Some thoughts on market makers, transparency & the @Forgd_ leaderboard: Yesterday, a ranking of crypto market makers made the rounds on X and generated a lot of debate. For context, the ranking was copy + pasted directly from a leaderboard built by @Forgd_, hosted on @DefiLlama & @Tokenomist_ai. Importantly, this leaderboard benchmarks market makers engaged by blockchain projects to support liquidity for their native tokens – not prop trading firms deploying their own balance sheets. It grades MMs based on a combination of: → Historical trade activity → KPI adherence → Venue coverage & treasury management capabilities → Size of client base It’s also only one of several leaderboards we publish. You can separately see which desks historically provide the deepest liquidity, generate the most maker volume, maintain the tightest spreads, and demonstrate the strongest uptime. Is the methodology perfect? Absolutely not. But there are far too many people in crypto claiming to have alpha on “who the best market makers are” based almost entirely on gut instinct and anecdotal evidence. After spending more than a decade in crypto (including time working at CEXs & market makers myself) I’ve probably been asked “Who are the best MMs?” hundreds of times. I wanted to take a shot at answering that question with actual data. So, some context on why we built these tools, how the data works, what the leaderboard does and does NOT tell you, and where I think we can improve 👇 1. Why we built it One thing worth acknowledging: Forgd wasn’t the first company to recognize this problem. Before we launched, other firms were already helping projects connect with market makers, structure deals, and better understand how their liquidity providers were performing. I think they deserve credit for helping validate an important thesis: market making was an enormous black box for most token issuers. Where we wanted to take a different approach was accessibility. We didn’t think projects should need to pay large advisory fees or recurring SaaS subscriptions simply to understand whether their market maker was doing its job. So we built self-service tools that projects can use completely free of charge to: → Monitor market maker performance → Run competitive MM RFQs → Compare proposals → Benchmark historical MM performance → Make more informed decisions Our belief was pretty simple: GTM infrastructure should be broadly accessible. Today, hundreds of projects across virtually every sector and stage use Forgd’s infrastructure. Some projects like @zama, @MeteoraAG and @metaplex have taken that a step further by making their market maker performance & engagement structures publicly transparent through products like “Universal Token Ratings”. We think that’s a good thing. The more transparency projects are willing to provide around how their market makers trade, where they provide liquidity, and how engagements are structured, the better informed the entire industry becomes. And because the tools are free, adoption has given us something extremely valuable: sample size. Since launching in Q4 2024, we’ve tracked nearly 600 market maker engagements across 30+ market makers, creating what we believe is one of the largest structured datasets for understanding how crypto market makers actually perform across real engagements. 2. How does the methodology actually work? TL;DR: i. Projects use Forgd to monitor their market makers. For every integrated engagement, the market maker transmits trading activity to Forgd through a standardized API integration. ii. Through these integrations, we capture things like maker fill volume, liquidity depth, spreads, KPI adherence and other engagement-specific data on a per-project, per-exchange and per-trading-pair basis. iii. Separately, Forgd independently consumes market-wide data directly from exchanges and on-chain infrastructure. That means we can observe not only what the market maker says it did, but what was happening across the broader market. put simply... → The API tells us what the market maker