Starting to think ethereum:0xad29f2723fcdbcf665f210f25e06f97477e417cf might have another leg in it. Been seeing some decent price action around @grvt_io lately, with the structure gradually improving since August. Nothing too explosive yet, but there are a few things making the setup look better: → Higher lows holding up since August → Gradual recovery without a massive blow-off candle → Trading volume starting to return → $0.30 looking like the next level to challenge Wouldn’t be surprised to see momentum pick up if buyers keep pressing. $0.20 remains the downside scenario if the recovery fails, but I’m leaning toward an upside attempt first. Feels like the kind of chart that could attract traders pretty quickly once it starts moving. The volume follow-through will probably decide how far that move goes. PS: Giving away $100 worth of ethereum:0xad29f2723fcdbcf665f210f25e06f97477e417cf to one winner. RT + comment your price prediction to enter.

Of the $433.5M @Collector_Crypt generated in revenue last quarter, only $25.4M came through as gross profit. Went through Pine Analytics’ Q3 report, and I think the customer data is just as revealing as the revenue itself. The numbers: → $433.5M in revenue, up 8% QoQ → $408.1M spent on card buybacks and redemptions → $25.4M in gross profit, up 12% → 5.9% gross margin So roughly 94% of revenue flows back out, leaving a relatively thin margin on a massive amount of activity. But the customer concentration is what caught my attention. 21,876 wallets purchased packs during Q3, nearly double the previous quarter. Yet just 548 wallets spending $100K+ accounted for 83% of sales. The top 100 alone contributed 54%. And the spending is moving toward more expensive products. Packs priced at $2,500+ generated $169.6M, accounting for 39% of sales, up from 21% in Q2. What’s more surprising is that only 18 of September’s top 100 buyers were also among June’s top 100. So a lot of the business depends on continuously attracting new high-spending collectors rather than the same whales consistently buying. @JupiterExchange also contributed 11% of Q3 sales after launching distribution in July, although retention among its first-time buyers was weaker than Collector Crypt’s own site. Meanwhile, monthly sales have cooled from June’s $212.2M peak to $134.5M in September. I actually like the underlying model here. Physical collectibles held in vaults, instant onchain ownership transfers, and the ability to redeem the actual cards. But looking at the numbers, I think the bigger question is how much recurring demand exists outside that rotating group of high-spending collectors. The $433M quarter shows how large the business can get. The customer concentration tells you a lot more about what’s driving it. h/t @PineAnalytics

More active addresses don’t necessarily mean more revenue for a blockchain. I compared seven-day chain revenue against active addresses across five networks. Here’s how much revenue each chain generated: → @base: $561.5K → @ethereum: $498.7K → @0xPolygon: $435.2K → @arbitrum: $128.6K → @Optimism: $19K Now, here’s the revenue generated per active address: → Base: $0.356 → Optimism: $0.300 → Polygon: $0.225 → Ethereum: $0.207 → Arbitrum: $0.178 Base leads both rankings, but Optimism surprised me. Despite generating the least total revenue, it ranks second in revenue per active address. It shows how differently networks monetize activity. Having more active addresses doesn’t automatically translate into more revenue. Of course, higher revenue per address isn’t necessarily better. Lower fees can also encourage more activity.

after @grvt_io’s first token buyback and burn, i went back to look at the numbers and what comes next for $GRVT. here’s the latest snapshot from DeFiLlama, Oct. 21: → $14.75B perp volume / 30D → $3.45B perp volume / 7D → $446.6M open interest → $36.1M TVL Grvt is processing serious trading volume, with $440B+ in cumulative perp volume. then came the October 20 announcement. Grvt bought and permanently burned 1.1M $GRVT using a portion of the app’s gross profit, removing close to 1% of circulating supply. i see this as a solid step because the buyback has moved beyond promises. the tokens were actually purchased on the open market and burned. but the bigger picture is what comes next. @grvt_io has four major releases planned before the end of November: → Grvt Earn: fixed-income strategies targeting up to 11% yield → Stable Funding Perps: zero trading fees, daily funding and a target of 1,000+ markets by December → Yield as Margin: earn yield on eligible balances while using them as trading collateral → Grvt 2.0: a redesigned investing app bringing these experiences together the direction makes sense to me. instead of competing on trading alone, Grvt is trying to make capital productive across earning and trading, without forcing users to move funds between separate accounts. that could create a stronger reason to stay on the platform and give $GRVT a more compelling story beyond speculation. still, there’s one number i won’t ignore. TVL peaked at $113.7M in March and sits around $36.1M today, roughly 68% below its peak. so despite the trading activity, Grvt still has work to do in attracting and retaining capital. the buyback is a good first step. now i want to see whether the upcoming products translate into sustained usage, stronger TVL and recurring buybacks supported by the business. with Grvt 2.0 approaching, the next few weeks could be important. the real test is whether Grvt can turn all this activity into a platform people want to keep their capital in.

