比特币现货 ETF 启航,管理它们的基金经理会面临哪些挑战?

foresightnewsPublicado a 2024-01-15Actualizado a 2024-01-16

Resumen

管理比特币基金会带来了传统基金不必面对的挑战和复杂性。

管理比特币基金会带来了传统基金不必面对的挑战和复杂性。


撰文:Daniel Truque

编译:Luffy,Foresight News


 FTX 崩盘后,轻蔑的批评者嘲笑 Caroline Ellison 的止损方法。 「我只是认为它们不是有效的风险管理工具,」她在 FTX 的鼎盛时期对公众如是说。但她说得有道理吗?


加密资产管理领域带来了一系列与传统基金领域截然不同的挑战。在这篇入门文章中,我们将深入探讨有抱负的基金经理在推出比特币行业基金时面临的问题,并研究当你走出传统资产管理世界时存在的主要差异。


波动性和风险管理


比特币行业基金面临的最重大挑战之一是加密货币市场中存在的极端波动。比特币的价格出现了强劲的看涨势头,引起了投资者的兴奋。然而,它也经历了崩盘式下跌,导致那些对这种价格波动毫无准备的人遭受重大损失。在如此动荡的环境中管理风险需要复杂的策略、严格的风险框架以及对市场趋势的深刻理解。



与大多数传统和主流蓝筹资产通常经历相对稳定的价格变动不同,比特币的价格可以在几个小时内发生大幅的变动。因此,比特币行业的基金经理必须做好充分准备来应对突然的价格波动,以保护投资者的利益。传统的止损结构可能无法达到预期的效果,因为订单簿滑点和价格快速变动导致收盘市价订单可能会以远低于预设触发价的价格执行,即所谓的「接落刀」。使用严格的止损作为基本的风险管理机制也可能会让你血本无归。例如,在闪电崩盘的情况下,即使市场在几分钟(或几秒钟)后恢复,头寸也可能会自动亏本出售。


虽然止损是一种替代方案,更好的选择是期权。期权是你可以购买的合约,它赋予你在给定时间(即到期日)以预定价格(即执行价格)买卖给定资产的权利。购买资产的期权是看涨期权,出售资产的期权是看跌期权。购买看跌期权(即远低于当前价格)可以在价格暴跌时作为挽回损失的保障。期权费将其视为为确保你的仓位而支付的溢价。


有时,为了抵御二元结果事件或特别高波动性的时间框架,你只需平仓并且不承担任何风险,等待比特币市场的下一次机会。例如,关键协议更新日期、监管决策或下一次比特币减半,但请注意市场在这些事件之前发生变化,因此你可能必须提前采取行动。


为比特币行业基金制定有效的风险管理计划可能涉及使用各种对冲技术、产品和工具(可能跨资产类别)、交易场所风险评分和风险调整分配、动态交易规模、动态杠杆设置以及采用稳健的工具监测市场情绪、潜在市场和运营风险。


保管和安全


比特币和其他加密货币的托管是比特币行业基金与传统同行区别的一个关键方面。与传统交易所仅撮合订单不同,比特币交易所负责订单撮合、保证金、结算和资产托管。交易所本身成为清算所,集中而不是减轻交易对手风险。去中心化交易所也带来了一系列独特的风险,从抵御矿工提取的价值到防止黑客攻击。


出于这些原因,保护数字资产免遭盗窃或黑客攻击需要强大的安全措施,包括但不限于多重签名协议、冷存储解决方案和风险监控工具。安全管理私钥以及选择和监控可靠交易所的责任完全由基金经理承担。监控市场基础设施本身的负担带来了传统基金管理中所没有的技术复杂性,在传统基金管理中,托管和结算是标准化和商品化的独立系统。



必须仔细选择比特币行业基金的托管解决方案,确保资产免受网络攻击和内部威胁。由于加密货币交易所遭受黑客攻击的事件备受瞩目,投资者尤其担心其资产的安全,任何安全漏洞都可能导致重大财务损失并损害基金的声誉。


结论


推出比特币行业基金是一项令人兴奋的努力,为寻求进入快速增长的加密货币市场的投资者提供了前所未有的机会。然而,重要的是要明白,推出基金并不是一件容易的事,除了交易策略的成功之外,还存在一些陷阱。每个季度关闭的基金都可能与发行的基金数量相同,这一点并不让人惊讶。



那些进入比特币行业基金领域的人应该以开拓精神接触它,保持信息灵通,并拥抱这个令人兴奋的新兴市场的波动性本质。尽管道路可能充满挑战,但成功的比特币行业基金经理的潜在回报可能是天文数字。

Lecturas Relacionadas

My Coding Betting Dashboard is Profiting, but Polymarket is Truly Not a Good Place for 'Arbitrage'

The author built a custom monitoring dashboard for Polymarket, a prediction market platform, and tested it with $1,600, achieving over 30% returns. However, the core argument is that Polymarket is not a good venue for traditional arbitrage. The dashboard has two main sections: a "Portfolio Dashboard" for tracking active positions with key metrics like total capital, P&L, and a risk-control module using a tier system (T1, T2, T3), and an "Opportunity Watchlist" for monitoring markets. The article details a critical structural trap in binary markets: a bet with a high perceived probability of success still carries a 100% loss risk if wrong. The author's T1/T2/T3 system is designed to manage this by limiting position sizes based on conviction and time horizon, emphasizing that high confidence should not equal high concentration. A key insight is the danger of "pseudo-diversification"—betting on different markets driven by the same underlying variable. The author concludes that Polymarket offers few true low-risk, arbitrage opportunities. It is instead a high-risk environment where wins can create a false sense of mastery, leading to large losses. The platform is better viewed as a training ground for honing judgment through disciplined, framework-driven betting rather than a reliable income source. The tools help transform intuition into structured, rule-based decisions to mitigate the risk of catastrophic errors.

marsbitHace 2 hora(s)

My Coding Betting Dashboard is Profiting, but Polymarket is Truly Not a Good Place for 'Arbitrage'

marsbitHace 2 hora(s)

WeChat AI Card Hands-On Guide: Has the AI Shopping Era Arrived?

