香港如何赢得「全球代币化中心」的竞争?

深潮Publicado a 2025-07-10Actualizado a 2025-07-10

如果成功,香港将不仅是领跑者,更将是未来金融形态的定义者之一。

编者按:《南华早报》网站 7 月 3 日刊登了 Cobo COO Lily Z. King 的文章,深入剖析香港如何在全球代币化竞争中抢占先机。文章指出,随着真实世界资产(RWA)代币化加速进入主流,香港正以清晰的监管框架、开放的市场策略和积极的政策创新,构建新一代金融基础设施。而这场竞争的下半场,关键将不再是政策导向,而是产品是否真正契合市场需求。

7 月 8 日 Lily Z.King 在香港德勤数字资产论坛

参会者有香港财经事务及库务司、证监会、立法会和金融管理局的官员和业界机构

当贝莱德董事长拉里·芬克(Larry Fink)在年度致股东信中写道:「每一只股票、每一笔债券、每一支基金——每一种资产都可以被代币化」,他并不是在预言某个遥远的变革,而是已经在发生的转变——一种正在重塑资本形成方式、资产分发机制和金融机会获取路径的演进。

这场变革的核心,是一个曾经小众、如今快速进入主流的概念:真实世界资产代币化(RWA)。如今,已有超过 240 亿美元的 RWA 在公有链上流通,涵盖了收益型美债、私募信贷池、代币化的大宗商品与房地产等。曾经被视为「加密好奇实验」的尝试,如今正在成为全球金融基础设施的一部分——资本市场的底层管道正在悄然重构。

所以问题不再是代币化会不会重塑金融,而是谁将塑造它。

在 6 月 26 日发布的《数字资产发展政策声明 2.0》中,香港表达了它想要引领的意图。

该声明推出了「Leap」监管框架,将监管范围扩大至稳定币发行方、托管方及 RWA 平台。更重要的是,它释放出一个明确信号:香港不只是「允许代币化,而是在积极倡导代币化。

「Leap」是「法律与监管简化(Legal)」、「代币化产品拓展(Expand)」、「应用场景推进(Advance)」以及「人才与合作伙伴发展(People and Partnership)」的缩写,它通过制定稳定币牌照制度、明确代币化 ETF的监管框架、延续此前在数字债券、绿色金融方面的试点,推动形成一个更广阔的愿景,鼓励从贵金属到可再生能源基础设施等各种资产的代币化。

但也许最有意义的变化,不在于政策具体监管了什么,而在于它如何定义代币化——将其视为新金融基础设施的核心支柱而非沙盒实验。仅这一点,就已让香港区别于其他市场。

相比之下,新加坡采取了更为审慎的做法——聚焦机构参与,限制零售投资者;而香港则选择了一种更广泛、更包容的路径。它在设定清晰适当性规则的前提下,允许零售用户参与,拓展了潜在市场空间。

相较于欧盟规范性的加密资产市场构架和美国碎片化的监管拉锯战,香港提供了一个更统一、以原则为基础的系统,为创新者和投资者提供了其所需的清晰度。

不过,仅仅铺好轨道,并不意味着列车就能准点运行。发行一项代币化资产很容易,难点在于有没有人愿意持有、交易并信任它。

6 月 5 日,全球最大的稳定币发行商之一 Circle Internet Group 首席执行官兼联合创始人 Jeremy Allaire(左三)和 Circle 总裁 Heath Tarbert(左二)在公司首次公开募股当天的纽约证券交易所。

照片:路透社

太多代币化项目是通过踩坑才明白这一点的:技术没问题,市场不买单。缺乏分发渠道、市场需求或实际相关性,许多产品最终只是被搁置。瓶颈不在于技术,也不在于监管,而在于商业价值是否真正存在。真正的考验是:某个代币化资产是否真的为一个明确定义的用户群体解决了问题。

当然,也有项目通过了这道考验并成功扩展。 例如,代币化的美债产品因为提供了稳定、透明的收益率,在全球储户中获得了广泛采用,尤其是在那些缺乏安全收益渠道的新兴市场。

又如,Maple Finance等协议在私募信贷领域开辟了新路径,通过撮合机构借款人和加密原生贷款方,并实现链上透明风控,使产品双向可用。

这些成功并非来自新奇的技术,而是资产、用户和包装方式三者的完美匹配。

香港本地的生态也正在朝这个方向演进。香港金融管理局的「Project Ensemble」正在实验代币化的债券、基金、碳信用、充电桩基础设施与供应链金融等场景。这些项目颇具潜力,但真正能大规模打通资产、受众和使用场景三要素的爆款项目,尚未出现。

所有要素已经就位,接下来需要的是「市场牵引力」。香港已经打下了坚实基础:监管清晰、机构认可、公私协作的可信项目正不断推进。 香港正日益被视为一个安全、结构清晰的数字资产实验环境,再加上其作为中国数字资产战略「桥头堡」的潜力,使其意义远远超出本地市场本身。

但最难的部分才刚刚开始。下一阶段的竞争,将由「产品与市场契合度」(product-market fit)决定,而非更多政策。香港能否吸引东南亚储户投资真正有收益的稳定币产品?能否通过合规的数字包装方式,把中国的产业资产连接到全球资本?能否孵化出新一代的不仅合法合规,而且真正有市场需求的 RWA 产品?

