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Market Personality · Report

SB — Sugar #11

SB is in a mean-reverting state — moves fade, ranges hold, breakouts get sold. This is the environment where fading extremes historically works. We built this read from 37 years of SB daily data.

Archetype: Working Range

 

Archetype verdict

Sugar #11 is a Working Range market right now — the archetype label is how the full 37-year read of its personality rolls up into one tag. Clean oscillation at normal vol. Mean-reversion books pay here.

Three readings drive that call (all scored against SB’s own history, not against other markets):

  • Volatility: Normal — 53rd percentile — in the typical band
  • Trend strength: Mean-Reverting — 37th percentile — medium-term persistence runs low (shorter memory)
  • Tail risk: Clean — 8th percentile on kurtosis — no fat-tail shocks piling up
Vol regime
Normal
Trend regime
Mean-Reverting
Tail regime
Clean
What to do with this read
  • If you’re a mean-reversion trader: This is your environment. Range-fading and overbought/oversold signals carry more weight here than during trend regimes.
  • If you’re a trend trader: Breakouts get faded. Wait for a Hurst move above 0.5 or a vol-regime shift before committing to trend systems.

Live SB signals · Feature glossary · Personality map

DNA radar

This radar chart is SB’s fingerprint today. Each of the six spokes measures one trait of the market — how strongly it trends, how volatile it is, how fat its tails are, and so on — ranked against SB’s own 37-year history. A big spike on one spoke means SB is unusually strong on that trait right now. The overall shape is the market’s personality at a glance.

SB DNA Radar

5-year trajectory

Today’s radar is only one frame. This strip shows four frames — 5 years back, 2 years back, 1 year back, and today — so you can see SB’s personality evolve over time. All four use the same yardstick (SB’s full history), so any change in the shape is a real change in the market, not a change in how we’re measuring it. The label under each frame is the archetype we called at that time.

SB 5-year personality trajectory

How to read it: a growing polygon means the market is heating up on those traits. A shrinking polygon means it’s cooling off. Big label changes between frames (e.g. Healthy Trend → Full Crisis) are the real regime shifts worth paying attention to.

Current-state scorecard

Here’s the full read — all 16 traits we track, measured over four lookbacks (1 year, 2 year, 5 year, lifetime). Each number is a percentile: how today’s reading ranks against this market’s own history over that window. BIG 6 tags the six traits that drive the radar chart above. Use the arrow column to see whether each trait is rising, flat, or falling vs its 2-year distribution.

Feature Current 1-year pctile 2-year pctile 5-year pctile Lifetime pctile Trend
Medium-term persistence (Hurst)BIG 6

~0.5 random-walk-ish; higher = long-memory; NOT a next-day trend signal
0.58 32nd 16th 32nd 37th ↓
Volatility (annualized)BIG 6

daily swing size, annualized
23.9% 67th 34th 13th 53rd ↓
Volatility of volatility (VoV)BIG 6

low = steady vol, high = regime change coming
0.19 95th 71st 80th 36th →
Tail fatness (excess kurtosis)BIG 6

0 = normal, >3 = fat tails, >6 = crisis tails
-0.12 16th 21st 36th 8th ↓
Tail direction (skew)BIG 6

negative = downside shocks worse than upside
+0.16 12th 33rd 52nd 72nd →
Predictability (sample entropy)BIG 6

low = patterns repeat, high = noise
0.57 74th 58th 53rd 55th →
Trend vs chop (5-day) (variance ratio)

>1 = trending, <1 = mean-reverting
0.91 41st 21st 19th 33rd ↓
Trend vs chop (20-day) (variance ratio)

>1 = trending, <1 = mean-reverting
0.78 71st 35th 52nd 45th ↓
Mean-reversion speed (OU half-life, days)

days for a shock to decay by half
25d 4th 26th 34th 29th ↓
Trend vs range test (ADF p-value)

>0.10 = still trending, <0.05 = range-bound
0.40 17th 36th 42nd 30th ↓
Day-to-day momentum (lag-1 autocorrelation)

positive = trend-continuation, negative = snap-back
-0.08 27th 13th 8th 9th ↓
Price-path roughness (fractal dimension)

