–30 years, harvested year-round
- Rule of thumb: about 4 t of oil per hectare
The soybean complex
Sown April–May (as late as July, risking frost). An oilseed, like peanuts, sunflower, and rapeseed.
- Hulls → dairy feed; beans eaten whole or crushed into meal (livestock feed) and oil (food, soap, even explosives)
- Crush volumes are a proxy for demand (imperfect — some beans are eaten or saved as seed)
- Producers: Brazil, US, Argentina; China is the largest crusher (of imported beans)
One 60 lb bushel crushes to about 44 lb meal + 11 lb oil + 5 lb waste.
Worked example: the board crush margin
Meal USD 300 per short ton, oil 30 cents/lb, beans USD 9.00/bushel:
- Meal: 44 lb = 0.022 short ton → 0.022 × 300 = 6.60
- Oil: 11 lb × 0.30 = 3.30
- Crush margin = 6.60 + 3.30 − 9.00 = USD 0.90/bushel
A crusher is long this margin. Buying the crush (long beans, short meal and oil) bets it narrows; a reverse crush bets it widens. Shifts in meal vs oil demand change the margin.
Checkpoint 1: balance sheets and grains
Checkpoint — sections 12.1 and 12.2
1 / 5Beginning stocks 50, production 400, imports 10, use 420. Ending stocks?
Pick an answer to see if you are right.
12.3 Soft commodities
Sugar
- Produced in about 110 countries; ~80% from cane, the rest from beet
- Top producers: India, Brazil, Thailand, China, US, Mexico, Russia, Pakistan, France, Australia (~70%)
- Uses: food, feed, ethanol; consumption ~172 Mt (2018), growth slowing
- ~64 Mt traded; Brazil dominates exports; main importers Indonesia, China, US
The source says beet is grown in the Northern Hemisphere and cane in the Southern. More precisely, cane grows in tropical and subtropical regions (India and Thailand are north of the Equator), and beet in temperate climates (Europe, Russia, the northern US).
Coffee
Bean anatomy (outside in): skin → pulp (compost) → mucilage (jelly) → parchment (mulch, paper) → silver skin → bean (seed).
Where: native to Africa (arabica from Ethiopia); now grown across the “bean belt” between the Tropics. Brazil dominates, then Vietnam, Colombia, Indonesia, Honduras.
| Type | Flavour | Typical use | ICO groups |
|---|---|---|---|
| Arabica | Smoother | Brewed, specialty | Brazilian naturals, Colombian milds, other milds |
| Robusta | More bitter, more caffeine | Instant, espresso blends | Robustas (Vietnam, Indonesia, Ghana…) |
Production process: 3–4 years to first crop, ~25-year life → harvest → wash → dry 1–2 weeks → bag → mature 6–12 months (up to 3 years) → roast → grind → brew. Longer roasts are darker: light ~8 min, city ~12, Italian ~20, French ~24.
- Roasting happens at roughly 190–250 °C (about 375–480 °F), not °F as printed.
- The caffeine figures for cola and black tea are mg, not g: cola ~40 mg, black tea ~45 mg, brewed coffee ~95 mg, espresso shot ~27 mg (by the source’s figures).
- The source gives 2019 production as 168 million bags, “of which the two main types” were 96 million, with arabica 72 million — this is garbled. ICO figures put arabica ≈ 96 million and robusta ≈ 72 million bags.
Forms: green, dried cherry, parchment, roasted, decaf, liquid, soluble (instant).
Statistics: the ICO coffee year starts 1 October; output is counted in 60 kg bags — 168 million bags ≈ 10.1 Mt. Production: South America 46%, Asia & Oceania 30%, Mexico & Central America 13%, Africa 11%. Consumption: Europe 39%, Asia & Oceania 26%, North America 23%.
flowchart LR
S[Smallholders] --> CO[Co-operatives] --> T[Trading houses]
L[Large estates] --> T
T --> R[Roasters<br/>specialist to Starbucks / Kraft]
L --> R
R --> O[Coffee shops, supermarkets,<br/>institutions]
Pricing: commercial deals price off the ICE “C” arabica futures (37,500 lb, US cents/lb) plus a negotiated premium for quality (Starbucks buys high-altitude arabica this way). For delivery, the exchange grades beans (origin, preparation, size, defects, cup quality) and applies fixed origin premiums/discounts — e.g. Colombia at a premium, Brazil at a discount. Robusta trades on ICE London. The ICO publishes a Composite Indicator price.
