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Research · Altcoins

Alt versus Bitcoin drawdowns

A drawdown is measured from a peak to the trough that follows it, and the comparison only means something if the same rule is applied to every asset. This page states the rule first, then describes how the large alts have behaved against bitcoin under it.

Last reviewed 2026-09-21Source: CoinGecko historical daily prices; Coin Metrics community network dataMethod and comparative structure only. No drawdown percentage is asserted without the peak and trough dates that define it.

The method comes first

A drawdown figure is only meaningful alongside the dates that define it. "Down 80%" is not a measurement until the peak date, the trough date and the price series are stated, because a different peak or a different series produces a different number. The comparison below therefore begins with the rule rather than with the results.

The rule used here is a running-maximum drawdown on daily closing prices. At each date, the peak is the highest close seen so far, and the drawdown is the percentage decline from that peak to the current close. The maximum drawdown over a period is the largest such decline within it. This is the standard definition and it has the property that the peak always precedes the trough, which a simple highest-to-lowest comparison does not guarantee.

The comparison uses a common window for every asset rather than each asset's own peak and trough. That choice understates the alts' falls, because an asset's own trough often occurs outside bitcoin's, and it is made deliberately: a comparison in which every asset is measured over its own best-case window is not a comparison.

What the comparison shows

How the large alts have behaved against Bitcoin in the broad declines of the record, described by the mechanism rather than by an unstated figure.
Asset groupDrawdown depthTime to troughWhat the behaviour reflects
BitcoinThe referenceThe referenceThe deepest and most liquid market in the complex, so it absorbs the factor move first and with the least price impact per unit sold
Largest altsDeeper than bitcoin over the same windowTypically similar to bitcoinSame holders and same venues as bitcoin, but thinner books, so the same flow produces a larger price move
Mid-cap altsDeeper still, with a wider spread of outcomesOften longer, because thin books clear more slowlyLiquidity withdrawal is most severe here; some assets also carry asset-specific failures that compound the factor move

Last reviewed 2026-09-21Source: CoinGecko daily series, running-maximum drawdown on closing pricesDirectional description only. Any figure requires the peak and trough dates and the asset set to be stated.

The pattern is consistent with the common-factor explanation set out on the companion page: the alts fall further because they carry more of the same exposure and because their books are thinner, not because bitcoin's decline transmitted into them. The depth ordering follows the liquidity ordering, which is what the mechanism predicts.

The duration column is the one most often ignored. Depth and duration are different properties, and an asset can fall less far but take much longer to reach its trough. A comparison that reports only the depth of a decline omits the part of the experience that a holder actually lives through.

Dataset, period, method and limitations

Dataset. Daily closing prices for bitcoin and for the largest non-bitcoin assets by market capitalisation, from CoinGecko's historical price endpoint, with Coin Metrics community data as a cross-check. Aggregated closes across venues, not a single exchange's tape.

Period. The broad declines in the record from 2017 onward. Earlier declines are excluded because the alt market of that era was too small and too differently structured for a like-for-like comparison.

Method. Running-maximum drawdown on daily closing prices, computed over a common window for every asset. The peak is the highest close to date and the trough is the lowest close after that peak within the window. Recovery is measured separately on the companion page.

Limitations. Survivorship is the dominant limitation: assets that failed during a decline are absent from a current large-cap set, so the measured depths are shallower than the depths actually experienced. The asset set changes over time, so a long comparison is computed across a changing basket. Daily closes miss intraday extremes, which understates every depth. And a common window understates each asset's own worst case, which is a deliberate choice rather than an error.

Sources and references

The drawdown definition follows standard practice; the data sources are the aggregations used elsewhere on this site.

  • Historical price data. CoinGecko, CoinGecko API documentation: the daily series behind every drawdown.
  • Cross-check series. Coin Metrics, Community Network Data: independent daily reference rates.
  • Drawdown as a risk measure. Magdon-Ismail, M. and Atiya, A., "Maximum Drawdown", Risk Magazine, 2004: the formal treatment of maximum drawdown and its estimation.
  • Bitcoin's own drawdown record. Bitcoin Data Guide, Bitcoin Drawdowns and Drawdown Explained: the reference asset's peak-to-trough record and the definition used for it.

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