The asymmetry of a crisis: fast shock, slow recovery
Crisis pressure builds faster than it resolves. A disruption that reaches peak intensity in 6 weeks may take 30 weeks to fully unwind. This asymmetry matters for how organizations budget and hedge: the spike is visible, the long tail is where cost exposure accumulates.
The chart below shows the structural shape of a typical crisis shock and how M1 and M2 contract types realize that pressure with a lag - M1 (spot and short-term, approximately 30-day invoice lag) and M2 (medium-term contracts, approximately 60-day lag).
Illustrative model. Index base = 100. Values reflect typical crisis shock and recovery patterns, not specific events. M1 = 30-day invoice lag; M2 = 60-day invoice lag. Peak amplitudes are compressed by lag: M1 ~90%, M2 ~75% of index peak.
Crisis library coverage
The analog library covers publicly documented disruptions from 2020 to 2026. Each event was selected for signal diversity - fuel shocks, capacity events, chokepoint restrictions, and demand surges - and for resolution quality, meaning sufficient weekly data exists to encode the full trajectory.
Crises in the analog library are selected for signal diversity and resolution quality. All are publicly documented events. Bar height is proportional to event duration within each year column. Ongoing events shown through latest available data (May 2026).
Example output - Red Sea 2024 (illustrative)During the Red Sea escalation in early 2024, sirius identified a strong analog match against a historical capacity-led chokepoint disruption. The matched trajectory projected FE_EU pressure peaking and plateauing before gradual resolution. M2 contracts were flagged as the primary exposure. The forward signal was available to Pro subscribers ahead of carrier rate announcements.(Illustrative example. sirius Pro subscribers receive the current week's analog match every Friday.)
Why historical analogs
Freight markets are not random. They follow patterns that have recurred across crises: a fuel shock builds capacity pressure, capacity pressure drives surcharge increases, surcharge increases tighten the FX impact on cross-currency lanes, chokepoint degradation amplifies the whole sequence, and environmental cycles determine whether the network can absorb it. The sequence and relative intensity of these six dimensions varies by crisis type, but the structural relationships between them are recognizable.
This means that when a new crisis begins to build in the data, it often resembles a historical precedent - not in its exact magnitude or geographic origin, but in its pressure pattern across the six dimensions. Different crisis types produce distinct pressure signatures across the dimensions. The analog engine identifies which historical event most closely resembles the current configuration.
The crisis analog engine exploits this structural similarity. Rather than extrapolating from recent trend alone - which is unstable in the early stages of a crisis - it identifies which historical event most closely resembles the current pattern and uses the trajectory of that event as a calibration anchor for the forward projection.
The crisis library
The analog library contains historical crisis events, each encoded as a time-series of multi-dimensional pressure readings normalized to the same base scale. The library covers a range of publicly documented disruptions across fuel shocks, capacity cycles, and chokepoint restrictions. A representative selection of events is highlighted in sirius Pro output; the full library composition is described in the Pro methodology appendix.
Each crisis in the library is encoded as a weekly time series starting from the first week of measurable pressure elevation through to recovery, defined as all pressure dimensions returning to near-baseline levels. This produces a crisis "trajectory" with a shape, a duration, and a resolution pattern for each event.
Six scoring dimensions
Each crisis event - both historical and current - is represented as a six-dimensional vector at each week in its trajectory. The six dimensions map directly to the sirius pressure model layers:
- Fuel: Normalized fuel pressure, capturing the combined effect of bunker, jet fuel, and road diesel market moves relevant to the lane being analyzed.
- Capacity: Normalized capacity pressure, capturing vessel utilization, container availability, and blank sailing data where available for the crisis period.
- Surcharge: Normalized surcharge pressure, capturing carrier-declared emergency surcharges, war risk premiums, and congestion charges as a proportion of base rate.
- FX: Normalized currency pressure, capturing the trade-weighted FX movement against the primary currency pair for the trade lane being scored.
- Chokepoints & Straits: Normalized throughput degradation at the key chokepoints relevant to the lane - Hormuz, Suez, Malacca, Panama. Derived from AIS transit counts relative to the 12-month rolling baseline. A partial restriction registers proportionally; a full closure registers at maximum.
- Environment: Normalized pressure from weather, seasonal cycles, and ENSO state. Captures typhoon season activation over Asia-Pacific lanes, monsoon cycle disruptions for Indian subcontinent routing, La Nina-driven drought impact on the Panama Canal, and the compounding effect of peak season demand on an already-stressed network.