~1.0 clean trend, ~1.5 noisy, ~2.0 chaotic
1.51 10th 44th 47th 61st →
Volatility stickiness (GARCH persistence)

near 1 = vol hangs around, <0.9 = vol fades
0.96 54th 59th 69th 62nd →
Cycle clarity (spectral entropy)

low = dominant cycle, high = no clear rhythm
0.93 97th 94th 96th 91st ↑
Price-vol link (leverage correlation)

negative = vol spikes on selloffs (normal), positive = squeeze
0.07 100th 79th 89th 73rd ↑
Worst drawdown (rolling max drawdown)

deepest peak-to-trough drop over the window
-28.2% 89th 72nd 37th 32nd ↑

← swipe horizontally on mobile to see all columns.

Trend column: ↑↑ strongly rising vs 2-year distribution, ↑ rising, → flat, ↓ falling, ↓↓ strongly falling. Thresholds are 0.5 and 2.0 standard deviations. Percentile ranks use the full lifetime distribution — a 70th-percentile reading means today is higher than 70% of all observed days. The 1-year column uses only ~252 days and should be read as a short-term signal, not a precise rank.

Macro lens

Macro lens

Separate from the per-market pair signals above, these are findings where SB‘s personality archetype carries information about an external macro regime — an inflation print, a yield-curve inversion, a drought. These are empirical “when this market’s personality looks like X, that external macro regime tends to follow” findings — context signals, not trade recommendations.

Macro lens
Brazil sugar drought lead indicator

When sugar enters a Momentum Run archetype, the Brazilian Center-South sugar belt sees a seasonal dry anomaly within six months 51% of the time — nearly double the base rate.

When SB is in Momentum Run, Brazil sugar-belt water deficit follows within 6 months  ·  51% vs 28% baseline (lift 1.79x, n=53 months)

Brazil is the world’s biggest sugar producer; its Center-South belt drives global pricing. Sugar’s momentum runs lead confirmed TERRACLIMATE deficits in that region. Companion to the KC coffee and S soy TERRACLIMATE signals — all three measure Brazilian agricultural stress from a different crop angle.

During active brazil sugar-belt water deficit, SB most often shows (over/under its own base rate)
Healthy Trend1.95x
Violent Range1.54x
Grind Higher1.39x
Coverage 2000-01 to 2025-12 · 312 months total, 16 in regime · Source: TERRACLIMATE_REGIONAL_MONTHLY (BRAZIL_SUGAR_CENTER_SOUTH)
● Firing now

Macro lens
Thailand sugar drought lead indicator

When sugar settles into a Working Range archetype, a seasonal dry anomaly in the Thai sugar belt follows within six months 52% of the time — roughly 2× the baseline.

When SB is in Working Range, Thailand sugar central water deficit follows within 6 months  ·  52% vs 26% baseline (lift 1.99x, n=29 months)

Thailand is the world’s #2 sugar exporter after Brazil. Companion to the Brazilian sugar-belt signal — together they cover both major cane growing regions. Coiled-Calm SB shows 2.79× lift during active Thai droughts, suggesting the market compresses before the supply reality is in the data.

During active thailand sugar central water deficit, SB most often shows (over/under its own base rate)
Coiled Calm2.79x
Healthy Trend1.49x
Hidden-Risk Range1.35x
Coverage 2000-01 to 2025-12 · 312 months total, 21 in regime · Source: TERRACLIMATE_REGIONAL_MONTHLY (THAILAND_SUGAR_CENTRAL)

Past co-movement does not guarantee future results. Macro-lens entries are context signals — not trade recommendations.

37-year history

Three ways to look at SB’s full 37 years of personality. First chart: every Big-6 trait over time, with the “normal range” shaded in cream and the big macro events (crashes, policy pivots, crises) marked. Second chart: the whole 37 years compressed into one map so you can see how the market has moved through regime-space. Third chart: a month-by-month color calendar of which archetype SB was in — scroll it like a weather map of the market.

Coverage: 1989-12-01 to 2026-05-22 · 9,146 daily observations.