did. → Our independent market infrastructure tells us what the broader market looked like. We can then calculate things like the MM’s share of total maker volume or total order book depth and evaluate its activity in the context of the entire market rather than looking at an isolated number. We aggregate those observations at the project level and then across each market maker’s engagements to understand how that desk performs on average for the projects we monitor. That allows us to compare things like: → Average depth of liquidity → Average maker / taker fill volume → Average spreads → KPI adherence / uptime → Engagement structures → Average loan sizes → Loan + option vs. retainer + working capital usage → Other commercial considerations If you want to nerd out on the actual methodology, including examples of how raw data is transformed into project-level and MM-level observations, we published the full documentation here: Some people will like the methodology. Some will hate it. That’s totally fine! I’d much rather publish the methodology, expose it to criticism, and continuously improve it than pretend we’ve somehow solved market maker benchmarking forever! 3. There are also important limitations. Our dataset is large, but it is not comprehensive. Forgd has tracked nearly 600 market maker engagements since launching, but we obviously don’t capture every token project or every market maker in crypto. Our software is free to use by design. We wanted to democratize access to tools that let projects monitor their market makers, understand how they’re trading, and make better-informed decisions without putting that infrastructure behind a paywall. That model has given us a very robust sample size, but we can’t force every project to use it. The same applies to market makers. Desks like @wintermute_t, @CumberlandSays, @jump_ , and @FalconXGlobal aren’t currently included because they aren’t integrated with our platform. Does that mean they’re bad market makers? Or that they’re “hiding something”? Absolutely not. My experiences with these desks throughout my career has been extremely positive, and I think they can be fantastic partners for projects launching tokens. Integration takes engineering resources, and these firms have their own development priorities. Hopefully we can convince more of them to integrate over time and make the dataset even stronger. On the flip side, I want to give credit to desks like @flowdesk_co, @GSR_io, @ambergroup_io, @SeliniCapital, @keyrock, @jpegtrading, @tophash and others that have invested time integrating with Forgd and working with our team to improve the infrastructure. Longer term, I think transparency around token liquidity is only going to become more important. I’d love to see a world where projects proactively disclose who their market makers are, how those engagements are structured, and (retroactively, T + 1) how those desks actually traded across different venues. That kind of transparency would give the investing public much better visibility into a token’s market structure, including the ability to distinguish organic liquidity and volume from liquidity and volume being subsidized through formal market maker engagements. We’re obviously not there yet. But the more projects & MMs that participate in initiatives like Universal Token Ratings ( & Token Transparency Framework by @Blockworks / @JasonYanowitz, the more complete the picture becomes. Our goal is to build the free infrastructure that makes providing that transparency as easy as possible. 