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Not Your Fault for Not Understanding the Market: Traditional Crypto Indicators Are Failing

The article "When Old Maps No Longer Apply: 8 Failed Classic Crypto Indicators and Their Structural Causes" examines why traditional metrics used to predict cryptocurrency market behavior have become unreliable. Key indicators like the four-year cycle theory (halving events), Pi Cycle Top, MVRV Z-Score, Rainbow Chart, Altcoin Season Index, Fear and Greed Index, NVT Ratio, and Stock-to-Flow (S2F) model have all underperformed or failed entirely in the 2024-2025 market cycle. The author attributes this collective failure to deep structural shifts in the crypto market: - **Institutionalization**: The influx of institutional capital via ETFs and corporate treasuries has created steady demand, smoothing out the volatile, retail-driven price swings these indicators relied on. - **Reduced Volatility**: Lower volatility means indicators depending on extreme price movements (e.g., Pi Cycle Top, Rainbow Chart) no longer trigger. - **Shift in Asset Class**: Bitcoin is increasingly influenced by macro factors (e.g., Fed policy, global liquidity) rather than on-chain events like halvings. - **Data Relevance**: On-chain data (e.g., for NVT, MVRV) is less representative due to Layer 2 solutions, internal exchange settlements, and ETF custody models. - **Scalability Issues**: As Bitcoin's market cap grew, fixed thresholds (e.g., MVRV Z-Score >7) became mathematically harder to hit. The conclusion is that these indicators were built on limited historical data and assumptions that no longer hold. Investors are advised to understand the limitations of these tools and adapt to a new market reality driven by institutional dynamics and macroeconomics.

比推02/19 06:50

Not Your Fault for Not Understanding the Market: Traditional Crypto Indicators Are Failing

比推02/19 06:50

Dragonfly: Crypto Was Not Made for Humans

Crypto Was Not Made for Humans: A Summary Dragonfly Capital partner Haseeb Qureshi argues that cryptocurrency was not designed for human use, but rather for AI agents. Despite being a crypto-native firm, Dragonfly still relies on legal contracts over smart contracts for investments, highlighting that traditional systems are built for human fallibility—featuring safeguards, reversibility, and intuitive interfaces that crypto lacks. Crypto, with its rigid, deterministic, and code-based nature, is error-prone for humans, leading to fears around transactions, phishing, and irreversible mistakes. However, these very traits make it ideal for AI. AI agents can perfectly verify transactions, audit contracts, and operate within crypto’s 24/7, borderless, and self-sovereign environment. They prefer code over ambiguous legal systems, which are slow and unpredictable. Qureshi envisions a future of "self-driving" wallets where AI agents handle all financial interactions, navigating DeFi protocols on behalf of users. These agents will also transact with each other autonomously, forming an economy of non-human participants—a reality already emerging with projects like Moltbook and Conway Research. In conclusion, crypto’s perceived flaws are not shortcomings but indications that humans are not the intended users. Within a decade, direct human interaction with crypto may seem archaic, as AI agents become the primary interface, unlocking the technology’s full potential.

marsbit02/19 05:14

Dragonfly: Crypto Was Not Made for Humans

marsbit02/19 05:14

After Raising $650 Million, Dragonfly Believes Crypto Was Not Made for Humans

Dragonfly Capital partner Haseeb Qureshi argues that cryptocurrency was not designed for humans but is instead the ideal financial system for AI agents. Despite being a crypto-native firm, Dragonfly still relies on legal contracts over smart contracts for investments, highlighting that traditional systems are built for human fallibility—featuring safeguards, reversibility, and intuitive interfaces. Crypto, by contrast, is rigid, error-prone, and unforgiving, with complex addresses, gas fees, and irreversible transactions posing significant risks to human users. Qureshi posits that AI agents are the natural users of crypto: they operate with precision, trust code over ambiguous legal systems, and can verify transactions instantly. Unlike humans, AI can navigate crypto ecosystem autonomously, negotiating and executing binding agreements via smart contracts within minutes. Crypto’s global, permissionless, and deterministic nature makes it perfect for AI-to-AI economic activity, which is already emerging with projects like Moltbook and Conway Research’s autonomous agents. He predicts the future interface for crypto will be “self-driving” wallets managed by AI, which will handle financial tasks on behalf of users. This shift will transform how protocols compete and market themselves. In a decade, humans may look back in astonishment that they ever interacted directly with crypto—its true potential unlocked only when its complementary technology, AI, arrived.

Odaily星球日报02/19 05:10

After Raising $650 Million, Dragonfly Believes Crypto Was Not Made for Humans

Odaily星球日报02/19 05:10

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