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Bitcoin Price May Be Near Bottom as Bear Cross Approaches

Close-up of a digital Bitcoin price chart on a monitor with candlesticks and glowing lines in a dim trading room, solo trader in background,

Bitcoin may be nearing the end of its bear market, according to a technical signal that has accurately marked the bottom of each of the cryptocurrency’s three prior multi-year drawdowns.

The signal, known as a bear cross, occurs when Bitcoin’s 50-week simple moving average falls below its 100-week average. At current prices near $62,400, the cross is expected to trigger within the next week if trajectories hold. Historically, the moment the cross officially prints has coincided with the exhaustion of selling pressure and the start of fresh multi-year rallies.

“By the time these bear crosses finally occur, the market froth is usually gone, short-term speculators have exited, and capitulation has already taken place,” analysts noted in a recent report. Bitcoin has fallen roughly 50 percent from its October 2025 high above $126,000 to the current range near $60,000, reducing participation from momentum traders and speculative buyers who entered near the peak.

The signal is far from a guarantee. Critics point out that only three prior instances exist, a sample too small to confirm universal reliability. Deutsche Bank has attributed Bitcoin’s recent slide to a combination of Federal Reserve policy, outflows from spot bitcoin exchange-traded funds, and broader selloffs in AI-related technology stocks.

Other analysts cautioned that Bitcoin may need to fall another 15 percent or more to confirm a definitive bottom. The market is also facing uncertainty around crypto regulation, including the Senate’s progress on the Clarity Act and an SEC delay on tokenized-stock products.

For now, the approaching cross offers a rare moment of technical optimism in an otherwise turbulent market. Whether it translates into a sustained rebound will depend as much on U.S. monetary policy and institutional ETF flows as it does on historical pattern recognition.

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