4. A note on competition I’ve seen plenty of criticism and debate around the methodology. That’s okay. In fact, I think it’s healthy. We’re always looking for ways to improve the methodology, and thoughtful criticism helps us do that. More broadly, competition is one of the healthiest forces in any industry. It forces everyone to build better products, serve customers better and continuously raise the standard. Web3 market infrastructure should be no different. In fact, some of the companies we now compete with helped validate the original problem we set out to solve. They demonstrated that projects wanted better ways to select market makers, structure engagements and understand performance. We simply had a different thesis around how those products should be delivered. Most notably, that critical infrastructure like MM monitoring and RFQs shouldn’t be locked behind SaaS paywalls or expensive advisory engagements. And I don’t think any of this needs to be zero-sum. There is plenty of room for multiple companies to build great products in the same category. Personally, I’d rather spend our time shipping better software than publicly tearing down other builders. If another platform develops a better methodology, feature, dataset or product, that should motivate us to improve ours. That’s how competition is supposed to work. And we’re building well beyond market maker analytics. MM monitoring and RFQs are only one part of Forgd. We’ve expanded the platform into tokenomics and protocol design, exchange listing intelligence, token unlock tracking, market structure analytics and novel institutional-grade research. These problems are interconnected, and we ultimately think better data leads to better decisions throughout a token’s lifecycle. 5. I’ll end with a question. What actually makes someone the “best” market maker? - Is it the desk that consistently provides the most depth? - The most maker volume? - The tightest spreads? - The strongest contractual KPI adherence? - The best treasury management capabilities? - The broadest exchange coverage? - The projects with the best post-TGE price performance? - Something else entirely? @mdudas and anyone else who spends time thinking about market structure — I’d genuinely love to hear how you’d approach it. cc @hosseeb @BrianInCrypto @ahboyash Our leaderboard will continue to evolve as the dataset grows and we get better feedback. The goal isn’t to declare that we’ve created the definitive answer to “Who is the best market maker?” The goal is to take one of the biggest black boxes in crypto and make it a little more transparent, measurable and data-driven. We’ll keep publishing the methodology, listening to constructive criticism, improving the product, and letting the data speak for itself.

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NEW: @Uniswap'S AGGREGATOR HOOKS GO LIVE ON @ethereum, @base AND @RobinhoodCrypto CHAIN WITH @0xfluid, @CurveFinance AND @PancakeSwap AMONG THE EXTERNAL LIQUIDITY SOURCES AVAILABLE AT LAUNCH

上周和 @Plus_Ultra_715 聊了一个多小时 很久没见到这样有激情的 Founder 了 会不由自主想要写一些东西分享出来 聊之前会觉得只是另一个 Gacha 平台 聊之后觉得实际在做卡牌的基础设施 过几天再回味，觉得是重构卡牌生意的经济关系 今天下笔又觉得是聚合卡牌供给，去创造大流动性 大部分人可能只停留在第二个层面 但只有看到了三和四，才能更深刻回过头去理解一和二 一些自问自答和碎碎念 论证 @renaissxyz 模式的商业逻辑 👇 --------------------- 1、卡牌是个周转生意，但被困在各个闭环里 卡牌的渠道分线下和线上。 由于自带的社交与收藏属性，即便是在互联网发达的今天，绝大多数卡牌仍是通过线下分销出去的。卡店/道馆进货、卖货（以IP原厂的密封卡包为主），为用户提供拆卡、对战、交易的场所，并可能对部分卡提供折扣回收服务，就构成了最初的卡牌一级市场和二级市场。 eBay出现后，借助其标准化的搜索、成交体系以及线上的流量，卡牌二手交易开始发生在互联网，不再受限于本地卡店。后来，eBay 收购了另一家卡牌线上交易平台TCGplayer（卡店上网卖货的主通道），深度绑定 PSA，成交量上了一个台阶，成为二级市场主力，大量卡店也开始把回收回来的货搬到 eBay 上卖。 再后来，Gacha 平台出现。和卡店大部分卖原厂卡包不同，Gacha 专做有明确市价、已评级的单卡，他们把二级市场上收来的卡，二次打包成精品盲盒，再硬性捆绑一个高比例的即时回购，售卖给那些追求多巴胺刺激的用户。而这套即时回购机制，也把卡的周转率一下子拉了起来，同一批卡，抽走、回购、再抽，再回购，每一次Gacha平台都赚一道，直到卡的库存成本被摊到趋近于零，比卡店那种一锤子买卖暴利得多。 然而这三种流转渠道其实是各自的闭环，并不完全互通。例如你拿一张卡，在 eBay 上挂着卖，这张卡能不能同时在 Gacha 平台的盲盒池里被抽？不能。它在 eBay 体系里，eBay 不知道也不在乎链上发生了什么。反过来，一张卡在 Gacha 平台被抽走、换了主人，eBay / PSA Vault那边也压根不会反映，它还可能挂在那儿出售。 以及还有大量的卡，其实并没有动起来，他们大多要么躺在收藏用户的抽屉里，或者被存储在一些诸如PSA的金库之中。相当于，大部分卡和货，目前飘在这些地方： - 线上eBay体系 - 线下卡店网络 - Gacha平台 - 收藏群体自持 - 金库存储 看似各类基础设施都很完善，但实际上，并没有一张网把它们全部串联起来。这为后面基建的重构，埋下了伏笔。 --------------------- 2、卡店 VS Gacha平台：亦敌亦友 有货才有钱赚，周转速度决定利润。 除去 eBay 这种不持有货源、只负责撮合的二手交易市场，另外两大流转源：卡店和Gacha平台，其业务的扩张都是依赖真金白银囤货的，边际成本不为零，所以对他们来说，如何提高周转效率，以及如何低成本获取货源，就是他们业务模型中最核心的变量。 而在我看来，两者亦敌亦友的点正好在于： Gacha 平台拥有最好的周转模型，但往往被货源数量给限制了业务规模，卡店并不缺卡和卡源，但并没有Gacha运营基因，周转速度上不去，长短板正好相反。 Gacha的货源需要自己去外面二级市场收，赚的钱大部分逃不开库存的再投入，甚至需要融资来填，这跟 AI 大模型公司必须不断屯更多算力和 GPU、才能服务更多推理需求，其实是同一个道理。 而卡店手里攥着大量收藏群体和社群流量，天生就能接触到各种流通的卡。用户开了一级卡包之后，那些不想要的卡，很多也会折价卖给卡店，重新变成卡店的库存，但这部分库存，卡店并没有一条像 Gacha 那样高效率的周转消化通道，大多还是积着，或者自己去 eBay 上卖掉。 