3 historically accurate Bitcoin on-chain metrics are flashing 'bottom'

CointelegraphPublicado em 2022-10-22Última atualização em 2022-10-22

Resumo

Key Bitcoin indicators tracking its market versus fair value, as well as long-term holders' confidence, hint at a market bottom formation.

Bitcoin and other riskier assets slipped on Friday as traders scrutinized macro indicators that suggest the Federal Reserve would continue to hike rates. Nonetheless, the BTC/USD pair remains rangebound inside the $18,000-$20,000 price range, showing a strong bias conflict in the market.
""

BTC price holding above $18K since June
""

Notably, BTC's price has been unable to diver deeper below $18,000 since it first tested the support level in June 2022. As a result, some analysts believe that the cryptocurrency is bottoming out, given it has already corrected by over 70% from its record high of $69,000, established almost a year ago.

BTC/USD daily price chart. Source: TradingView

""

During the 2018 bear market, BTC saw a max drawdown from peak to trough of 84%, lasting 364 days, while the 2014 cycle lasted longer, bottoming after 407 days," noted Arcane Research in its weekly crypto market report, adding:
""

"Both bottoms were followed by unusually low volatility."

Bitcoin's historical drawdowns. Source: Arcane Research

""

In addition, a flurry of widely-watched on-chain Bitcoin indicators also hints at a potential bullish reversal ahead. Let's look at some of the most historically significant metrics. 
""

Bitcoin MVRV-Z Score
""

The MVRV-Z Score assesses Bitcoin's overbought and oversold statuses based on its market and fair value.
""

Historically, when Bitcoin's market value crosses the fair value, it indicates a market top (the red zone). Conversely, it indicates a market bottom (the green zone) when the market value crosses below the fair value.

Bitcoin MVRV Z-Score. Source: Glassnode

""

The MVRV-Z Score has been in the green zone since late June, suggesting Bitcoin is bottoming out.
""

Reserve Risk
""

Bitcoin's Reserve Risk assesses the confidence of the token's long-term holders relative to its price at the point in time. Historically, a higher Reserve Risk (the red zone) has coincided with market tops, reflecting lower investment confidence at record-high Bitcoin prices.
""

Conversely, higher confidence and lower Bitcoin price mean lower Reserve Risk (the green zone), or better risk/reward for investing.

Bitcoin Reserve Risk vs. price. Source: Glassnode

""

Bitcoin's Reserve Risk plunged into the green zone in late June, suggesting that BTC may undergo a strong bullish reversal sooner or later.
""

Bitcoin Puell Multiple
""

The Puell Multiple reflects the ratio of the daily Bitcoin issuance (in U.S. dollars) and the 365-day moving average of daily issuance value.

""

Historical data shows Bitcoin market bottoming out when the Puell Multiple drops into the green zone defined by the 0.3-0.5 range. Conversely, the market peaks out when the ratio crosses into the 4-8 red zone.

Bitcoin Puell Multiple vs. price. Source: Glassnode

""

As of October, Bitcoin's Puell Multiple is inside the green zone, suggesting a potential price reversal ahead to the upside.
""

As Cointelegraph reported, the BTC balance on cryptocurrency exchanges has also fallen to multi-year lows at the fastest pace since June, suggesting that current price levels are becoming an important area of accumulation. 

Leituras Relacionadas

The Real Battlefield of AI Lies in the 'Dark Forest'

The article "AI's Real Battlefield is in the 'Dark Forest'" discusses the shifting dynamics in the global AI landscape, contrasting the strategic directions of Chinese and U.S. AI developers. Chinese companies like Alibaba (with its "HappyHorse" video model), ByteDance (Seedance 2.0), and Kuaishou (Kling 3.0) have taken the lead in text-to-video generation, surpassing OpenAI’s now-discontinued Sora. These models are deeply integrated into their parent companies’ content ecosystems (e.g., Douyin, Kuaishou), serving to reduce content creation costs and enhance user engagement rather than operating as standalone profit centers. In contrast, U.S. firms are pivoting toward high-stakes enterprise and security applications. Anthropic’s Claude Mythos model demonstrates advanced capabilities in autonomously discovering and exploiting software vulnerabilities, prompting concern at the highest levels of U.S. financial and governmental institutions. OpenAI responded with its own GPT-5.4-Cyber, signaling a strategic shift from consumer-facing products to enterprise-grade tools focused on cybersecurity and programming. The divergence is attributed to fundamental differences in resources and market structures. U.S. companies, backed by vast computational resources (e.g., Amazon and Google supply Anthropic with substantial funding and TPU access), can pursue deep, specialized R&D in high-value B2B sectors. Chinese firms, facing significant compute power constraints and a less mature enterprise SaaS market, have found success by leveraging their massive consumer platforms and optimizing for cost-efficiency. The article warns that the AI race is entering a "dark forest" phase—a reference to competitive dynamics where cybersecurity capabilities could determine digital sovereignty. While Chinese models like Zhipu AI’s GLM-5.1 show promise in narrowing the gap in coding proficiency, the author stresses that achieving parity in security-critical AI will require asymmetric strategies, including greater investment in coding models, adaptation to domestic hardware, and exploring international markets in the Global South.

marsbitHá 1h

The Real Battlefield of AI Lies in the 'Dark Forest'

marsbitHá 1h

Trading

Spot
Futuros
活动图片