Executive summary
Pierre Andurand’s flagship Andurand Commodities Discretionary Enhanced fund experienced a sequence of extreme monthly losses in 2025 that produced a cumulative drawdown of 52% by April 23, 2025 and roughly 60% by mid-June 2025. The fund began 2025 with roughly $900M in assets under management, declined to about $432M by April (≈-52% from the start of the year) and to about $360M by mid-June (≈-60% YTD). This case study explains the trading and risk dynamics behind that collapse, quantifies the P&L path, and extracts lessons for quantitative researchers and risk managers.
1. Strategy and positioning: concentrated, directional, leveraged
Andurand’s approach has long been to take large directional positions — often highly leveraged — in commodity futures and related markets, with a structural tolerance for outsized risk. That style produces large positive skew in good years and very large negative skew in bad years. The recent collapse shows how quickly concentrated, directional bets can become catastrophic when:
exposure is sizeable relative to AUM, and
positions are leveraged without strict maximum-loss or volatility caps.
By late 2024 the fund managed roughly $900M and had extended its trading beyond oil into cocoa, copper and other commodity markets.
2. The loss sequence (concise timeline & math)
Starting capital (Jan 1, 2025): $900,000,000
January 2025: –17%
Remaining: $900M × (1 − 0.17) = $747,000,000February 2025: ≈–25% (on the January balance)
Remaining: $747,000,000 × (1 − 0.25) = $560,250,000Result after February relative to start: loss ≈ (900 − 560.25)/900 = 37.75% YTD
April 1–23, 2025: further deterioration to –52% YTD
Remaining: $900M × (1 − 0.52) = $432,000,000
Cumulative loss through April = $900M − $432M = $468,000,000Mid-June 2025: further decline to ≈–60% YTD
Remaining: $900M × (1 − 0.60) = $360,000,000
Cumulative loss through June = $540,000,000
Recovery requirement: To regain $900M from $360M requires a return of (900/360 − 1) = +150%.
3. Where it went wrong — trade-level breakdown
A. Core oil positions
Andurand remained structurally long oil into 2025.
Market context in 2025: supply additions (notably OPEC+/other production increases) and downward demand revisions from major agencies pressured prices. Several institutional forecasts for 2025–26 implied lower forward oil prices than traders who maintained very bullish positioning had assumed.
With significant leverage, relatively modest adverse price moves produced outsized equity losses.
B. Cocoa diversification that amplified drawdown
The fund expanded meaningful exposure to cocoa in 2024; early gains contributed materially to 2024’s strong performance.
Cocoa then reversed sharply in 2025: prices collapsed from 2024 highs (near ~$12,900/ton in December 2024) to a range materially below that level in 2025.
Market illiquidity and extreme volatility in cocoa produced gap moves and realized losses that were not offset by other positions, so the diversification did not provide the intended hedge — indeed, it amplified realized losses.
C. Leverage and margin dynamics
Typical initial margin profiles in commodity futures imply effective gross leverage of multiple times equity (often 10×–20× on gross notional).
At those leverage levels, an adverse move of a few percentage points can translate to double-digit percent losses in fund NAV. The realised sequence of oil and cocoa moves, combined with concentrated sizing, explains the speed and magnitude of the drawdown.
4. Risk management failures (diagnostic)
Expertise drift: decade-long oil expertise did not automatically translate to cocoa (different supply chains, seasonality, weather and microstructure).
No hard risk limits: absence of strict position-level and portfolio-level loss thresholds permitted drawdowns to compound.
Correlation breakdown during stress: positions across commodities moved together during the market dislocation, undermining diversification.
Liquidity mismatch: large directional notional in less liquid commodity instruments created execution and gap risk during volatile sessions.
Model fragility: historical calibration failed to anticipate a regime shift where momentum and spec flows caused extreme autocorrelation and tail events.
5. Quant lessons for researchers and risk teams
Stress test for correlation regimes: backtests must include scenarios where cross-commodity correlations rise sharply (stress → correlations → 1).
Limit leverage by scenario: set maximum allowable leverage conditional on realized and implied volatility regimes.
Position-level stop rules and portfolio loss limits: automatic de-risking triggers preserve optionality and prevent cascade effects from margin calls.
Horizon alignment: ensure liquidity of instruments matches the time horizon of the strategy; avoid oversized positions in markets that can gap during settlement or thin sessions.
Domain humility: treat domain expertise as partially transferable and validate models rigorously when entering new commodities.
6. Market context that mattered (concise)
Oil: weaker demand revisions and OPEC+/production increments pressured prices in 2025; several institutional forecasts lowered medium-term price expectations.
Cocoa: after an extreme 2024 rally (≈+177% in prices year-on-year), cocoa entered a severe mean reversion phase in 2025; grinding statistics and demand indicators showed declines in some regions, amplifying downside.
Macro & microstructure: volatility regimes shifted abruptly across multiple commodity markets, increasing realized losses for directional, leveraged bets.
7. Short takeaway (one-paragraph)
A concentrated, highly leveraged commodity fund can generate spectacular returns but is exposed to catastrophic losses when market regimes change and correlations spike. Andurand’s 2025 drawdown is a textbook demonstration of the hazard that follows when large directional positions in different commodity markets move together and when diversification into unfamiliar markets is not matched with commensurate risk controls. For quantitative researchers, the clear actionable lesson is to harden risk frameworks to account for regime changes, liquidity shocks, correlation breakdowns, and the limits of model portability across commodity domains.
Technical appendix — P&L cascade (explicit numbers)
Start (Jan 1, 2025): $900,000,000
After Jan (–17%): $900M × 0.83 = $747,000,000
After Feb (–25% on Jan balance): $747,000,000 × 0.75 = $560,250,000 (≈37.75% YTD loss vs. start)
By April 23 (–52% YTD): $900M × 0.48 = $432,000,000 → $468,000,000 cumulative loss
By mid-June (≈–60% YTD): $900M × 0.40 = $360,000,000 → $540,000,000 cumulative loss
Recovery needed from $360M to $900M: +150%
Sources
Bloomberg (March 5, 2025) — “Andurand’s Hedge Fund Erases Last Year’s Gains After 37% Slump”
Bloomberg (June 24, 2025) — “Andurand Hedge Fund’s Losses Worsen to 60% as Turmoil Spreads”
Bloomberg (August 2, 2025) — “Andurand Pulls Back From Cocoa Bets After Extreme Volatility Drives Losses”
Bloomberg (December 3, 2024) — $900M AUM confirmation
J.P. Morgan Global Research — Oil price forecasts (66/66/58), cocoa analysis ($6,000/tonne forecast)
International Energy Agency (IEA) — Oil Market Report April 2025, demand revisions (730/690 kb/d)
U.S. Energy Information Administration (EIA) — STEO August 2025 ($58 Q4 2025, $50+ 2026)
Trading Economics — Current commodity prices (Brent $66.30, WTI $62.46, Cocoa $5,956–6,000)
CNBC, Forbes — OPEC production data (411,000 bpd increase)
QC Intelligence (April 25, 2025) — 52% YTD loss confirmation
International Cocoa Organization — Q2 2025 grinding statistics
Cover photograph: Gary Bembridge from London, UK, CC BY 2.0, via Wikimedia Commons.