Bitcoin HODLing Has Never Been More Popular

CoinDeskPublished on 2023-05-24Last updated on 2023-05-24

Abstract

More BTC than ever has been held for at least a year, according to Glassnode, a potentially bullish sign.

Investors are hanging onto their bitcoin (BTC) longer than ever – HODLing in industry parlance – according to data from Glassnode.

The proportion of BTC that’s been held for at least a year has climbed to a record 68%, Glassnode data shows, while 55% of bitcoin has been held for at least two years and 40% for three years.

Many analysts consider it bullish when BTC sits dormant on grounds that investors are choosing to hold on rather than sell. The prevalence of buy-and-hold in crypto contrasts with the long-term shift in U.S. stocks, a market where investors now hold assets for dramatically less time than they used to.

BTC: supply last active 1yr + age bands (Glassnode)

Sean Farrell, head of digital assets research at FundStrat, said that being a long-term holder has tended to get more popular over time. The exception is when markets get frothy and investors who bought dips sell their older coins to eager buyers.

“The trend is bullish insofar it means that higher prices are ahead in this cycle and any reticence to sell from current HODLers could result in a mini-supply squeeze,” said Farrell.

He added that looking at long-term holder supply metrics is not necessarily useful for short-term price signals.

Long-Term-Holder Supply, which Glassnode deems as coins held for longer than 155 days, has also seen a new all-time high — reaching 14.46 million bitcoin. “This reflects coins acquired immediately after the FTX failure maturing into long term holder status,” said the report.

Bitcoin long term/short term holder threshold (Glassnode)

Glassnode’s Liveliness metric – which compares the relative balance between HODLing and spending behavior – also shows investors are hanging on. It has fallen to the lowest level since December 2020.

Related Reads

Jensen Huang: Prompts are Becoming Obsolete, Loops are the New Paradigm

Jensen Huang, alongside AI leaders like Peter Norvig, Boris Cherny, and Andrew Ng, is advocating for a shift from "prompt engineering" to "loop engineering" as the new paradigm for AI development. Instead of manually crafting individual prompts, the focus is now on designing autonomous loops—systems where AI agents execute tasks, self-validate results, and iterate until completion without constant human oversight. A loop is a management framework that enables agents to operate independently. Key implementations are seen in Claude Code (with features like /loop, /goal, and /schedule) and OpenAI Codex, which employ multiple agents working in parallel within isolated environments. A core principle is the separation of roles: one agent (or model) performs the task, while an independent agent (or a smaller, separate model) validates the output to ensure objectivity. The article outlines a practical roadmap for implementing loops, starting with a "four-condition test" to assess suitability, building a minimal viable loop, and emphasizing critical pitfalls to avoid, such as lacking hard stop conditions or allowing loops to handle tasks requiring human judgment. This evolution is framed as the fourth major shift in AI interaction: from Prompt Engineering (crafting instructions) to Context Engineering (providing background information), then to Harness Engineering (building tool-enabled environments), and finally to Loop Engineering (creating self-sustaining systems). This progression reflects a consistent trend of increasing abstraction, moving human involvement from direct instruction to system design and rule-setting. The concept has academic roots in frameworks like ReAct, which formalized the "reason-act-observe" cycle. While loop engineering promises greater automation, experts caution about managing token costs and warn against outsourcing understanding—AI can assist, but deep problem comprehension remains essential.

marsbit39m ago

Jensen Huang: Prompts are Becoming Obsolete, Loops are the New Paradigm

marsbit39m ago

GPT Designs GPT

OpenAI has unveiled its first custom AI chip, Jalapeño, a move signaling a strategic shift beyond being a mere model company. While many see it as a challenge to NVIDIA, its core aim is to control the entire intelligent production pipeline—from models and chips to data centers and energy. The key driver is the evolving competitive landscape: model advantages are shrinking, while the computational gap in areas like cost-per-token, system throughput, and energy efficiency is becoming the true long-term barrier. Jalapeño is primarily an inference chip, targeting the massive and growing "inference tax"—the daily operational cost of generating tokens for services like ChatGPT and APIs. By designing its own hardware optimized for its specific workloads and future product roadmaps (even using AI to aid the chip design process), OpenAI aims to drastically reduce token generation costs and improve system efficiency. This creates a potential flywheel: better models help design better chips, which lower costs for running next-generation models, supporting more users and products, which in turn provides more data to refine future chips. The strategy mirrors Apple’s integrated approach, building a closed loop where hardware, software, and applications are co-optimized. In the long term, OpenAI is not trying to become the next NVIDIA (a supplier of "shovels" to all AI companies) but to own and operate the entire "mine"—selling the end product of intelligence itself. This move marks OpenAI's ambition to evolve from creating the smartest models to controlling the foundational infrastructure of AI production.

marsbit1h ago

GPT Designs GPT

marsbit1h ago

Ethereum Foundation Interim Executive Director Speaks Out: What Is Our Mission?

The Ethereum Foundation's core mission is to ensure Ethereum remains a truly permissionless, censorship-resistant, private, and open infrastructure for large-scale, sovereign coordination. The article clarifies the EF's focus and dismisses irrelevant objectives, such as pursuing institutional popularity or short-term speculation. Its core work centers on eliminating systemic weaknesses. This involves fortifying Ethereum across multiple layers—protocol, access, user, and institutional—against exploitation, control, or surveillance. Key initiatives include minimizing harmful MEV and preventing privileged control over transaction flow, making unconditional privacy a foundational default, ensuring staking remains permissionless and decentralized, and strengthening user-facing access points to uphold autonomy. Concurrently, the EF aims to seize strategic opportunities. These include leading the transition to post-quantum cryptography, achieving a fully verifiable protocol stack, establishing Ethereum as private digital cash, integrating user-owned AI agents with personal wallets, and demonstrating that trusted-neutral infrastructure can competitively handle disintermediated coordination at an institutional scale. The article also addresses recent organizational changes, stating that personnel departures were due to strategic realignment, role fit, or natural evolution. It clarifies the approach to spin-outs, emphasizing that external funding will be provided only for work critical to the EF's mission that reduces Ethereum's dependency without creating new risks or mission drift. Ultimately, the EF is committed to building an enduring, neutral system that reshapes global coordination, focusing relentlessly on the principles of censorship resistance, openness, privacy, and sovereignty (CROP).

链捕手1h ago

Ethereum Foundation Interim Executive Director Speaks Out: What Is Our Mission?

链捕手1h ago

Trading

Spot
Futures
活动图片