Definition. A strategy is regime-dependent when its edge is conditional on a market state — a volatility level, rate environment, trend phase, liquidity ecology, or participant mix — rather than unconditional. Almost every real edge is; the failure isn’t dependence itself but unexamined dependence: a backtest that quietly averaged over a favorable mix of states, sold as an all-weather number. Regime dependence is also the honest competitor to the overfitting explanation: when a live edge goes quiet, noise-fitting, regime shift, and ordinary variance are the three suspects, and they demand different responses.
The worked example: the average that never happens
A short-volatility carry strategy backtests at SR 1.6 over 2012–2019. Decompose by VIX tercile and the story changes: SR ≈ 2.5 in the calm two-thirds of months, SR ≈ −1.8 in the turbulent third. The headline 1.6 is an average over a regime mix — and the strategy’s forward performance is entirely a bet on that mix persisting. 2020 reweights the mixture for one quarter and erases three years of carry. Nothing “stopped working”; the conditional structure was always there, and the unconditional Sharpe was an answer to a question nobody would knowingly ask. The same decomposition indicts many trend, carry, and liquidity-provision results across the archive.
Detecting regime-carried results in a paper
- ☐ Conditional performance table: results by volatility tercile, rate environment, and trend state. Absence in a 15+ year backtest is the omission that robustness sections owe.
- ☐ Contribution concentration: what fraction of total P&L comes from the best 10% of months? Edges earned in bursts are regime bets with a drumroll.
- ☐ Era honesty: does the sample span structural breaks the mechanism cares about — decimalization for microstructure, the zero-rate decade for carry, pre/post-2018 crypto institutionalization? A mechanism whose habitat no longer exists has a perfect backtest and no future.
- ☐ Mechanism-regime coherence: the paper’s story should predict the conditional pattern. Momentum that claims a behavioral mechanism but earns only in one rate regime has a story-evidence mismatch.
The live-trading diagnosis problem
The hardest question in production: the strategy is down — decayed, regime-shifted, or just unlucky? They’re separable only with pre-committed structure:
- Base rates first: a true SR 1.0 strategy spends long stretches underwater with substantial probability — run the fan before pattern-matching to doom. Most “it stopped working” calls at month 8 are reading noise.
- Regime instruments: if the edge is conditional, monitor the conditioning variable, not just P&L. Short-vol losing while VIX is at 35 is on-model; losing at VIX 12 is evidence against the mechanism.
- Decay signature: alpha decay from crowding tends to be gradual and monotonic (each year weaker than the last, spreads compressing) versus regime losses which are state-locked and reversible. The post-publication literature shows decay; 2020’s factor reversals showed regime.
- Pre-commit the rules: the production checklist’s written stop criteria exist precisely because this diagnosis is impossible to make honestly mid-drawdown.
What to do with a regime-dependent edge
Dependence is manageable; three honest options, in order of ambition: size by state (condition exposure on the regime variable — now the regime model is part of the strategy and counted in its trials); diversify across regime exposures (pair edges with complementary habitats — the real argument for multi-strategy construction); or accept and disclose (run it unconditionally, but with the conditional table taped to the monitor and drawdown expectations set by the bad-state Sharpe, not the average).
Questions to ask while reading
- What state variable would this mechanism predict conditions the returns — and does the paper test it?
- What share of profits comes from the single best regime episode?
- Does the sample’s regime mix resemble any plausible future?
- If this edge went quiet for 18 months, what observation would distinguish shift from decay?
What our scoring captures — and misses
Subperiod and conditional analysis feed the rigor axis directly — papers with regime tables outrank equal-Sharpe papers without them. What scoring can’t do is judge habitat survival: whether the states an edge needs still occur is a forward-looking market question, not a paper-quality one. The score certifies the fossil is real; whether the climate still supports the animal is your call.
Companions: Robustness’s five dimensions → · Drawdown base rates → · A layer across regimes → · When to stop a live strategy →