ethereum L2s processed 14.5x as many transactions as mainnet over the past month, as of october 21. but how much of that activity translates into value for ethereum? according to @growthepie, L2s paid just $82K in settlement fees over the 30 days ending october 21. meanwhile, @base generated $2.77M in onchain profit and @RobinhoodCrypto chain $2.80M over the same period. this measures fees collected minus settlement costs, not full operating expenses. the gap raises a bigger question about the L2 business model. they can offer cheaper transactions and retain much of the revenue users generate, while ethereum provides settlement and data availability. as ethereum expands its own capacity, low fees alone may become a weaker reason to choose one L2 over another. distribution, liquidity and the applications built on top could matter far more. scaling transactions is one thing. building an economy that captures lasting value is another.

DeFi lending vault deposits have grown from ~$4B at the start of 2025 to more than $10B by October 2026. That’s 2.5x growth in roughly 21 months. But the bigger story isn’t the capital entering these products. It’s the lending risk depositors are outsourcing in exchange for yield. Crypto lending vaults typically offer 3–10% returns, while riskier strategies can exceed 20%. That spread deserves scrutiny. Here’s where I think the risk becomes more interesting. » Curators are becoming the risk managers Take @Morpho. Its Vault V2 separates strategy from execution. Curators determine which markets and adapters are permitted and establish risk parameters. Allocators deploy capital within those rules. That creates a layer between the depositor and the underlying lending markets. But there’s an important technical detail: Morpho’s documentation says allocation caps aren’t continuously enforced ceilings. Exposure can move above a cap without a new allocation. A risk limit is useful, but it isn’t a guarantee that exposure can never exceed it. » APY doesn’t tell you how quickly you can exit Vault deposits are deployed into lending markets to generate returns. When borrowers use most of the available liquidity, the vault may not have enough assets immediately available to satisfy every withdrawal. Morpho explicitly distinguishes this situation from bad debt. A withdrawal delay doesn’t necessarily mean funds are lost. But it does mean that advertised yield and immediately available liquidity are two different metrics. » The real stress test is a collateral failure Suppose a borrower owes $10M against collateral initially worth $12M. If that collateral falls to $8M before liquidation can recover the debt, the position may leave the lending market with a shortfall. In Morpho Vault V2, bad debt reduces the value of the vault’s assets, and the loss is shared proportionally among depositors. The smart contracts can enforce the rules correctly and depositors can still lose money. That’s the distinction between protocol security and credit risk. » Look beyond the headline yield A useful comparison: Two Prime’s Bitcoin lending vault on Pareto launched with a target yield of 1.5 – 2% and roughly $10M of the firm’s capital committed to absorb initial losses. That doesn’t make it risk-free, and the strategy isn’t directly comparable to every DeFi vault. But it illustrates the questions I want answered: → How much collateral and market concentration sits behind the yield? → What proportion of deposits is immediately liquid? → Who can change the allocation, and what protections apply? → Is any manager capital committed to absorbing losses before depositors? → What happens to the vault’s share value when bad debt is recognized? DeFi vaults are making sophisticated lending strategies accessible to more capital. My take: growth in deposits shouldn’t be mistaken for better risk management. As more capital flows through curated strategies, the quality of the curator becomes just as important as the underlying protocol. I’d rather use a vault with transparent exposures, realistic withdrawal assumptions and clearly defined loss protections than chase an extra few percentage points of APY. In the long run, I think the vaults that earn lasting trust will be the ones that make their risks as visible as their returns.

Always testing new platforms, and @trdEverything definitely caught my attention. I threw a quick trade on a small $SOL move with 1000x leverage and walked away with +53.6% High leverage carries high risk, but it highlights how much opportunity lies in small price swings.

Crypto can generate billions in trading volume while almost everyone participating loses money. And the numbers from Solana’s memecoin trading scene show just how extreme that disconnect can get. Out of 829,539 wallets: → 90% lost money after fees → Median loss: $25 → Estimated aggregate losses: $395M → Top 1% captured 94% of all positive P&L → Trading platform fees reached ~$40M The surprising part isn’t that most wallets lost money. It’s how differently the losses and profits were distributed. Most losing wallets were down less than $100, while a relatively small group accounted for much larger losses. On the profitable side, almost all the winnings went to a tiny fraction of wallets. And the platform collected fees regardless of who won or lost. Before fees, 15% of wallets were profitable. After fees, that dropped to 10%. So fees pushed a meaningful share of otherwise profitable wallets into losses, even though most of the aggregate damage came from the tokens themselves. There’s another misconception worth challenging here: buying early doesn’t automatically make you profitable. The first ten buyers of tokens that eventually attracted 1,000+ traders earned a 71% aggregate return. But include the tokens that never became popular, and even the earliest buyers lost around 6%. That’s what happens when you measure the entire opportunity set instead of only looking at the winners. Of course, these are wallet-level estimates, and transfers or illiquid holdings can affect the precise results. But the broader picture is difficult to ignore. Trading platforms can grow, fees can accumulate, and a small group of traders can generate enormous profits while the typical wallet continues losing money. Volume tells you how active a market is. It doesn’t tell you who benefits from that activity.

