What if Bumper Brazil soy crop floods market, sinks oilseeds?
A record Brazilian soybean harvest gluts the global oilseed market, depressing soy and meal prices and easing protein-feed and food-inflation pressure.
24%
our model probability over 1–3 years
prediction markets — wisdom of the crowd
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◎ Empirically anchored 24%· 90% range 6–42%· 40 analogues · measured class deflation 69% in 3 yr · 3% held back for the unknownhow we built this number — every step
Measured class rate — deflation ≈0.3895/yr → 69% in 3 yr69%
Analyst prior · editorial share 35% of the class24%
Pooled · weight 87%25%
Crowd — no liquid market—
Reserve 3% · no extremizing (×1.0)25%
Published24%
The class rate is measured from our dated, sourced event library (decade-normalized Poisson — the full table is public at base_rates.json). The variant’s share within its class is the analyst’s editorial call, published so you can audit it. A wider range means thinner precedent. Full recipe: methodology · scored at Reality Check.
The butterfly cascade
How this trigger trickles across markets, left → right — the root shock, its first‑order moves, then the ripple effects. Drag any node; tap a market for its real price history.
Resolution timeline — how this probability is moving
Our model's odds (gold) over time vs the crowd's (Polymarket, blue), from the past toward the 1–3 years horizon. Each dot is a real macro event that nudged the probability — green pushed it up, red pushed it down. Tap a dot for the source. The gold path is an illustrative reconstruction anchored to today's estimate — real dated events, not a live re-estimate history.
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What it would mean
If this plays out, it is a mixed shock. A record Brazilian soybean harvest gluts the global oilseed market, depressing soy and meal prices and easing protein-feed and food-inflation pressure. The trigger decomposes into signed root‑shocks — Corn ▼ · EM currencies ▲ · Climate/crop supply ▼ · Food inflation ▼ — which propagate through our causal graph to the markets below.
If it happens — the markets it would move
Biggest moves first. Projected moves are cascade-model priors; hist A–B% = what comparable past events actually did (measured abnormal returns), and model prior · unmeasured marks markets with no analogue backing yet. Tap any market for its price history.
Market
Class
Projected move
1
CornCORNon Hyperliquid📈 chart
Commodity
▼ -0.6%
hist -0.69–+0.89% · other way -6.18% (n=6)
2
WheatWHEATon Hyperliquid📈 chart
Commodity
▼ -0.4%
hist -0.52–+0.44% · other way -2.01% (n=6)
3
Turkish liraTRY📈 chart
FX
▲ +0.3%
hist -0.63–+0.31% · other way +0.91% (n=6)
4
Indian rupeeINR📈 chart
FX
▲ +0.2%
hist +0.04–+0.24% · other way -0.21% (n=6)
Probable recommendation
If the scenario above plays out, the probable cross‑asset positioning → a scenario‑conditional read, not personalized investment advice
For a common-man portfolio: Mixed for a typical portfolio — the move is more about rotation than direction. Favour the winners over the losers below rather than net exposure.
Also moves (not yet on Hyperliquid): Turkish lira +0.3% · Indian rupee +0.2%
Historical precedent — what analogous events actually did
Across 40 analogous events (overlap‑weighted), as abnormal returns — market beta stripped, so it's the event's own effect, not the market backdrop. Shown at 20 days (persistent) and 5 days (immediate); ↺ fades = the two horizons disagree. Confidence = consistency × sample × significance.
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