这些问题将决定 RWA 是否只是一个风口,还是能成为一个持久变革;也将决定香港是否能成为这个新时代的全球代币化之都。如果成功,香港将不仅是领跑者,更将是未来金融形态的定义者之一。

Lecturas Relacionadas

Mysterious "Ox Alpha" Large Model Goes Viral with Limited-Time Free Access

A mysterious anonymous AI model named "Ox Alpha," nicknamed "Cow is Coming" by Chinese netizens, has appeared on OpenRouter, sparking widespread speculation. The model offers a 1 million token context, supports text, image, and video inputs, can call tools, and is currently free. Its standout feature is strong coding ability. Initial tests on the DeepSWE benchmark, which evaluates real-world software engineering tasks, showed an 80% pass rate on a subset of tasks, reportedly nearing top-tier code models. However, follow-up tests yielded a 63% score, with variations attributed to different task sets and configurations. The model's true developer is a major topic of debate. The prevailing theory points to Zhipu AI's unreleased GLM-5.3 Flash or its multimodal variant. Evidence cited includes identical visual token consumption patterns with GLM-5V-Turbo for videos, a consistent offset in text token counts compared to GLM-5.3, and similar behavioral traits like refusing audio processing. Zhipu has a precedent of anonymous testing. Simultaneously, another anonymous model, "korrine," appeared on Code Arena, with guesses ranging from Moonshot's Kimi K3.1 to models from Qwen or MiMo, adding to the industry's guessing game. This trend of anonymous "undercover" testing allows for unbiased performance evaluation in platforms like Arena and provides real-world, high-pressure testing through tools like OpenRouter before official release. It also serves as an effective marketing tactic, prolonging discussion through suspense. If Ox Alpha is indeed a "Flash" model, its performance raises expectations for the full-scale version's potential.

marsbitHace 2 hora(s)

Mysterious "Ox Alpha" Large Model Goes Viral with Limited-Time Free Access

marsbitHace 2 hora(s)

Breaking News: DeepSeek Announces All-Day Off-Peak Pricing on Weekends, Making Weekend Work More Cost-Effective?

DeepSeek has announced a significant change to its API pricing model, effective August 23. The new policy removes peak/off-peak distinctions on weekends (Saturdays and Sundays), charging the lower off-peak rate for the entire two-day period. This adjustment has sparked mixed reactions within the developer and professional communities. For developers and businesses heavily reliant on DeepSeek's V4-Flash and V4-Pro APIs, this is welcome news. It allows them to schedule bulk processing tasks on weekends without the higher peak-hour costs, potentially halving their API bills for such workloads. Some users have celebrated the move for making weekend work more cost-effective. However, the announcement has also raised concerns among employees. There is apprehension that companies, particularly in cost-sensitive sectors like AI-powered short drama production, might reorganize work schedules to align with these new cost incentives. Instances are already emerging where teams schedule high-token tasks during cheaper nighttime hours or adjust staff shifts. This has led to worries about a potential shift towards weekend workdays and weekday time-off, prioritizing cost savings over traditional work-life balance. Debate has ensued regarding the practicality of such schedule changes, with questions about increased communication overhead and overall efficiency. Speculation about DeepSeek's motives for the change includes theories that peak pricing correlates with internal model training schedules, though others counter that training is largely automated. The new pricing structure is now in effect, prompting users to reconsider their task scheduling strategies.

marsbitHace 2 hora(s)

Breaking News: DeepSeek Announces All-Day Off-Peak Pricing on Weekends, Making Weekend Work More Cost-Effective?

marsbitHace 2 hora(s)

Just Now, The World's First Human vs. Robot Tennis Match Begins, Robot's Desperate Save Leaves Zheng Jie Astonished

Just now, the world's first human vs. robot tennis match began, featuring stunning robotic saves that left tennis star Zheng Jie in awe. This historic event, part of the second World Humanoid Robot Games and broadcast live globally by China Media Group, marked a pivotal moment in Chinese technological innovation and embodied artificial intelligence. The match featured both mixed human-robot doubles and a groundbreaking singles match between Zheng Jie and the "Galaxy Xingzai" humanoid robot developed by Galaxy General. The robot demonstrated impressive skills including serving, forehands, backhands, and strategic court movement, with serves exceeding 100 km/h. It exhibited remarkable adaptability, recovering from a fall to continue play and handling slices and spins. The doubles match highlighted its ability to coordinate dynamically with a human partner. The event's significance extends far beyond a novelty match. Tennis represents an ultimate pressure test for embodied AI, demanding real-time integration of perception, decision-making, full-body motion control, and live博弈 within fractions of a second—a stark contrast to the discrete, contemplative environment of board games like Go mastered by AlphaGo. It directly confronts Moravec's paradox, showcasing AI's move from digital cognition to physical execution. This capability is powered by Galaxy General's proprietary "Galaxy Star Brain" (AstraBrain) model. Its key innovation is a unified architecture that integrates high-level task understanding/tactical decision-making ("brain") and dynamic whole-body motion control ("cerebellum") into a single model, eliminating latency and information loss between separate modules. The model was trained using a two-step process via the "Galaxy Star Workshop" platform. First, it learned foundational movement priors from "imperfect" human motion data (both amateur and professional). Second, it underwent massive-scale evolution in a virtual tennis simulator where multiple AI agents played millions of games against each other. Through this adversarial training, skills like极限救球and recovery from falls emerged autonomously without explicit programming, before being transferred to the physical robot. This "AstraTennis" moment symbolizes a major leap: a decade after AlphaGo conquered the digital world, embodied AI from China has now demonstrated it can operate under the extreme, unpredictable physical pressures of real-world competition.

marsbitHace 2 hora(s)

Just Now, The World's First Human vs. Robot Tennis Match Begins, Robot's Desperate Save Leaves Zheng Jie Astonished

marsbitHace 2 hora(s)

Trading

Spot
活动图片