Bitcoin volatility stays low as profit‑making supply nears historic bear‑to‑bull level
Low volatility observed
Bitcoin’s price movement has been calm, with the cryptocurrency trading around $78,000 after briefly reaching $82,000 last week. Analysts say the market is consolidating rather than breaking out.
Key points
- Long‑term holder supply is the strongest factor explaining one‑month realized volatility, according to Glassnode.
- More than 71% of Bitcoin supply is currently in profit, close to the historical mean of 74.7% that has marked bear‑to‑bull transitions.
- Bitcoin’s market cap is less influential on volatility than who holds the coins.
- ETF inflows and stablecoin growth are adding support to the broader crypto market.
Analyst findings
Glassnode’s analysis shows that the amount of Bitcoin held by long‑term investors explains more of the month‑to‑month volatility than market cap, open interest, funding rates, or trading activity. Illiquid supply ranks second, while market cap is far down the list.
Bitfinex analysts note that the profit‑making supply figure rose from about 67% when Bitcoin traded above $82,500 in May to over 71% now. They add that crossing the 74.7% historical average has typically signaled the start of a bull market.
Supply in profit
When Bitcoin’s price exceeds a holder’s cost basis, those coins become “in profit.” The current level of 71% means a large portion of the Bitcoin supply could be sold if prices fall, creating latent sell‑side liquidity.
Market backdrop
Crypto market capitalization, excluding Bitcoin, Ether, and stablecoins, has risen by $51.2 billion since early September, reaching levels seen in mid‑August. Continued inflows into Bitcoin exchange‑traded funds (ETFs) and growth in stablecoins are also supporting the market.
Why it matters
Low volatility combined with a high share of profit‑making supply suggests the market is in a consolidation phase. If the profit‑making supply surpasses the historic 74.7% threshold, it could indicate a shift toward a bullish trend, according to past patterns.