Cocoa
- Grown within 10° of the Equator; Côte d’Ivoire, Ghana, Indonesia lead; the EU and US consume most
- Consumption is measured by grindings
- Needs lower altitude and more heat than coffee; ~1.5 years to flower, six more months to pods
- Process: ferment beans (up to a week) → dry (1–2 weeks) → roast → crack to nibs → grind to cocoa liquor → press into cocoa butter (chocolate, cosmetics) and presscake (cocoa powder)
- Bean grades: fine/flavour vs bulk/ordinary
| Chocolate | Main ingredients |
|---|---|
| Dark | Cocoa solids, cocoa butter, sugar |
| Milk | Cocoa solids, cocoa butter, sugar, milk |
| White | Cocoa butter, sugar, milk — no cocoa solids |
- Cocoa beans are typically roasted at roughly 120–150 °C for 15–35 minutes; the source’s “five minutes at 50 °C” is far too cool and short.
- The source lists “butter” as the extra ingredient in milk chocolate and “cocoa” in white. Milk chocolate adds milk; white chocolate uses cocoa butter but no cocoa solids.
Cocoa hit record highs above USD 12,000/t in late 2024 after disease, ageing trees, and bad weather cut West African crops; arabica coffee also set records above USD 4/lb in early 2025 on Brazilian drought. The EU’s deforestation regulation (EUDR) adds traceability requirements for cocoa, coffee, palm oil, soy, and others.
12.4 Ethanol
“If you look at the ethanol landscape worldwide, the US and Brazil are like Kuwait and Saudi Arabia.” — FT, 2006
What it is: an alcohol (C₂H₅OH — a hydrocarbon chain with an –OH group). For fuel, the aim is high strength and few impurities.
The source calls ethanol the simplest alcohol. Methanol (CH₃OH) is the simplest; ethanol is the next.
Process (corn): grind kernels to meal → add water and enzymes (starch → sugar) = mash → heat to kill bacteria → cool, add yeast → ferment to ethanol + CO₂ → distil → molecular sieve removes the last water.
Energy output ÷ input: sugarcane 8.3, sugar beet 1.9, corn 1.8 — cane is far more efficient.
| Argument | For | Against |
|---|---|---|
| Carbon | Crop reabsorbs the CO₂ released | Land clearing (Amazon), energy-hungry processing, fertiliser made from fossil hydrogen |
| Supply | Renewable | Huge land needs; competes with food and feed |
| Logistics | Blends into gasoline | Can’t use oil pipelines (absorbs water); needs trucks/rail and new retail infrastructure |
Other biofuels: cellulosic ethanol (waste plant matter), biobutanol (more energy, higher blends), biodiesel from non-food crops, biomass-to-liquids.
Scale: ~49 bn litres (2004) → ~108 bn litres (~24 bn gallons, 2018); US ~56%, Brazil ~28%.
History:
- Brazil: 1970s subsidies after oil shocks (90% of crude was imported) → all-ethanol cars by the 1980s → bust (cane shortages, decontrolled pump prices, dear sugar, poor cars, cheap oil) → flex-fuel cars from 2003, which were 50–75% of new sales by 2006.
- US: mandates, tax credits, and tariffs; demand jumped when MTBE was banned. Blends E10–E15; more needs modified engines.
- Europe: mainly from sugar beet, plus maize, wheat, barley, rye.
Checkpoint 2: softs and ethanol
Checkpoint — sections 12.3 and 12.4
1 / 5Which coffee is typically used for instant coffee?
Pick an answer to see if you are right.