Billions sitting in DeFi lending protocols doesn’t mean billions are being allocated efficiently. $ETH collateral, tokenized Treasuries and institutional credit carry different risk profiles. Yet lending infrastructure has historically tried to accommodate multiple exposures within broadly shared liquidity systems. That becomes a problem when leverage builds. Capital might be available, but the underlying risk isn’t necessarily priced correctly. Two different approaches are emerging. → @Morpho: Isolated markets with independent collateral parameters and curator-directed capital allocation. → @Aave V4: Specialized lending markets connected through shared liquidity infrastructure. The difference is how capital moves and where risk sits. Isolation contains exposure but can fragment liquidity. Shared liquidity improves capital access but introduces dependencies between markets. Neither structure eliminates liquidation risk. And the distinction becomes more important when markets get stressed. When collateral prices fall, leveraged positions become vulnerable, liquidations accelerate and available borrowing liquidity can tighten. Isolated markets can limit the exposure of lenders outside the affected market. Shared liquidity can support capital allocation across different markets, provided risk controls prevent losses from spreading. But there’s another problem. Higher lending yields can attract capital into markets where the underlying risks are poorly understood. A 12% lending return means little if collateral concentration and insufficient liquidation liquidity expose lenders to disproportionate losses. High utilization can look attractive during stable conditions. But when borrowing demand concentrates around illiquid collateral, the same utilization can make withdrawals and liquidations harder to execute. And if leverage keeps accumulating faster than available liquidation liquidity, lenders may end up absorbing bad debt despite collecting higher yields. That’s where the two architectures face different pressures. Morpho’s isolated markets depend heavily on collateral selection, curator decisions and the liquidity available to each market. Aave’s shared-liquidity approach depends on how effectively its risk controls contain exposure while allowing capital to move between markets. The bullish case is specialized lending attracting deeper capital without weakening risk containment. The bearish case is fragmented liquidity, aggressive collateral parameters and lending yields that fail to compensate for eventual losses. If specialization consistently produces lower utilization and worse risk-adjusted returns than general-purpose pools, the capital-efficiency thesis breaks. More lending markets don’t necessarily create better credit infrastructure. The advantage belongs to platforms that can deploy capital efficiently without allowing one poorly managed collateral market to compromise the rest.

Information Technology accounts for $1.55B of the $2.47B tokenized stock market tracked on @coingecko, roughly 63% of the total. It also recorded $531M in 24H trading volume, nearly 58% of the $918M across all sectors. That concentration is easy to miss when you only look at the market-wide figures. Market cap shows where tokenized assets are concentrated. Trading volume shows where activity is happening. I use CoinGecko’s sector view to compare these metrics across industries instead of treating tokenized stocks as one uniform market. Explore the live breakdown and see how each sector compares: coingecko.com/en/stocks/sect…

The next big tokenization story may look boring from the investor’s side. Federated Hermes manages about $911 billion. It plans to issue its first directly issued tokenized fund share classes in early 2027, through Prometheum. The key detail: they’re built for traditional brokerage accounts and financial advisers, not a crypto wallet. Think of a restaurant that keeps the dining room as it is and rebuilds the kitchen. The diner sees the same menu. The plumbing underneath is different. What’s confirmed: → $911B asset manager → Early 2027 target → Federated Hermes issues the share classes itself, not through third parties → Prometheum’s SEC-registered broker-dealer subsidiaries handle brokerage, custody, clearing and settlement → Other broker-dealers can offer the products through Prometheum’s clearing platform What isn’t: the funds, the blockchain, fees and investor eligibility. Money market funds may come first. Six places a fund share’s lifecycle could change without changing who the investor is: 1. Fund administration: the NAV process doesn’t have to change 2. Transfer agency: the ownership ledger could move onto a blockchain 3. Shareholder records: the record of who owns what could live in the token itself 4. Brokerage distribution: same accounts, same advisers 5. Custody: held by a registered broker-dealer, not a personal wallet 6. Regulatory reporting: the fund’s obligations stay in place Some of the largest tokenization opportunities will keep the investor relationship and change the infrastructure underneath it. DeFi access was never the requirement. Operational efficiency was.