那有没有可能，干脆让他俩搭伙， 卡店出货，Gacha 出周转，各取所需？ 道理是这个道理。大方向上也符合我们之前所说的打通各个流转闭环趋势。但毕竟也是半个竞争对手，要协作，还得依赖一层双方都能信任的中介。 --------------------- 3、金库或卡店的POS系统，可以是这个信任中介么？ 卡店和 Gacha 要协作，或者往大了说，各个流转渠道之间要互通所依赖的信任，其本质是： 货源的状态同步。 卡店、Gacha、交易市场、收藏群体，大家共享同一批货，那么谁手里有什么、哪张被抽走了、哪张卖掉了，就必须有一个所有人都认、且实时更新的统一账本。 那现成的，有没有可以扛起这个重担的玩家呢？ 候选无非两个：金库，或者，卡店的 POS 系统。 先说金库。 大部分金库其实只管存，根本不管同步和查询。比如 Brink's，全球最大的金库安保公司，它本来就是服务黄金、艺术品这类几乎不周转、不流动的昂贵资产的。卡牌这种经常换手的东西，根本不是它的理想客户，还贵。那便宜、对卡牌友好的呢？比如 PSA Vault，但它对外开放的可验证信息少，比如只能看到一个认证编号对应的卡的在库状态，至于持有人是谁，经手过谁，是查不到的。 本身是出于隐私保护，但也催生了一个鸡贼的空间：一个 Gacha 平台完全可以声称自己拥有这张卡然后拿来给人抽，反正纯粹的外部人员没法通过官方渠道查到持有人和这个 Gacha 平台的对应关系。某种程度上，这也是为什么 PSA Vault 会和 eBay 体系闭环绑定这么深，所有权和流转，只在 eBay 这个闭环内相对保真，一旦卡跑到它控制不了的外部渠道，例如卡店、Gacha 等去换手，就没法核实和背书了，更不用说状态同步了。 再说 POS系统。 它至少是会同步卡牌状态的，这是它的本职。POS（Point of Sale）就是那个零售店常用的收银系统，卡牌店的POS系统会更复杂一些，因为卡牌 SKU 比较多，而且单卡价格是波动的，因此需要依靠一套专门的POS来负责扫码入库、自动定价、管理回收，再把库存同步到线上各个渠道去卖，主流的是 BinderPOS、SortSwift 这类。 BinderPOS 能把库存推到 Shopify、eBay；SortSwift也是类似，Shopify、eBay、Square、CardTrader，全是 Web2 市场。它本质上只是个传统多渠道零售的同步器，压根没覆盖链上、Gacha 这种快速增长的新场景。 看到这里，你会和我有同样的释然么？ 一开始我也觉得，卡牌的传统基建似乎已经很完善了，评级、托管、交易、数据，一应俱全，再去做一遍，是不是重复造轮子？可是你看到了其实他们压根是如此老旧，既没法覆盖快速增长的新场景，也根本谈不上透明、可验证，就知道这里面空间和痛点太大。 就应该被重构。 --------------------- 4、Renaiss 改变了产业链上玩家的经济关系 很多人看到 Renaiss 要做一堆事情，会觉得它摊子铺得太大，但其实核心都是围绕打通原先各自为战的流转闭环来做的。把分散在各处的货源打通，聚成一个 Universal 的流动性池，为上层经济/金融活动构建基础。 并且不止卡店，Renaiss 还顺手把原先基本不参与这门生意的持卡个人，以及他们存卡的金库，一起拉进来了。原本那些卡一直躺在家里和金库抽屉里，只用作收藏和升值目的，现在也可以成为这个存货周转游戏的一环。 为此，Renaiss 做了 2 件事情： - 把卡店、金库拉进来的，可验证的托管/库存同步系统 - 让供货有利可图的寄售分成经济体系 Renaiss的托管，500 美金以下的低价卡，走卡店签名托管；500美元以上的高价卡，进专业金库；再叠一层谁都能查的第三方验证，信息包含物理位置，存储在谁手上，以及各种流转信息。便宜、换手快的卡，塞进专业金库不划算，让卡店就近周转；贵的、不常动的，进金库。 而寄售模式某种程度上其实也是对卡牌业务扩展性问题的一个回答。原本卡店和 Gacha 自己囤货，边际成本不为零，而寄售则是把库存的来源，从自己垫钱投入变成靠外部贡献，扩张不再受限于资本，而获得这些卡源的成本，是每个月给寄售用户的收入分成（来自Gacha或其他上层经济活动），边际成本大幅降低。 这其实是一种以“租”代“买”的业务模式、经济关系变革。 而这套模式，对参与的多方，这都是划算的： 例如卡店、金库在这个模式之中，本质上是等于多开了一条线上的业务收入来源，每次抽卡或者上层经济活动发生，他们也都能分到收入，不用额外投入资金，也不用承担自己去做一个 Gacha 平台的获客和运营成本，只需要接入这套系统，加入这个游戏即可。 而对于广大的收藏群体用户，他们手里的卡也能周转起来，从单纯的持有等升值变成一个生息的资产，每一次被抽中，持卡人都能分到一笔抽卡收入，未来还可能有其他的收入！换个角度看，这笔分成也相当于在持续摊薄他持有这张卡的成本，变成和 Gacha 平台一样的持卡角色。 对 Gacha 平台来说，这套模式也帮助把一个"重资产、靠自有资本扩张"的生意改造成一个"轻资产、靠聚合外部库存扩张"的生意，卸掉了资本投入的包袱。并且，之前，卡是平台自己花钱屯的，存货风险压在它头上，它得留点操作空间保命、回本，往往会不得不留后门，也不敢开源其抽卡概率，但当货源风险分摊了，开源也就没阻碍了。 既解决经济问题，又解决信任问题的典范。 --------------------- 5、卡店、金库为什么愿意参与这个游戏？ 即便有商业利益，要让卡店、金库改变自己用了多年的现有模式，总归是有迁移成本的，毕竟你也是在给他们画饼嘛，因此得有一些额外的东西来说服他们。 Renaiss给的，是两样东西：数据，和库存管理。 数据，尤其是卡的价格，是卡店每天都要查的。可它们之前能参考的大多只有 eBay 这类线上渠道。但是并非所有交易都在线上，大部分成交实际发生在卡店这样的线下零售渠道，这部分 eBay 上是看不到的。 Renaiss 通过和卡店合作、给卡店铺系统，一方面拿到了这些线下的报价数据，一边也让愿意加入这个游戏的卡店，能看到其他卡店的报价和成交，你会不想要接入一个更全的行情网络吗？ 而库存管理，与我们之前所说的货源状态同步诉求息息相关。Renaiss 给卡店的库存管理，是一个涵盖链上的状态同步系统。这意味着同一张卡，理论上可以同时挂在各个渠道，线下店里、线上市场、Gacha 盲盒池，最大化它被卖出、被抽走的可能。而一旦它在某一个渠道成交了，或者在盲盒里被抽走了，其他所有渠道立刻同步下架，绝不会出现两头都卖、超卖穿仓的情况。 对卡店来说，这就是直接的生意改善：货能铺到更多渠道，周转率就更高；周转率高了，收入就更多，切中最大的痛点上，之前就说过，线下卡店最缺的就是周转效率。 这也是我理解，为什么 Renaiss 会铺那么多业务的原因 - Vault OS：托管 - Renaiss Protocol：流动性协议，含 Gacha，Market - Renaiss Index：价格预言机 - Renaiss Fi：上层的DeFi应用 - Renaiss Labs：SDK / CLI / Skill等生态工具 甚至做 Gacha 业务，也是在给这些卡店和金库打样，给他们看到实打实的 PMF，让他们自己去算这笔经济账。 到这里，其实很多东西也都自洽了。 "If you're offered a seat on a rocket ship, don't ask what seat. Just get on." --------------------- 6、写在最后：NFTFi未竟之志的延续 作为一个 Crypto 老人， 经历过NFT时代各种Fi（Perp，AMM，借贷、碎片化等等）的崛起以及后续的衰落，多年后看到 Renaiss 试图做的事情，总会有一种试图振兴 NFTFi 未竟之志的既视感。 而这一次，因为标的本身就有庞大的线下收藏群体以及相对成型的交易市场，你不需要从零到一去为标的创造需求、培育共识，而只需要去看有哪些经济关系能优化，以及可以叠加哪些新的产品体验，从而激发新的增长，这就和之前的 PFP 非常不一样。 而这也是为什么我会对基于 TCG NFT 的 Fi 存有不小期待的原因。当初NFTFi 的教训，本质上还是标的选择的问题。一个资产能不能被拿来抵押、借贷，还是取决于是否有真实而稳定的需求，有了真实的需求，才能催生出真实可信的价格；有了真实的价格，才能真实地给风险定价。而PFP 的需求本身就是不稳定的，OpenSea 上的价格本身就是虚的，因而衍生的Fi也是不健康的，既 price 不了风险，也没法在必要时做清算。 TCG 恰恰相反。它线下的需求扎实，只是目前被分散在不同的闭环内，打破闭环，把货聚合到一个流动性池，意味着有更多的 liquidity venue 和 source of demand 可以去承接标的的清算；价格汇集到一处，综合线上与线下的真实成交，也会让这个价格更接近真实。需求是真的，价格是真的，你才能真实地 price 风险。 那么在这之上的 Fi，自然就更可持续、也更健康。

Coinbase charges 2% as a processing fee for new loans. That's of the borrowed funds, not 2% of the interest! Meanwhile, most onchain protocols struggle to charge anything. Really shows who owns the more valuable asset (distribution).