Feature history

One panel per Big-6 trait, over all 37 years. Hover any point for the exact reading. Drag the bar at the bottom to zoom into a specific era (e.g. 2008, 2020). The cream band is the p10-p90 envelope — the middle 80% of all-time readings. Treat it as a “normal zone” with a caveat: markets with fat tails routinely visit the extremes, so a value outside the band isn’t anomalous, just historically unusual. Triangles along the top mark major market events (structural breaks — crashes, policy turns, war); hover to see each one.

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Personality map

This map shows where SB has lived over 37 years. The shaded region is a density map — darker patches are where the market has spent most of its time. The labeled circles (1990s, 2000s, 2010s, 2020s) are decade medians, color-matched to time (navy = early, gold = recent). The gold diamond is today, with the exact reading. Left-to-right is how strongly the market was trending (right = more trend, left = chop). Up-down is how volatile it was vs SB’s own history (0 = quiet, 100 = extreme). Read it as: is today close to where the market usually lives, or at the edge of unfamiliar territory?

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Regime calendar

Every month of SB’s life, labeled as one of 12 personality types (combinations of volatility, trend, and tail risk). Each color is one archetype — the legend below the chart ranks archetypes by how much of the history the market has spent in each. Hover any band to see the exact month and archetype. Triangles are the same macro-event annotations from the first chart.

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Methodology

The 16 traits. We group them into four families (click any underlined term for a quick definition):

  • Trend traits (does the market keep going in one direction?): Hurst exponent (R/S estimator), variance ratios, ADF p-value, OU half-life, lag-1 autocorrelation.
  • Volatility traits (how big are the daily swings, and are they sticky?): annualized vol (std dev of daily log returns, rolling 252-day window, scaled by √252), vol-of-vol, GARCH(1,1) persistence.
  • Shape traits (are the tails fat? which side are shocks on?): skewness, excess kurtosis (Fisher), leverage correlation.
  • Complexity traits (is the price path noisy or clean? do cycles repeat?): sample entropy, spectral entropy, fractal dimension, rolling max drawdown.

How we pick the archetype. Three pieces — volatility level, trend strength, tail risk — combine into a 12-box grid of personality types. We use SB’s own history (not a cross-market ranking), so a quiet market and a wild market can both be scored fairly against themselves. The classifier reads exactly three of the sixteen traits (Hurst percentile, annualized-vol percentile, kurtosis percentile) through hand-set thresholds. The other 13 traits inform the scorecard but not the archetype label.

How to read a percentile. “70th percentile vol” means today’s vol is higher than 70% of SB’s own history — NOT higher than 70% of other markets. Every number on this page is scored against SB itself. Cross-market comparisons live on the personality clusters page.

Caveats worth knowing.

  • Percentile series look ahead. Readings on the feature-history chart are ranked against the market’s full lifetime, including data after the x-axis date. A 2008 reading at the 90th percentile is high relative to what we now know of history, not relative to what was known in 2008. This is a snapshot characterization, not a point-in-time rank series.
  • The archetype classifier reads only 3 of 16 traits. Features like skewness, entropy and the complexity family feed the scorecard but not the label.
  • Hurst is a structural measure, not a daily-trend signal. Hurst > 0.5 indicates long-memory in the 252-day rolling return series — useful for characterizing regime. It does NOT reliably predict positive next-day return autocorrelation. Our in-house empirical test on 37 years × 18 markets found no such link. Don’t read a “trending” Hurst label as a day-trading signal.
  • Rule-based classifier. Thresholds are hand-set. The classifier does not learn from alert performance (that lives in TA Profile).
  • Short-window instability. 1-year percentiles use ~252 days; on recently-listed markets (e.g. BTC) they are noisier than lifetime stats. Read the Lifetime column when confidence matters.
  • Rolling windows lag sharp breaks. Expect feature readings to lag sharp regime breaks by a few bars.
  • Event markers are hand-curated. The triangles on the feature history and regime calendar are macro-event annotations, not the output of a change-point detection algorithm. Alignment between an event and a visible shift on the chart is for reference, not a statistical claim.

Full plain-English definitions for every feature in the Feature glossary.

Related

  • Market Personality hub — back to the market index.
  • Personality clusters — both the structural map and today’s state map across all live markets.
  • Feature glossary — plain-English definitions for all 16 features.
  • Live risk-state detector (Phase 4 continuous stress score) — coming soon.