Normalization maps each dimension to a 0-1 scale relative to the observed range across all historical crisis analogs. This prevents a crisis with extreme fuel pressure from dominating the similarity score simply because of scale differences.
What an analog match looks like
Each week, sirius scores the current freight pressure pattern across six dimensions against every week in each historical crisis. The closest match becomes the primary analog. sirius then uses the trajectory of that historical event - how pressure evolved from the matched point forward - as the anchor for the forward projection.
The output delivered to sirius Pro subscribers includes: the name of the primary analog event, the week-in-crisis it matched, the confidence score, and the projected path for the next 8 weeks based on how that event unfolded. Secondary analog matches are shown to indicate whether the forward trajectories converge or diverge.
When the top-3 analog matches all point toward a similar trajectory, the confidence band in the forward projection is narrow. When they diverge - for instance if one analog resolved quickly and another persisted for 18 months - the band is wider, which is the correct reflection of genuine historical uncertainty.
Reading the confidence score
The confidence score is published alongside each weekly sirius reading in the Pro report. It tells you how strongly the current pattern resembles a historical precedent - and therefore how much weight to give the analog trajectory in your forward planning.
A high confidence score means the current pattern closely matches a historical crisis at a specific point in its trajectory. The forward projection from that analog is a well-anchored directional signal. A low confidence score means the current pattern does not closely resemble any historical precedent in the library - which is itself informative. It signals either an early-stage crisis still developing its signature, or a genuinely novel event.
When sirius shows low confidence, the appropriate response is to widen your scenario range and rely more heavily on the current-week reading than on the projected trajectory. A novel crisis with no close historical match should not be modeled using the average outcome of past events.
How analogs drive forward projections
When the analog engine finds a high-confidence match, the trajectory of the matched historical event becomes the anchor for the sirius forward projection on that lane. The trajectory is calibrated to the current situation's magnitude and extended forward from the matched point in the historical event.
sirius generates three forward scenarios - base, escalation, and de-escalation - grounded in the trajectories of the closest historical analogs. The scenarios reflect genuine historical variance in how comparable crisis patterns have resolved, not arbitrary percentage bands applied mechanically around the base case.
This structure means the scenarios are not arbitrary. They are grounded in observed historical outcomes on the closest precedents available. The uncertainty band reflects genuine historical variance in how similar crisis patterns have resolved, not a uniform percentage band applied mechanically around the base case.
Why analogs are bounded and not extrapolated
The analog engine explicitly does not extrapolate beyond crisis resolution. Once the analog trajectory reaches its resolution window, the forward projection transitions to the sirius baseline model.
This is a deliberate design choice. The further a projection extends beyond the analog's resolution window, the less the historical precedent constrains it. A 16-week forward projection based on a crisis that resolved in 12 weeks is anchored for only the first 12 weeks. After that, any trajectory is equally plausible and the model would be manufacturing false precision.
The sirius Pro report shows the analog's resolution window explicitly so users can see where the historically-anchored projection ends and where the baseline model takes over. The confidence band widens significantly at and beyond the resolution boundary.
Limitations
The analog engine is a useful calibration tool, not a prediction mechanism. Several limitations are important to hold in mind when interpreting analog-anchored projections:
- The library is finite: The library covers roughly 6 years of modern freight market dynamics across multiple crisis types. A genuinely novel event - a crisis type not well-represented in the library - will produce low-confidence matches. This is a signal to use wider judgment, not to ignore the reading.
- Historical context differs: Even a high-similarity pattern match does not guarantee that the future trajectory will follow the historical precedent. Market structure, carrier concentration, regulatory environment, and geopolitical context all change over time. The 2020 container shortage and a hypothetical 2027 container shortage with the same pressure pattern may resolve differently for structural reasons the model does not observe.
- Six dimensions are not the full picture: The analog engine uses six dimensions. Real crisis dynamics involve many more variables. The engine captures the dominant signals but may miss nuances in demand patterns, political resolution mechanisms, or infrastructure changes that would influence the trajectory.
- Analog confidence is not probability: A high confidence score means the current pattern closely resembles a historical precedent. It does not mean the outcome will follow that precedent with high probability. Both should be understood as directional guidance, not precise forecasts.
The sirius index publishes the primary analog name, its similarity score, and the confidence composite for every weekly reading in the Pro report. This transparency allows users to assess the quality of the historical anchor for themselves rather than accepting the projection as a black-box output.