$SATS One of the first IPOs @saturn_credit has participated in - and the first of many. We see digital credit proliferating and are building the infrastructure to capture that growth. Super bullish on the Strive team’s meticulous execution. Just getting started.

Bringing TCG into onchain finance. Beyond collecting and trading, we’re opening up new ways for onchain collectibles to earn through @renaiss_fi . Renaiss Earn is coming soon, letting your cards earn yield through staking. Unlock the value of your cards. The next step is coming.

The Copernican Model Over the last few months, I’ve been studying the crypto models that seem to be discussed on a "fundamentals" basis: HYPE/Aave/Venice/etc, following the users/ revenue/relationship between a useful product and its token - all to create a sort of "value accural ontology." This is a case study from that research. The reason was more selfish: I wanted to understand which models work when your business has to interact with the "real world," namely for how we want to take @usdai_official for the most alignemnt As a founder, I’ve had doors literally shut on my face when we started because we’re “crypto” (literally left in the waiting room like a tv show). I still believe tokenization is one of the most important technologies we have today. But the institutions we need to work with often want a equity counterparty, a board, and a contract. You just wont get around this for the next 10 years (no a cayman foundation doesnt work) That experience has made me increasingly interested in the role of an equity surrogate: an independent operating business that connects a network to the world outside it.. but frankly there werent many clean examples out there without value destruction. The case I keep returning to is @tradexyz and Hyperliquid.. and im not really sure they even know how symbiotic of a relationship they created. They technically SHOULD be the same team.. but they are divided across the river due to regulatory issues, while being symbiotic Consider the S&P 500 agreement, they licensed the benchmark to tradexyz for a perpetual market: the institutional relationship sits with the company, but the product runs on the network. tradexyz can negotiate licenses, develop products, operate markets, and build distribution. Hyperliquid provides shared execution and settlement infrastructure. And if theres a company that ever wants "exposure" to the Hyperliquid business, but they just cant buy a "token" (and believe me, it's super super hard to get a traditional enterprise to buy a token, it doesnt fucking matter if you have an ETF, you literally have to convince a boomer board to do it and get the infrastructure set up to do it). Instaed, they could just invest in this equity, as it is not burning the HYPE it buys, but is increasing its share of it. so instead of buyback-n-burn, its closer to commit-n-compound. I’ve started thinking about this as a value-accrual architecture, with two different forms of capital (terms best described by a16z crypto's post in 2025): Network asset: scarcity at the core. - Its supply discipline can become more credible, its economics more programmatic, and its operation less dependent on any single company. - It coordinates shared infrastructure and connects activity across many businesses to a common asset. - That is what I