CBBI — Bitcoin Bull Run Index, explained

What is the CBBI?

Most Bitcoin cycle indicators fail in the same way: they look brilliant on one cycle and miss the next one entirely. The Pi Cycle Top Indicator nailed the 2013, 2017 and April 2021 tops — and then misfired in November 2021. The Stock-to-Flow model called the 2020 bull market beautifully and then quietly fell apart in 2022.

The CBBI — the Bitcoin Bull Run Index published by Colin Talks Crypto — addresses that problem by refusing to bet on any single signal. Instead, it averages nine independent indicators, each scaled to a 0–100 confidence score, and reports the result as one number. When most signals agree, the score is high (top conditions) or low (bottom conditions). When they disagree, the score sits closer to 50 and the model effectively says "unclear cycle phase, look elsewhere."

The 9 components

Each of the nine inputs is calculated independently from public data, then converted to a 0–100 score using historical extrema as anchors. Equal weight, simple average. Here's what each one measures:

How to read the 0–100 score

Historical extremes — what actually happened

The CBBI has been around long enough to backtest cleanly against four major Bitcoin cycle events:

• December 2017 cycle top — CBBI hit 99. Price was around $19,800. The model called the top within a week.
• December 2018 cycle bottom — CBBI dropped to 6. Price was $3,200. This was the lowest CBBI reading of the post-2013 era.
• March 2020 COVID flash crash — CBBI fell to 11 as BTC briefly touched $3,800. The recovery into the 2021 bull market started within weeks.
• April 2021 first peak — CBBI hit 89 with BTC at $64k. The model flagged distribution but didn't max out — a hint that the bull cycle wasn't fully exhausted.
• November 2021 second peak — CBBI reached ~85 with BTC at $69k. Notably below 2017's peak — the model read this as a structurally weaker top, which the subsequent 2022 drawdown confirmed.
• November 2022 FTX-collapse bottom — CBBI registered 9 with BTC near $16k. Within 14 months price had quintupled.
• March 2024 spot ETF rally peak — CBBI pushed into the low-80s as BTC made new all-time highs above $73k. Distribution zone — but not as overheated as 2017.

Two patterns are consistent. Scores under 15 have caught every major durable bottom. Scores over 80 have caught every major distribution phase. Neither is a precise timing signal — the model has stayed in extreme zones for weeks at a time.

Limitations

The CBBI is the most carefully designed cycle composite available for free, but it has real limits:

• It's backward-calibrated. Each component's 0–100 mapping is anchored to past cycle extremes. If cycle dynamics change (post-halving compression, institutional ETF flows, regulatory shifts), the calibration may understate or overstate the next top.
• Components have different time lags. Pi Cycle and Trolololo react slowly. Google Trends spikes and crashes in days. The model averages these without time-aligning them.
• It doesn't see macro. Fed rate cuts, ETF approvals, MicroStrategy buys, geopolitical shocks — none of these are direct inputs. The model reacts to price/on-chain effects of those events, not the events themselves.
• Extreme readings persist. Reading 95 in November 2017 did not equal "sell at 19k". The CBBI stayed in the 90s for most of December. A user mechanically selling on first touch of 80 would have exited at $18k and watched it run to $19.8k.
• Stock-to-Flow is contested. One of the 9 components — Stock-to-Flow Deflection — has been broken since 2022. Colin keeps it in the index for historical comparability but its predictive value is now disputed.

How btclyzer uses the CBBI

btclyzer fetches the live CBBI score and the individual component breakdown from Colin's public dashboard. Both feed into the adaptive multi-factor algorithm — but the weight is timeframe-dependent.

On the 1H and 4H ratings, CBBI's influence is small. The index moves slowly; on those short timeframes RSI, MACD and volume dominate. On the 1W and 1M ratings, CBBI is one of the heaviest inputs — those timeframes track the slow cycle dynamics that CBBI was designed for.

A CBBI of 85 in the dashboard won't automatically flip the rating to SELL. The algorithm checks whether the technical structure agrees — is price extended above EMA 200? Is MACD turning down? Is the RHODL component above its own historical 80th percentile? Only when multiple signals converge does the rating shift. This is also where the live DCA zones are projected — accumulation ranges anchored to support when the rating leans BUY, distribution ranges anchored to resistance when CBBI and trend agree on overheated conditions.

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