12.5 Price drivers
The three Fs: food, feed, fuel
What links a Brazilian cane farmer, a US corn farmer, Chinese meat demand, and Iowa soybean prices? Crude oil.
flowchart TB
O[Crude oil rises] --> B[Brazil: more cane into ethanol<br/>less sugar]
O --> U[US: more corn into ethanol]
M[China: richer diets → more meat] --> FD[More corn for feed]
U --> CP[Corn prices up]
FD --> CP
CP --> A[Farmers plant more corn]
A --> S[Less land for soybeans → soy prices up]
Physical factors
| Driver | Notes |
|---|---|
| Weather | The key harvest variable; climate change shifts long-term trends |
| ENSO | El Niño / La Niña shift rain and temperature worldwide (below) |
| Physical limits | Land, labour, water, environmental and political limits |
| Transport choke points | Panama Canal, Strait of Malacca, Hormuz, Bosphorus (Black Sea grain) |
| Input costs | Diesel, fertiliser, seed |
| Innovation | Coffee capsules first cut demand (less coffee poured away), then drew in new drinkers; GM crops raise yields (not accepted everywhere); buyers fund smallholders to secure supply |
| Crop switching | “Battle for acreage” as relative prices and biofuel demand change |
| Supply elasticity | Fast for annual crops (one season) vs years for mines |
| Substitution | Roasters add more robusta when arabica is dear |
| Inventories | Carry-over and stocks-to-use |
El Niño and La Niña
In a neutral year, east-to-west trade winds pile warm water toward Indonesia and Australia (rain there), with cold water upwelling off South America.
| El Niño (warm phase) | La Niña (cold phase) | |
|---|---|---|
| Trade winds | Weaker | Stronger |
| East Pacific (off South America) | Warmer | Colder |
| Typical effects | Drought in Indonesia, Australia, northern South America; wetter southeastern South America, East Africa, southern US; fewer Atlantic hurricanes | Roughly the reverse: drier southern US, colder/wetter US Northwest, more Atlantic hurricanes |
| Frequency | Every ~3–5 years; no two alike |
(The source writes “El Niña”; the cold phase is La Niña.) Market read: El Niño drought in Southeast Asia → lower palm oil output; drought in Australia → lower wheat output.
Societal factors
- Health: sugar labelling and substitutes like stevia (300–400× sweeter, no calories)
- Population: 6.7 bn (2007) → 7.8 bn (2020) → over 8.2 bn today
- Seasonality: turkeys peak before Thanksgiving and Christmas; ~80 million Easter eggs in the UK lift cocoa butter in the first half of the year; Ramadan lifts lamb demand
Government
- Data quality: e.g. USDA’s Prospective Plantings surveys ~80,000 of ~2 million farms; revisions happen. Traders count trucks at Abidjan cocoa warehouses or charter helicopters over crops.
- Protectionism: subsidies (income support, price floors such as the EU’s Common Agricultural Policy), import tariffs, export bans, production limits.
Financial factors
- Food price level: rising over the past two decades (FAO index)
- US dollar: most contracts are priced in USD
- Investors: index rolling (e.g. S&P GSCI) affects curve shape. Are speculators to blame for food prices? Questions to ask: how is speculation defined? Do speculators follow or set trends? Would hedgers lose liquidity without them? How big are futures relative to physical? (Beans are a small part of a Starbucks latte’s price.) Notably, markets with little or no futures trading still spiked: US peanuts tripled (2011), rubber +75% (2010), barley doubled in six weeks (2010), rice USD 300 → 1,000+ (2008).
- Emerging-market wealth: richer diets need more grain — about 3 kg of cereal per kg of pork and 8 kg per kg of beef; higher incomes also shift drinkers from instant (robusta) to brewed (arabica).
Checkpoint 3: drivers
Checkpoint — section 12.5
1 / 5Crude oil prices surge. Most likely effect on soybean prices?
Pick an answer to see if you are right.
12.6 Commitments of Traders (COT)
The CFTC publishes weekly (Tuesday data) a breakdown of open interest (contracts not yet closed) in markets with 20+ large traders. Total longs always equal total shorts.
Legacy categories: commercial (hedgers with an underlying exposure) vs non-commercial (speculators) — though a commercial can still speculate. Since 2009, the disaggregated report adds four groups: producer/merchant/processor/user, swap dealers, managed money (CTAs, commodity pools), and other reportables.