mean by a progressively hardening asset. The scarcity and independence have to be earned through the design of the system. - Not capital intensive, as it must be smart contract based. - Can often place be the seat of the "decentralized security" - as there is no central underwriter. If HYPE was a company.. itd be regulated out of the wazoo. Enterprise equity: elasticity at the edge. - A company can issue shares, raise capital, hire people, acquire licenses, and build products. - Its capital structure can expand with the work required to bring the network into the real world. - New shares dilute ownership percentages, but productive investment can increase value per share. - That ability to finance expansion is why I think of equity as elastic - This is the part where its OK to be regulated, because most of the regulational burden is held by HYPE, theyre just asset issuers. These different traits are the reason to combine them. An enterprise can raise the capital to grow while the network maintains its own supply discipline. The connection is the activity that expansion creates, and the mechanisms that route value from that activity back to the network. Hyperliquid makes part of that relationship explicit. Trading generates fees for the deployer and the protocol. The Assistance Fund (insurance) automatically converts its allocated fees into HYPE, which the documentation specifies is burned. Hyperliquid fee mechanics The broader strategy I take from this is Commit & Compound that is conducted around the equity enterprise. It's effectively what a DAT 2.0 would do: create a business first, then max-bid HYPE with that entity, then get new investors to invest in the convexity of HYPE^2. Build a useful business around the network. Commit capital to its asset. Retain exposure to the infrastructure your business helps make more valuable. For a company that accumulates and holds the network asset, growing enterprise value and participating in network value become connected opportunities. There is a business to capitalize and a shared ecosystem in which to hold an economic stake. That is why I find the assumption that every successful application eventually needs its own token less compelling. Building a valuable company around an existing network asset is a meaningful strategy in its own right. Notice how much kinetic language I’m using: commitment, circulation, gravity I think network assets and enterprise assets represent different forms of gravity HYPE is the sun: the network asset at the center tradexyz equity is a planet: an enterprise building its business around that network Its real-world integrations are moons: the licenses, institutional relationships, and distribution channels that gather around the enterprise and extend its reach Enterprise value forms around network value. Real-world relationships form around enterprise value. Their activity feeds back into the shared system. Personally, I think the greatest value can ultimately accrue at the network level. But that belief has to be substantiated by the businesses being built around it: real users, useful products, liquidity, and recurring economic activity. A token doesn’t acquire gravity simply because we call it a network asset. This is the distinction I found useful in a16z’s writing: can the network function and accrue value independently of the original company? Can other businesses build on it and contribute to its economics? The company can become a great business. The network can become the foundation for many great businesses. Scarcity at the core. Productive expansion around it. I’ve learned a lot from this Commit & Compound structure, with a Copernican asset at the center. It has changed how I’m thinking about USDAI and CHIP. More on that in the next post

