Cohort Window Sensitivity
Cohort survival across adjustable onboarding windows (30 to 365 days) - test how sensitive the holder-conviction curve is to the accumulation window chosen.
What is it?
This view reuses the per-halving-epoch cohort survival but exposes the cohort-definition parameters: the onboarding window width (30, 90, 150, 180 or 365 days) and the number of days it opens before the halving. Changing the window redefines who belongs to the cohort, and therefore the shape of the survival curves. It is a robustness tool: a conclusion that holds across several windows is more reliable than one that depends on a precise setting.
How to read
Pick a window and observe the ordering of cohorts; change it and check whether the ordering holds. A short window (30D) isolates the buyers at the core of accumulation; a long window (365D) dilutes the cohort with later entrants. If the conviction ranking between cycles stays stable across windows, the finding is structural; if it flips, the reading depends heavily on the definition.
Key zones
The same retention thresholds apply (50% / 25% / 10%), but the focus here is the spread between windows rather than the absolute level. A tight bundle of curves (across all windows) indicates a homogeneous cohort; a wide bundle indicates the cohort composition changes a lot depending on the chosen window.
What to observe
Spot cycles whose conviction is robust (curves close together regardless of window) and those that are fragile (widely dispersed curves). Observe the effect of the pre-halving offset: opening the window earlier captures more of the cycle-bottom accumulation phase, opening it later captures pre-top euphoria.
Historical context
Across the 2012, 2016, 2020 and 2024 halvings, the 150-day window offers a readable compromise between precision and sample size. Cohorts near a cycle low tend to stay more robust to window changes than those onboarded in a late bull phase. The 2009-2012 cohort stays hidden by default (unstable denominator, no price before mid-2010).
Expert notes
The preset windows (30/90/150/180/365 days) sit on age-band edges so the initial cohort size N₀ is exact. Beyond those fine edges, the reconstruction relies on linear interpolation between bands, reliable under six months then increasingly approximate. Sensitivity to the window is itself informative: it is a measure of the cohort's compositional stability.
Common mistakes to avoid
Do not pick the window that 'fits' your thesis: the point of this view is precisely to test robustness, not to select the most flattering setting. A change in ordering between windows does not invalidate the metric - it indicates the conclusion is sensitive to the definition and should be qualified.
Programmatic access
REST API
curl -sS \
'https://api.trinityinsights.io/api/v1/onchain/cohort-hodl-window-sensitivity/history?days=90' \
-H 'X-API-Key: $TRINITY_API_KEY'MCP server
{
"tool": "get_chart_value",
"metric_id": "cohort-hodl-window-sensitivity",
"timeframe": "1y"
}Required tier: pro. See the pricing grid for the tier list and the MCP documentation for multi-client configuration.
Related metrics
Institutional disclaimer
Trinity Insights is an educational and analytical tool. The metric above does not constitute investment advice. Trinity Insights is not a Crypto-Asset Service Provider (CASP) registered under MiCA Regulation (EU) 2023/1114. See the full disclaimer.