Quantile Zones Cold / Warm / Hot
Adaptive valuation framework derived from the standard Koenker-Bassett 1978 quantile regression statistical method. The chart fits log10(price) ∝ days_since_genesis on a rolling 4-year window, then projects the q33 and q66 percentile band edges at each date. The chart segments price action into three zones: Cold (price below q33 - accumulation regime), Warm (between q33 and q66 - neutral mid-cycle), Hot (above q66 - extreme regime). The bands compress with network maturation, preserving cycle-comparability across all 3 verified cycles.
What is it?
The Quantile Zones Cold/Warm/Hot chart overlays the Bitcoin spot price with three adaptive valuation bands computed via OLS quantile regression on log10(price) vs days_since_genesis over a rolling 4-year window. The lower band edge is the q33 quantile (33rd percentile predicted price), the upper band edge is the q66 quantile (66th percentile). The three resulting zones - Cold (below q33), Warm (between q33 and q66), and Hot (above q66) - adapt to the network's maturation over time. By construction, each band absorbs roughly one-third of historical observations within its rolling window, providing structural cross-cycle comparability that fixed-band frameworks (like a static power-law) cannot. The chart is updated daily at publication T+0 (no editorial lag).
How to read
Read the chart in three layers. First, the primary line (Trinity Gold) shows the Bitcoin spot price on a logarithmic scale. Second, two dashed Trinity Gold lines mark the quantile band edges: the lower line at q33 (33rd percentile predicted), the upper line at q66 (66th percentile predicted). Third, three colored filled bands reinforce the regime visualization: a cyan band below q33 (Cold accumulation territory), a terracotta band between q33 and q66 (Warm neutral regime), a bordeaux band above q66 (Hot extreme regime). The right Y-axis shows BTC spot price for context (always-on overlay). Historical markers anchor past regime extremes: red down-arrows for past cycle peaks touching or exceeding the Hot band, cyan up-arrows for past cycle troughs touching or piercing the Cold band. Read the chart structurally: the current position of the price relative to the three bands immediately tells you which regime quantile the network is in.
Key zones
Cold band (cyan fill, below q33): the lower third of the rolling 4-year price distribution. Historically Bitcoin entered Cold regimes during cycle bottoms and deep accumulation phases. Three documented historical examples: January 2015 (cycle 1 trough), December 2018 (cycle 2 trough), November 2022 (cycle 3 trough). Cold regimes have historically lasted multiple months and have been followed by long-duration bull markets. Warm band (terracotta fill, between q33 and q66): the middle third of the rolling 4-year price distribution. Historically Bitcoin spent the majority of inter-cycle time in this neutral regime - neither extreme. The band represents the network's typical operating range. Hot band (bordeaux fill, above q66): the upper third of the rolling 4-year price distribution. Historically Bitcoin entered Hot regimes during cycle peak windows and advanced bull market phases. Three documented historical examples: December 2013 (cycle 1 peak), December 2017 (cycle 2 peak), April 2021 (cycle 3 first peak). Hot regimes have historically been briefer than Cold regimes (weeks to a few months, vs months of Cold). Band evolution: the band edges shift over time as the rolling 4-year window evolves. Past cycle Hot bands sat at lower absolute prices than future cycle Hot bands - but the structural percentile rank is constant.
What to observe
• Cold band entry/exit: when the price drops into the Cold band, structural accumulation regime begins. Past entries marked cycle bottoms within months. Exit from Cold (back into Warm) has historically marked the start of recovery phases. • Hot band entry/exit: when the price climbs into the Hot band, structural extreme regime begins. Past entries marked the approach to cycle peaks. Exit from Hot (back into Warm) has historically marked the peak event. • Time spent per band: in past cycles, Cold band time has been months, Warm has been the longest (years cumulative), Hot has been weeks. Asymmetric time distribution is structural to the quantile framework. • Band adaptation: the band edges shift over years as the rolling window evolves. Old historical observations leave the window, new ones enter. The bands grow with the network's price scale. • Cross-cycle comparison: the structural percentile rank is the comparable measure across cycles, not absolute prices. A Hot band touch in 2013 (Mayer-equivalent at the time) and a Hot band touch in cycle 4 (different absolute prices but same percentile rank) represent the same structural regime.
Historical context
The quantile regression statistical method was formalized in econometrics in the late 1970s (Koenker & Bassett 1978, public-domain method) and has been widely used in finance and economics since. The application to Bitcoin valuation - fitting rolling quantile bands on log-price vs network age - emerged in the on-chain visualization community in the mid-2020s as a refinement over fixed-band frameworks. The advantage of the rolling 4-year window is adaptation to network maturation: cycle 3 amplitude compression vs cycles 1-2 is automatically reflected in the band edges shifting. By construction, each band absorbs roughly 33% of historical observations - a calibration constraint built into the regression. Trinity v3.0 implements the framework via numpy OLS + percentile residuals (refit weekly + linear interpolation between fits). Historical regime sequences: cycle 1 Cold late 2014/early 2015, Hot December 2013; cycle 2 Cold late 2018, Hot December 2017; cycle 3 Cold late 2022, Hot April 2021. The post-ETF cycle 4 will see the bands evolve dynamically as new observations integrate into the rolling window.
Expert notes
The quantile regression uses ordinary linear quantile regression on log10(price) ~ days_since_genesis. The rolling window is 1460 days (4 years). For performance, the regression is fitted weekly (every 7th day) and the band edges are interpolated linearly between fits - this reduces compute by ~7× without meaningful accuracy loss given the slow evolution of the rolling window. The q33 and q66 quantile choices give a clean three-zone partition by construction (cold = bottom third, warm = middle third, hot = top third). Alternative quantile choices (e.g., q20/q80 or q10/q90) would give different zone widths but the same conceptual framework. Trinity chose q33/q66 for balanced zone occupancy. Caveat: the rolling window means the bands are slightly lagged - observations near the current date have less rolling history to fit against. The 1460-day window requires data from 2011 onward; the minDate of the chart is 2014 (4 years of warmup), well-suited to display the cycle 2/3/4 dynamics.
Common mistakes to avoid
• Treating the bands as fixed price levels: the bands are adaptive - they evolve as the rolling 4-year window evolves. A Hot band edge in 2018 was at a very different absolute price than the Hot band edge in the cycle 4 post-halving era. • Assuming each band always holds 33% of time: the 33% target is a calibration property by construction over the rolling window - observations near the current date may have transient deviations. • Expecting cycle peaks always to break Hot: in past cycles, the price has historically reached or exceeded the Hot band at peaks. But cycle 3 amplitude compression made the cycle 3 first peak (April 2021) sit closer to the Hot band edge than cycle 1-2 peaks. Future cycles in the post-ETF regime may continue this compression. • Reading bands as forecasts: the bands describe past distribution patterns, not future targets. A current price near the Hot band edge does not guarantee future cycle peak materialization. • Using on short timeframes: the chart's value is the multi-cycle adaptive band visualization. Reading on 1y loses the cross-cycle comparability that makes the framework valuable.
Programmatic access
REST API
curl -sS \
'https://api.trinityinsights.io/api/v1/cycle-intelligence/cycle-quantile-zones-cold-warm-hot/history?days=90' \
-H 'X-API-Key: $TRINITY_API_KEY'MCP server
{
"tool": "get_chart_value",
"metric_id": "cycle-quantile-zones-cold-warm-hot",
"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.