今天 CT 上这个新的 Perp 挺火 它的设计核心，在我看来就是： Tolerated Insolvency + Loss Mining ‼️长文警告‼️ 好多年前我也曾试图为 Pool-Based DeFi 项目设计过类似的亏损挖矿激励，但最后不了了之，因为我发现最终就是从一个坑跳到了另一个坑。 后来 @dYdX @HyperliquidX 这些订单簿 Perp 势头远远盖过 Pool 模式，大家用做市商激励直接绕过了 Pool 模式的扩张困境，也就没人纠结 Pool 模式怎么 GameFi 了。 所以看到 @papertrade_xyz，由衷有一种莫名亲切.. 想从产品设计的角度，聊聊我对这套逻辑的一些理解： ----------------------- 它不是DEX，而是一个边池（Side Bet） 个人认为，没有价格发现的，都不能算作 Exchange。而 PaperTrade 就是这样，其只是基于 Hyperliquid 产生的一个合成的 Perp 敞口，具体的赌注、收费、赔付规则全是自己的，与 Hyperliquid 完全不同。 几个细节： 1）没有订单簿概念，所有成交都和虚拟的 LP 对手方执行，具体会参照 Hyperliquid CLOB 上实时的 Best Bid Offer (BBO)，0滑点，0交易费，0 资金费率，最高可以 1000x 杠杆； 2）没有流动性或者深度概念，只要在每个交易对的 Open Interest (OI) 上限之内，用户的多空照单全收，也不存在所谓的 LP 存款行为； 3）用户的盈亏会进入一个只是用于结算而非用于交易执行的 LP 池，用户发生亏损，对这个 LP 池子是正流入，用户产生盈利，对这个 LP 池子是负流出，如果 LP 池子没钱赔赢家，赢家的利润进入一个 FIFO 队列，等未来有人亏了，LP 池子里有钱了再按顺序赔付。 是的，它其实更像是一个边池（Side Bet），借主桌牌面定胜负，但赌注、赔付结构、经济关系全部独立于主桌。 ---------------------- 而要理解 PaperTrade 这么设计的原因， 就要先理解传统 Pool 模式的扩张困境。 传统的 Pool 模式是一种垫付制（Prefunded），需要大家先把钱存进来一起当 LP，既充当流动性和深度，也充当交易者赢的时候的利润兑付来源，好处是 LP 能够分到交易手续费、资金费以及交易者输的时候的客损。 理想情况是，多空完美对冲，从而两者之间的盈亏相互抵消，LP 不承担方向性风险，纯赚交易手续费、资金费。但现实是交易者之间的多空 Skew 在大部分情况下是比较明显的，因而传统 Pool 模式系统的设计重心，都被放在了如何去激励多空双边的平衡，从而降低 LP 的风险上。 毕竟保 LP，就是保交易量和 OI 而解决方案也无非大多是动态 Funding Rate 惩罚 Skew，例如多头太拥挤就收更高的 Funding，逼一部分人平仓或转空，又例如在报价上设置更多的滑点等。用处肯定有，但治标不治本，其次，这类机制也往往导致 Pool 给的报价不一定等于市场上的公允价格，而更多是一个LP 能扛得住的价格。 也正是因为无论用什么方式，最终的多空 Skew 和 LP 方向性敞口，始终会存在不确定性，从而很难精确对冲风险，传统的 Pool 模式都会多多少少被迫用代币激励去弥补 LP 的风险和亏损，但依旧容易面临，在 TVL 达到一定规模后很难更上一层楼的困境，因为这般风险偏好的资金容量就那么多。 这种 LP 不想承担方向性风险，但偏偏系统就需要 LP 来承担的矛盾，永远都存在。 ----------------------- 这其实也是很多新的 Perp Dex，后来并没有把牌全部押注在 Pool 模式上的一个原因，大家要么把它当做初始冷启动的抓手，之后转向订单簿，要么只是充当订单簿之外的一个补充和辅助。 因为， 订单簿没有上面所述矛盾，任何人都能通过价格来表达其风险偏好，和转移其认为的风险，没有谁强迫谁承担任何不想要和未知的敞口。 PaperTrade 的思路则正是在这种订单簿已经基本胜出的背景下，在依旧坚持 Pool 模式路线的基础上，试图去寻找新的突破口。 它也想绕过这个矛盾，怎么做？ 赊账制（Deferred Settlement）！ 即把理想状态下 Pool 模式里的多空完美对冲，强制硬编码。永远都是亏的用户去兑付赢的用户，哪怕有用户先赢了，但是用于结算的 LP 池子里没有钱，也是先赊账，等有人亏了再兑现。 也就是说，这套机制允许系统在某些时刻处于资不抵债（Tolerated Insolvency）状态，如果有赢家暂时拿不到利润，没关系，排队等着呗，未来有人亏了自然就赔你。允许错配，用时间来消化。 好处当然是不需要预先说服任何人来当 LP，也没有传统 Pool 模式的那些动态滑点、动态 Funding Rate 等等机制，干干净净。似乎唯一的代价就是赢家可能会面临排队领取利润的情况。 但真的如此么？ ----------------------- 让我们回到交易者的第一性原理视角： 你亏了，钱是真金白银地没了，被划入 LP 池。你赢了，有一定几率，你的利润只是一个等待队列里的数字，什么时候能拿到取决于未来有没有足够多的人来亏损。亏损是确定的、即时的；盈利是不确定的、延迟的。 这天生就有一个负螺旋： 利润队列长 → 交易者走 → 亏损少 → 利润队列更长。 那怎么打破这个负螺旋呢？ Paper Trade 团队的方案是：亏钱挖矿 Loss Mining。 当你亏钱的时候，协议会 Mint 出 $PAPER 给到你，让你不在意亏钱给协议，甚至想要主动亏钱给协议，其实就是用亏损来买 $PAPER 代币啦！而大家买 $PAPER 的原因也是因为可以用来 Staking 分协议的收入，和 LP 池充裕的时候的客损，因此相当于可以分享协议的繁荣。 LP 池子不同余额，也对应不同 Loss Mining 规则： 1）LP 余额 < 0，资不抵债 此时赢家利润需要排队，用户端亏损都优先用于兑付赢家的利润，然后才是积累到 LP 池余额中，并且此时，用户正常的亏损了结是不会 Mint $PAPER 的，只有爆仓的亏损才会 Mint $PAPER，为激励更快有亏损产生，此时爆仓 Mint $PAPER 的速率也是最快的，100 PAPER / $1。 2）0 < LP 余额 < $2M 此时赢家等待队列已清空，用户端产生的亏损因此可以直接积累到 LP 池余额中，正常的亏损了结和爆仓亏损也都可以 Mint $PAPER，速率依旧维持在最快的状态来刺激亏损，100 PAPER / $1。 3）$2M < LP 余额 < $5M 同上，随着 LP 池子余额逐步充裕，Mint 速率渐进衰减。 