Example: CBOT Soft Red Winter wheat, 24 March 2020 (open interest 359,729)
| Legacy | Long | Short | Spreads |
|---|---|---|---|
| Non-commercial | 97,437 | 62,621 | 121,381 |
| Commercial | 113,970 | 133,809 | — |
| Total reportable | 332,788 | 317,811 | |
| Non-reportable | 26,941 | 41,918 |
Check: 97,437 + 121,381 + 113,970 = 332,788; plus 26,941 = 359,729 ✓.
| Disaggregated | Long | Short | Spreading |
|---|---|---|---|
| Producer/merchant/processor/user | 28,192 | 104,769 | — |
| Swap dealers | 69,832 | 13,094 | 15,946 |
| Managed money | 62,852 | 42,709 | 88,589 |
| Other reportables | 34,585 | 19,912 | 32,792 |
Read: producers and merchants are net short 76,577 (hedging crops); managed money is net long 20,143; swap dealers are net long 56,738 (offsetting index investors’ long swaps). Weekly changes are watched as sentiment indicators.
12.7 Exchange contracts and spreads
| Corn | Chicago SRW wheat | Soybeans | |
|---|---|---|---|
| Size | 5,000 bu | 5,000 bu | 5,000 bu |
| Bushel weight | 56 lb (~25.4 kg) | 60 lb (~27.2 kg) | 60 lb (~27.2 kg) |
| Par grade | No. 2 yellow (No. 1 +1½¢; No. 3 −2 to −4¢) | No. 2 SRW (No. 1 +3¢) | No. 2 yellow (No. 1 +6¢; No. 3 −6¢) |
| Tick | ¼¢/bu = USD 12.50 | same | same |
| Quote | cents/bu | cents/bu | cents/bu |
| Months | Mar, May, Jul, Sep, Dec | Mar, May, Jul, Sep, Dec | Jan, Mar, May, Jul, Aug, Sep, Nov |
| Last trade | Business day before the 15th | same | same |
Conversions: a corn contract ≈ 5,000 × 25.4 kg ≈ 127 t; 1 t of corn ≈ 39.4 bu; 1 t of wheat or soy ≈ 36.7 bu.
Spreads that mimic real economics (some with informal names):
| Spread | Legs |
|---|---|
| Soybean crush | Beans vs meal + oil (processing margin) |
| Hog crush (feeding margin) | Corn and soymeal vs lean hogs — a hog producer’s hedge is long feed, short hogs |
| “BBQ”, “popcorn” spreads | Playful pairings (energy vs live cattle; corn vs sugar) |
Options on the crush spread let processors trade expected meal vs oil demand.
12.8 Case study: “Chocfinger” and the July 2010 cocoa squeeze
flowchart TB
A[Poor Ivory Coast crop<br/>5 years of deficits] --> B[Large long position in July 2010<br/>open interest unusually high]
B --> C[Consumers buy July calls → banks delta-hedge by buying futures]
C --> D[Prices rise; curve backwardates<br/>July–Sep spread GBP 156 → 300]
D --> E[Processors short futures can’t roll<br/>no willing sellers]
E --> F[Expiry 15 July: price GBP 2,750<br/>Armajaro takes delivery of 240,100 t]
- Size: 24,010 lots × 10 t = 240,100 t ≈ 7% of world output; value ≈ 240,100 × 2,750 ≈ GBP 660 million — the biggest delivery in 14 years. Armajaro’s Anthony Ward had done similar in 1996 (300,000 t) and 2002 (148,000 t).
- Why processors were hurt: grinders sell futures to hedge their butter and liquor sales, rolling each contract before expiry. With one dominant long refusing to sell, they had to bid ever higher to close — or deliver beans they didn’t have. Their real exposure was a spread (beans vs butter/liquor), which bean futures hedge only as a proxy.