Yesterday, @raincards introduced noncustodial wallets across 12 blockchains. But I think the more important development is what Rain is building around those wallets. It’s effectively trying to become the infrastructure layer for stablecoin-powered financial accounts. Consider what a fintech application needs to operate: → Wallets to hold and transfer assets. → Virtual accounts to receive and manage funds. → Cards to enable spending through merchant networks. → Payouts to distribute money to recipients. → Rewards to encourage account activity. These functions traditionally require separate infrastructure providers. Rain is bringing them behind one integration. Why does this make business sense? Because the economics of a financial account extend beyond payments. A wallet generates activity around balances and transfers. Cards create spending-related revenue opportunities. Payouts generate transaction volume. Combining these services gives an infrastructure provider more opportunities to monetize the same customer relationship. And distribution is already part of the equation. Rain says its card infrastructure reaches 175 million merchant locations. That represents access through existing card networks, not 175 million merchants directly accepting stablecoins. The distinction is important. Rain isn’t necessarily trying to convince merchants to adopt stablecoins. It’s connecting stablecoin balances to payment infrastructure merchants already use. But who captures the value? The fintech application controls the customer experience. Rain supplies the financial infrastructure and can potentially earn revenue across multiple services. That creates a stronger commercial relationship than providing a standalone wallet or payment API. There are still limitations. One integration doesn’t eliminate banking dependencies, compliance requirements or the economics of card networks. And broader product coverage doesn’t automatically translate into higher usage or profitability. The real test is whether applications adopt multiple Rain services and generate recurring activity across them. Still, the strategic direction is clear. Stablecoin infrastructure providers are moving beyond competing for individual transactions. Rain is positioning itself to power the entire financial account, with multiple opportunities to capture revenue from the same underlying user activity.

A7 International launches today, bringing a new approach to cross-border payments. Developed by Russia’s PSB Bank, the service lets users settle invoices from foreign counterparties in USDT, while recipients receive the funds through a regular SWIFT bank transfer in their preferred currency. The service targets foreign trade businesses but is also open to individuals, with a fixed fee of 0.3%. PSB Bank Chairman Petr Fradkov and A7 CEO Ilan Shor will introduce the service today at 10:13 UTC. Live: a7.biz/live

Nvidia’s perpetuals traded around 15.6x the volume of its tokenized stock over the past 24 hours. CoinGecko currently shows $321.27M in NVDA perps volume against $20.53M in tokenized volume. Apple’s gap is even wider: $193.87M in perps volume versus $8.67M in tokenized volume, roughly 22.4x as much. Both markets track the same companies, but they offer different kinds of exposure. Tokenized stocks are blockchain-based representations of shares, while perpetuals are derivatives that track price movements. The difference is revealing: for these two stocks, trading activity is concentrated far more heavily in derivatives than in tokenized versions of the shares. That matters when assessing RWA adoption. Heavy trading in stock perps shouldn’t be mistaken for equivalent demand to hold tokenized shares. @coingecko’s RWA tracker puts tokenized volume, perps volume and open interest side by side for individual assets. Explore the data: coingecko.com/en/rwa

We’ve spent years figuring out how to put assets onchain. But creating the token is probably the easiest part of building an actual market around it. Once you tokenize a stock, bond, fund or private credit position, you still need: → Issuance: a way to bring the asset to market → Liquidity: somewhere holders can actually buy and sell → Price discovery: a market that can establish what the asset is worth → Collateral utility: somewhere the asset can be deposited and used → Credit: lenders willing to finance positions against it → Asset management: vaults and strategies that can deploy capital into it → Distribution: investors and institutions willing to hold it That is where the @orca_so + @Loopscale merger starts making sense. Orca has processed more than $550B in trading volume since 2021. Loopscale has $150M+ in deposits and has facilitated more than $2B in loans. Now they are combining under @formation_so. The initial stack brings together trading, lending and vaults, with origination and issuance infrastructure planned next. The stronger part is how those pieces can feed each other. Better liquidity makes an asset easier to accept as collateral. Credit gives holders another option besides selling. Vaults can push capital into both trading and lending markets. And deeper markets make it easier for issuers to distribute more assets. You can see how that becomes a much bigger business than simply charging a fee every time someone swaps a token. The opportunity is not just tokenization. It is owning more of the asset lifecycle: issuance → trading → collateral → credit → asset management → distribution There is still a big difference between combining these products and proving the economics work at scale. But the logic is clear. Tokenization solved how to create the asset. The next business is everything required to make the asset useful.