4）LP 余额 > $5M 此时，LP 池子余额处于充裕状态，Mint 速率降到最低，并且此时用户端产生的亏损（客损）都可以被 $PAPER Staker 分走，相当于 LP 池子有一个软顶 $5M ----------------------- 然而既然是挖矿，那就是可以被薅的， 比如你可以用两个地址对敲，一个盈利，一个亏损，并用亏损地址去领取 $PAPER。虽然协议通过盈利者需要交付一笔 Haircut 把纯套利漏洞堵住了，即盈利端只能拿到小于 100%，亏损端亏 100%，结果是净盈亏取决于 Haircut 与 Mint 出来的 $PAPER 的价值大小。并且协议也用资不抵债时只有爆仓才能 Mint 做了进一步防御， 但事实是你与矿工的关系是相爱相杀的。 从项目方角度，你早期必须拉拢矿工为 LP 池子余额做贡献从而吸引真交易者（毕竟谁都不希望来交易，赢了钱拿不到吧，因此隐含了赊账制虽然不需要 LP 真金白银预先投入，但间接仍需要为潜在赢家尽量提前备好兑付金）。而这个过程中， $PAPER 价格就是最大的影响因素： - 无利可图，矿工离开 - 有利可图，矿工小试牛刀 - 持续上涨，矿工大包大干 当然是希望越涨越好啦， 然而谁又能完全保证价格呢？ 并且挖矿的人越多，对 $PAPER 的价格压制也越强： 当 $PAPER 涨过挖矿盈亏平衡点 → 有人来刷 → 供应膨胀 → 价格被压回来。想要继续持续上涨，就要有更多的买盘，以及对 Staking 分红的正向预期，不能走弱。 然而，LP 池余额低 → $PAPER Mint 速率最高 → 供应快速膨胀 → $PAPER 价格承压 → Staking 分红相对于 $PAPER 市值的 Yield 下降 → 没人愿意为了 $PAPER 来交易 → LP 池更难填充 → $PAPER Mint 更快。 这也使得代币流通量越来越多之后， 你系统的容错率是越来越低的， 并且你还无法摆脱币价的影响。 ----------------------- 这也是为什么我会感叹，从一个坑跳到了另一个坑 因为本质上来说， - 传统：垫付制（Prefunded） - 创新：赊账制（Deferred Settlement） 垫付制也好，赊账制也好，两者其实都寄希望于 Token 激励来解决问题，区别只是在于垫付制直接激励 LP 存款方，而赊账制，则是直接给予亏损者奖励，让他们为 LP 池贡献更多的资金，从而去备兑赢家利润。 但 Token Price 本身就是一个不可控的变量，我们也看到了，其价格变化会影响到用户的行为，从而引发达成预想目标的不可控性。 这就是 Token 驱动型机制的反身性陷阱的本质，以及为什么很多创新，总是一鼓作气，再而衰，三而竭。 当然我写这些也并不是为了 Diss PaperTrade， 恰恰相反，在熊市，在大家都跑去AI，高喊 Crypto 没戏了的当下，继续积极探索新范式，这本身就需要勇气。 赊账制作为一个巧妙的思路，确实提出了一种绕过传统 Pool 模式启动和扩张困境的可能性，只是或许需要进一步思考对 Loss Mining 的依赖，以及继续探索不完全被 Token Price 反身性绑架的方式。 @Forgd_ 这边非常愿意和团队交流。

喜聞 @coinbase 進軍 TCG 賽道，提供鏈上抽卡產品給予美國用戶，適逢我們 @renaissCLTB 旗下 TCG產品 @renaissxyz 的新里程碑，營業額正式突破 3千6百萬美元，過去專注在亞洲發展的 XYZ ，在營業額外有甚麼亮點值得分享？ 1. 過去 30 天的平均提卡交貨時間只需 1.3 天，全亞洲最快 2. 整個10月的贖回手續費將降至 0 美元，全亞洲最低 3. 推出 RIP ，將鏈上抽卡行為由開源框架下提供可驗證公平證明，精準至每一張卡的隨機路徑，市場唯一 如果對 TCG 鏈上抽卡的亞洲市場感興趣，歡迎隨時聯絡，亦歡迎貨比三家 這個賽道深耕已久的我們，不止在上述多個領域斷檔式領先，亦已有幾乎能一鍵部署的SDK、AGENT CLI 、Index pricing API 等成熟配套 雖說時勢做英雄，但必須飲水思源，感激 @BNBCHAINZH 和 @yzilabs 從 2025 年就提供各種的支持，參加 2025 年的 BNB 黑客松並獲勝是一切的起點，謝謝這個不問出處，只看交付的生態環境，Renaiss 才可以在一年內持續發展至今 接下來的三個月，除了 Upbit layer2 @GIWA_by_Upbit 的 Dex @GiwaterFinance 已宣布接入 Renaiss TCG GACHA 抽卡功能外，更多意想不到的合作和部署即將公布 另外分享個有趣的預告？ 10月2日，敬請期待，又一個大的要來了 #BNB# #TCG# #KBW#

A few friends asked what I'm looking for. Here is my short answer: privacy, post-quantum. - privacy, institutions can adopt - cryptography, quantum computers can't break Most of what gets built on top of crypto in the next cycle depends on both. This is my target for EASY Residency S5 @EASYResidency

特别喜欢Aylo讲的这一段经历 在我看来，等待底部就是极其不明智的，因为“足够便宜 + 足够共识 + 足够安全”不可能同时出现，在下跌过程当中，执行买入，要比纠结是否买到最低点重要得多。 很多人总鼓吹右侧交易，但我的暴论是，对于大部分普通人来说，左侧要远远优于右侧，因为更符合心理学。 行为金融学中，人有损失厌恶、后悔厌恶以及非常著名的心理账户，这三个效应在左侧和右侧里，是完全不同的： 一、大部分人到最后根本无法执行右侧 因为大部分人不是时刻在一线盯盘的交易员，很难感知到哪一次是真突破，更不具备那种从反应过来到快速执行的肌肉记忆。在长期的熊市环境中，大部分人早已经把资产价格锚定在记忆中的低价区了，一旦价格真的开始涨，你的心理账户自动把它标记为"贵了"，并产生强烈的后悔厌恶，表现出对于没有早买入的难以接受，从而非但不是买入，而是等待回调，越犹豫越等，越等越错过，等到市场彻底确认趋势，所有人都看多的时候，FOMO 进去。 而此时成本在高位，信心脆弱，一回撤就会极其难受。 二、左侧反而是人更容易执行的 在下跌中买入，心理账户会有一个归类为"捡便宜"的心理暗示，而如果事先预估好盈亏比和下行空间，比如每跌一定幅度加一次仓，就能通过"不断降低成本 + 放大敞口"的方式，让自己处于为未来上涨积累更大幅度的舒适区，把本身的损失厌恶，转化成一种期待下跌的积极心理暗示。 而一旦市场反转，左侧建仓的投资者往往享有更低成本、更大盈利空间，这种正向反馈也更能增强持仓信心。 三、DCA Now，Start Today! 定投就是左侧里最适合普通人的执行方式， 因为它在心理上帮你做了三件事： 1）安全垫暗示： 你告诉自己最多再跌 20-30%，而且如果真跌了，我反而能买到更便宜的，从怕买高变成期待下跌。 2）拆单法： 把一个需要巨大勇气的大决定，拆成一个个不需要勇气的小决定。每次只花一小笔，心理负担极小，执行率极高。 3）Free Lunch 心理： 以及，当你定投的钱来自每个月的收入，而不是从现有仓位里调拨的时候，心理感受完全不一样。这笔钱本来就不在你的资产账户里，花出去是没有痛感的，你甚至会觉得每个月都有免费的BTC拿。

Across Protocol has been transferred to a new company, Across, Inc. ("AcrossCo"), and $ACX is sunsetting. Holders of $ACX now have two options, summarized in this article. The exchange portal is live at