- Aftermath: a better October crop and a forecast surplus pushed December futures below GBP 2,000, and to ~GBP 1,770 by November. Against a reported average cost of GBP 2,100–2,200 and storage and financing of about USD 7–10 million a month, remaining stock likely lost money. Armajaro sold out by December, delivering much of the ~110,000 t into the December contract.
- Regulation: NYSE LIFFE found no manipulation — taking delivery is a core exchange function. Today’s EU Market Abuse Regulation (2014) explicitly covers “securing a dominant position” over supply that fixes prices or creates unfair conditions.
Lessons: manipulation is hard to define; liquidity can vanish near expiry; proxy hedges carry spread risk (an OTC hedge on butter/liquor would cost more but fit better — like the jet fuel example in lesson 6).
Checkpoint 4: COT and the cocoa squeeze
Checkpoint — sections 12.6 to 12.8
1 / 5Managed money: long 62,852, short 42,709. Net position?
Pick an answer to see if you are right.
12.9 OTC agricultural derivatives
Food companies rarely hedge beyond 12–18 months — crop sizes vary too much year to year. Banks offer swaps even where no liquid future exists, usually settling against CME futures so the physical price and the hedge share a reference.
Corn swap
| Term | Value |
|---|---|
| Notional | 700,000 bu (140 contracts’ worth) for November |
| Fixed payer | Counterparty, USD 3.50/bu |
| Floating | Bank pays the average daily settlement of the first nearby CME corn future |
November average 3.80 → counterparty receives (3.80 − 3.50) × 700,000 = USD 210,000, offsetting a dearer physical purchase.
Spread swaps: biodiesel margins
A biodiesel producer buys soybean (or palm) oil and sells fuel priced like diesel — a spread exposure. In a vanilla swap it pays the floating spread (soy oil − diesel, monthly average) and receives fixed, so a rise in soy oil relative to diesel is offset. Basis risk remains if the swap references e.g. ULSD futures rather than biodiesel itself.
Watched spreads: POGO (palm oil − gas oil), BOHO (soybean oil − heating oil), BOGO (soybean oil − gas oil).
Spread options: selling a POGO put
Put payoff = max(K − (P_palm − P_gasoil), 0) — pays when the spread falls (palm gets relatively cheap).
| Palm | Gas oil | Spread | Payoff (K = 0) |
|---|---|---|---|
| 200 | 250 | −50 | 50 |
| 250 | 250 | 0 | 0 |
| 300 | 250 | +50 | 0 |
Indicative premiums (both prices 250, 30% vols, 6 months, K = 0): correlation −1 → 42, 0 → 30, +1 → negligible. Higher correlation → cheaper, because the spread moves less — true for spread calls and puts alike.
A producer that can switch to palm oil sells the put for 30. If the spread falls to −50 it pays 50 (net −20), but now buys cheaper palm oil as feedstock — it has monetised its switching flexibility. If the spread rises, it keeps the 30.
Accumulator-style producer structure (book: “TARN”)
| Term | Value |
|---|---|
| Reference | 6-month CME corn future (now 3.15) |
| Strike | 3.45 — 30¢ above market |
| Weekly | Price < 3.45 → producer sells 5,000 bu at 3.45; price > 3.45 → sells 10,000 bu at 3.45 |
| Knock-out | Ends if the price trades ≤ 2.85 at any time |
| Cost | Zero |
Decomposition: a weekly strip of bought puts (5,000) and sold calls (10,000, i.e. 2× leverage), both struck at 3.45 and both down-and-out at 2.85.
- Week at 3.20: sells 5,000 at 3.45 → USD 1,250 better than market.
- Week at 3.70: must sell 10,000 at 3.45 → opportunity loss USD 2,500.
- Below 2.85: the structure ends just when protection is most needed.
This first example terminates on a price barrier, not a cumulative profit target — the market usually calls it an accumulator (or knock-out forward). A true TARN (target redemption) ends when cumulative gains hit a target, as in the next example.