**"WeChat AI Card" Practical Test Guide: Has the Era of AI Shopping Arrived?** WeChat has officially launched the "AI Exclusive Card," a feature integrated into its Workbuddy AI assistant. This card is designed to handle payments for AI-initiated purchases. Our hands-on test reveals it's not yet a tool for fully autonomous AI shopping, but rather a controlled payment layer for AI agents. The AI Card functions as an isolated sub-wallet within WeChat Pay. Users must bind the card and transfer funds into it from their main wallet. Crucially, every transaction requires explicit user confirmation via smartphone scan; AI cannot spend autonomously. Currently accessible through the Workbuddy agent, the card targets specific digital consumption scenarios: purchasing paid content (reports, data), calling paid APIs/tools, and subscribing to services. Its design prioritizes security and control by separating funds and mandating approval for each payment. We tested a real-world scenario: ordering bubble tea via Workbuddy using a "Meituan Life Assistant" skill. The process encountered multiple hurdles: high "skill" usage costs (exceeding daily free credits), and most importantly, while a payment was successfully initiated, the AI purchased an incorrect product (a mismatched group-buy coupon instead of the desired drink). This highlights the current limitation: the **AI Card only solves the payment step**. The broader challenge lies in the **AI agent's execution chain**—accurately understanding intent, navigating third-party platforms, selecting the right product, and ensuring proper fulfillment. The payment succeeded, but the purchase failed to meet the user's need. In conclusion, the WeChat AI Exclusive Card is a cautious, early-step experiment in AI commerce. It provides a secure, user-controlled payment method for agent interactions but is not yet capable of reliable, end-to-end complex purchases. For now, it's best used for low-value, low-risk digital services with careful user verification at each step. The vision of AI handling complete shopping tasks remains a work in progress.

marsbitHace 4 hora(s)

WeChat AI Card Hands-On Guide: Has the AI Shopping Era Arrived?

marsbitHace 4 hora(s)

Deconstructing Notion's Growth: From a Note-taking Tool to 100 Million Users—How Notion Built a Triple Growth Flywheel Through Product, Templates, and Community

Notion's growth from a niche note-taking tool to a platform with 100 million users is powered by three interconnected flywheels: Product-Led Growth (PLG), a Template Economy, and Community-Driven Growth. First, Notion's PLG strategy relies on a highly flexible, "plastic" product that users can adapt to countless personal and team workflows. Its freemium model lowers the barrier to entry, while features like page sharing and collaboration drive organic, usage-based viral growth as users naturally invite others. Second, the Template Economy solves the "blank page" problem. Templates, created by both Notion and its community, transform abstract product capabilities into concrete, copyable solutions for specific scenarios (e.g., project management, content calendars). This dramatically lowers activation costs for new users and fuels SEO-driven discovery. Third, a vibrant Community acts as a distributed growth engine. Users and official Ambassadors create tutorials, share use cases, and host local events. This community not only educates users but also fosters a sense of identity around pursuing "better ways of working," strengthening loyalty and enabling global, low-cost expansion. Together, these flywheels create a self-reinforcing ecosystem: a great product attracts users who create templates and community content, which in turn attracts more users and deepens engagement. This system allowed Notion to scale from individuals to teams and enterprises through a bottom-up adoption path. Looking ahead, AI integration promises to accelerate these flywheels further by making templates smarter and the platform a potential AI-native work operating system. Ultimately, Notion's defensible advantage is not just its features, but this deeply entrenched network of user assets, creators, and community trust.

marsbitHace 4 hora(s)

Deconstructing Notion's Growth: From a Note-taking Tool to 100 Million Users—How Notion Built a Triple Growth Flywheel Through Product, Templates, and Community

marsbitHace 4 hora(s)

$10 Billion, Qualcomm to Acquire Chip Legend Jim Keller's Company

Global mobile chip giant Qualcomm is in advanced talks to acquire AI chip startup Tenstorrent in a deal valued between $8-10 billion, according to media reports. This potential acquisition would be one of the largest in the AI chip sector in recent years. Tenstorrent, led by legendary chip architect Jim Keller, has gained prominence for its RISC-V architecture and AI accelerator designs. The move highlights Qualcomm's strategic push to diversify beyond its core smartphone chip business. As the smartphone market matures, Qualcomm is aggressively targeting growth in automotive, data center, and cloud AI. Acquiring Tenstorrent would allow Qualcomm to rapidly enter the high-end AI computing market, bypassing lengthy in-house development cycles. Tenstorrent's cost-effective system architecture, which avoids expensive HBM memory and relies on standard Ethernet for clustering, offers a potential alternative to Nvidia's costly solutions. Furthermore, Tenstorrent's high-performance RISC-V CPU technology and its focus on the automotive and edge computing segments align with Qualcomm's strategic goals, including its "Snapdragon Digital Chassis" platform. Despite the strategic rationale, the high valuation has sparked some investor caution. The successful integration of Tenstorrent's open-source culture and independent team into Qualcomm's organization, along with the commercialization of its technology, remains a key challenge.

marsbitHace 5 hora(s)

$10 Billion, Qualcomm to Acquire Chip Legend Jim Keller's Company

marsbitHace 5 hora(s)

Trading

Spot
Futuros
活动图片