Soybeans.
CBOT soybean futures — global oilseed benchmark
$
CBOT Soybeans (cents per bushel)
52-Week Range
953.25 — 1,248.75
568 trading days
Ann. Volatility
17.1%
MLE λ=0.992 (N=567)
VaR (95%)
1.82%
Cornish-Fisher
Regime
Mixed
P(turb.) = 38%
Price History.
Daily closing prices with Bollinger Band overlay
Regime Detection.
Hamilton (1989) two-state Markov switching model
Calm State
σ = 11.8% ann.
Avg. duration: 2 days
Turbulent State
σ = 21.6% ann.
Avg. duration: 2 days
Regime Timeline
Transition Probabilities
P(calm → calm) = 51.7%
P(calm → turb.) = 48.3%
P(turb. → turb.) = 50.0%
P(turb. → calm) = 50.0%
Model Diagnostics
Converged: Yes
Observations: 567
Log-likelihood: 1763.8
Vol ratio (turb/calm): 1.8x
Returns Distribution.
Log return histogram with normal overlay
Mean
0.0054%
Std Dev
1.0933%
Skewness
-0.149
Excess Kurtosis
0.798
Jarque-Bera
17.16
JB p-value
0.0002
Normal?
No
Observations
567
Why this matters
The return distribution is approximately normal, suggesting standard risk metrics are reasonably accurate.
Volatility.
EWMA volatility (λ = 0.992) — annualized
Seasonality.
Monthly return patterns across available history
| Year | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2024 | — | — | — | +15.1% | +3.6% | -8.4% | -7.4% | -2.2% | +5.7% | — | -0.5% | +2.1% |
| 2025 | -1.4% | -2.1% | -1.1% | +2.9% | -0.3% | -1.4% | -3.7% | +6.6% | -5.0% | +7.0% | +1.7% | -7.6% |
| 2026 | +6.2% | +10.0% | +0.0% | +2.1% | -0.7% | -0.5% | — | — | — | — | — | — |
Average Monthly Return
Seasonal Context
The US planting season (April–May) and growing season (June–September) drive weather-premium pricing. Brazilian planting (October–December) and harvest (February–April) create a secondary cycle. USDA WASDE reports on the 12th of each month are the single largest volatility events.
Risk Metrics.
Value at Risk, Expected Shortfall, and drawdown analysis
Interpretation: On 95% of trading days, the loss is expected to be smaller than 1.82%. On the worst 5% of days, the average loss (CVaR) is estimated at 2.19%. The 99% VaR captures more extreme tail events at 2.85%.
Estimated from 567 daily returns. Tail risk estimates improve with longer history.
Maximum Drawdown: 23.66%
Related Markets.
Return correlations with economically linked assets
ZS vs ZW: 165 overlapping return observations
ZS vs KC: 163 overlapping return observations
Note: Return correlations are unstable over time and do not imply causation. These pairs are shown because they share economic drivers (e.g., agricultural supply chains, energy complex), not because correlation alone is meaningful. Short-sample correlations (N < 250) should be treated as rough estimates.
Trend Analysis.
Hurst exponent and Bollinger Band bandwidth
Hurst Exponent
Estimated via R/S analysis from 567 return observations
Bollinger Bandwidth
Bandwidth is contracting (squeeze) — volatility is compressed. Whether this resolves up or down is not predictable from bandwidth alone.
About Soybeans.
Fundamentals, catalysts, and Ethiopian trade relevance
Ethiopian Trade Relevance
Ethiopia's growing oilseed sector (sesame, niger seed, soybeans) competes in the same global vegetable oil market. Soybean prices set the floor for Ethiopian oilseed exports and influence domestic edible oil costs. The crush spread (soybeans vs. meal + oil) is a key margin indicator.
Supply & Demand Fundamentals
The most traded oilseed globally. Brazil surpassed the US as the largest producer in 2020. China imports ~60% of globally traded soybeans. The crush spread (ZS vs ZM + ZL) reflects processing margins. Trade flow disruptions (tariffs, logistics) create basis volatility.
Key Reports & Catalysts
Quote Convention
CBOT Soybeans (cents per bushel)
Unit
¢/bu
Trading Days/Year
252