TARN collar for a corn consumer
| Term | Value |
|---|---|
| Notional | 5,000 bu a month for 6 months, cash-settled on the monthly average |
| Client buys call | Strike 2.65 (prompt future 3.15 — deep ITM) |
| Client sells put | Strike 2.00 on 2× notional |
| Target | Cumulative call receipts of USD 1.00/bu (= USD 5,000), then the trade ends |
| Month | Avg price | Receives /bu | Cumulative | Pays /bu |
|---|---|---|---|---|
| 1 | 3.20 | 0.55 | 0.55 | 0 |
| 2 | 2.90 | 0.25 | 0.80 | 0 |
| 3 | 2.80 | 0.15 | 0.95 | 0 |
| 4 | 2.30 | 0 | 0.95 | 0 |
| 5 | 1.90 | 0 | 0.95 | 0.20 (0.10 × 2) |
| 6 | 2.75 | 0.05 (capped; 0.10 due) | 1.00 | 0 |
Month 1 cash = 0.55 × 5,000 = USD 2,750; month 5 the client pays 0.10 × 10,000 = USD 1,000.
Effective cost below the put strike (per base bushel): market + 2 × (2.00 − market). At 1.90 → 2.10; at 1.50 → 2.50; at 1.00 → 3.00 — the leverage means the cost rises as prices crash.
Redemption variants for the final payment that would breach the target: partial (pay up to the target — as above), full (pay it all), or none (pay nothing; the client would end at 0.95).
Rank: agriculture practice
Agriculture practice
1 / 3Rank the corn-to-ethanol process.
OrderDrag the handle to rearrange — top should be first.
- 1Add water and enzymes → mash
- 2Distil
- 3Molecular sieve removes water
- 4Heat, cool, add yeast to ferment
- 5Grind kernels to meal
Drag items into the correct order (or use ↑↓), then check.
Check: agriculture
Agriculture
1 / 6Why can grain supply respond faster to high prices than copper supply?
Pick an answer to see if you are right.
Calculate: numeric practice
Type the number (no units; minus sign for payments).
Formula sheet
| Item | Formula |
|---|---|
| Ending stocks | beginning + production + imports − use (− exports, if separate) |
| Stocks-to-use | ending stocks ÷ use |
| Board crush | 0.022 × meal (/lb) − beans ($/bu) |
| Bags → tonnes | bags × 60 ÷ 1,000 |
| Bushels → tonnes | bu × lb per bu × 0.45359 ÷ 1,000 |
| Contract value | price × 5,000 bu |
| Net COT position | long − short |
| Swap (fixed payer) | (average − fixed) × bushels |
| Spread put | max(K − (P₁ − P₂), 0) |
| TARN collar cost below put | price + 2 × (put strike − price) |
Calculate: agriculture
1 / 16Beginning stocks 280, production 764, use 754 (million t). Ending stocks?
Enter a number (at most 0 decimal places).
Randomized practice
Practice: agriculture drills
1 / 6106 million 60 kg bags of coffee. Million tonnes? Round to 2 decimals.
Enter a number (at most 2 decimal places).
Takeaways
- Ags (grains/oilseeds) respond fast; softs are concentrated and shock-prone
- Balance sheet: supply = carry-in + production + imports; ending stocks = supply − use; stocks-to-use ~20–40% is normal
- Crush: 60 lb bushel → 44 lb meal + 11 lb oil; margin = meal + oil − beans
- Coffee: arabica vs robusta, 60 kg bags, “C” futures + premium; cocoa measured by grindings
- Ethanol links ags to oil; cane is far more efficient than corn
- Drivers: the three Fs, weather and ENSO, acreage battles, policy, USD, investors, richer diets
- COT: who is long and short; hedgers net short, managed money drives sentiment
- Squeezes happen when shorts must roll and the long takes delivery
- OTC: swaps, spread swaps/options (correlation matters), accumulators and TARNs — cheap entry, leveraged downside, capped upside
Further Reading
- Next: 13. Commodity-linked financing
- 11. Climate and weather
- 6. Crude oil — proxy hedging (jet fuel)
- 5. Base metals — option structures
- USDA WASDE and Prospective Plantings; ICO, ICCO and ISO statistics; CFTC Commitments of Traders; CME and ICE contract specifications
- Background: N. Schofield, Commodity Derivatives: Markets and Applications (Wiley) — used as a study outline