I made an exit strategy so you don't have too! So my main take away from the last bull run is you go into the bull market not knowing what is going on and you will assume you will figure out the top and sell perfectly. This does not happen even and you will get burnt. I did and i'm sure that many of you will have had similar experiences. There are so many ways to exit the market, here is just one idea I had that makes sense to me. Please change this as you see fit to taylor your portfolio. Step 1, Making a duplicate portfolio tracker: On coingecko/ coinmarketcap make a new portfolio. This will be important for this strategy. Once you start selling (this point will be discussed), you will not mark the sales on this duplicate portfolio. Only on your main one. This is so we can accurately track the % we should be selling. Step 2, when to start selling: This is not an exact science, however for the purpose of this I have chosen one month after the previous break of ATH. Feel free to change this however the rest of the data below will use this. Step 3: Estimating the length of the bull run: Below I will show the length of the last 3 bull runs from the point where they break the ATH. 2013, the break of ATH to top is 272 days. This was a very volatile bull markets however we don't expect this due to the size the market has grown too. 2017, the shortest of the three at 230 days. 2021, the longest bull run lasting 348 days. So here we have 3 bull markets to work with. Obviously we have to assume that something will change majorly for the next rally, however we use what we have to give ourselves the best chances. Average of the 3 = (348 + 230 + 272) / 3 = 283 days. Minus one month which we wait before we start to sell will equal 262. That is what we will be working with. Step 4, the strategy: First of all I will be working on the assumption that you are trying to sell 100% of the portfolio. 100% / 262 = 0.38%. This is what percent needs to be sold per day to achieve 100% sold using our time estimate. Now, you should not sell everyday 0.38%. Once you wait the month after the previous ATH breaks, you start counting percent, each day accumulating. E.G. day 1 = 0.38, day 2 = 0.76 etc. You let this build until a green green day which you sell. Could be worth waiting for the largest moves (+10-20%). Once you sell this amount, the count resets to 0. So why did we create the second portfolio? Because if you are selling the ratio in your portfolio would change. For example, if you hold 1 BTC and sell 50%, then the next day you sell 50% again, you would have 0.25 BTC. Not sold 100%. However, if you keep one portfolio not touching it when you sell, you can put in say what is 5% in dollars and the next day 5% again, and you would have sold 10%. Otherwise the maths will get extremely complicated. Once you get toward the end, you might have to sell on some red days. Don't be afraid! This is very important if you want to take full profits, so in the last say 100 days be less picky about you sell days. We always speak about DCAing in so use this strategy if you would like to DCA out :). NFA and Always DYOR!

Bitcoin’s 1-year realized volatility has fallen to 43%, below its 10-year average of 64%, according to Grayscale. Deeper liquidity, spot ETFs, and institutional participation are changing how $BTC trades, bringing its volatility within the range of individual S&P 500 stocks. The implications extend to how BTC collateral, leverage, and derivatives are priced across DeFi. @Grayscale’s research, led by @LowBeta, places Bitcoin’s volatility within the range of individual US large-cap stocks. - 81%: Five years ago - 64%: 10-year average - 43%: Latest 1-year reading Realized volatility measures historical price fluctuations, not future downside risk. Spot ETFs and deeper order books are changing Bitcoin’s liquidity profile. - Spot BTC ETFs: $105–111B in assets and roughly $57B in cumulative net inflows. - BTC order-book depth within 1% of the midpoint: up ~75% year over year. - Strategy: ~848,000 BTC held. Deeper books reduce the price impact of large trades, while ETFs broaden market access. Neither factor alone explains the full decline in volatility. Grayscale’s comparison shows where Bitcoin sits relative to individual stocks. - JPMorgan: ~20% - Amazon: ~31% - $BTC: 43% - Oracle: ~55% - @coinbase: ~70% - SanDisk: ~110% BTC is more volatile than roughly four out of five S&P 500 stocks, but its volatility remains far above that of the index itself. Coinbase, the most crypto-exposed name on the chart, is more volatile than Bitcoin itself. Independent data from @K33Research, @CharlesSchwab, and @Bitwise supports the broader trend. - K33: Daily volatility fell to 2.24% in 2025, from 2.8% in 2024. - Schwab: BTC volatility was 42%, below Nvidia at 50% and Tesla at 63%. - Bitwise: BTC’s 2025 price range was ~68%, versus ~120% for Nvidia. - Deribit DVOL: 30-day implied volatility was ~37–38 in October 2026. Lower BTC volatility could improve collateral efficiency across @aave, @Morpho, @sparkfinance, and @SkyEcosystem by reducing liquidation frequency and collateral-sale slippage. Higher LTVs may become viable, but extreme drawdowns, oracle delays, and liquidity gaps still constrain how much leverage these protocols can safely support. Lower implied volatility is compressing BTC options premiums across @DeribitOfficial, @binance, and @Bybit_Official. This changes the economics of covered calls, basis trades, and structured products. Options sellers collect less premium, while sudden volatility spikes can still generate outsized losses. Bitcoin’s declining volatility makes position sizing more relevant than treating BTC as a binary allocation decision. - Drawdown tolerance - Correlation with growth equities - Liquidity under stress - Tail risk BTC’s positive correlation with growth stocks can limit diversification in tech-heavy portfolios. Bitcoin’s maturing market structure can support more efficient collateral markets and deeper institutional participation in DeFi. Lower realized volatility does not remove the risk of severe drawdowns or liquidation cascades. The focus should remain on collateral parameters, leverage, and tail-risk exposure, not volatility compression alone.

Really appreciate it Eddy, means a lot coming from you. Wouldn't it be cool if the wallet supported zcash too…? 😉

The riskiest US corporate bonds now pay more than they did at the worst of the April 2025 tariff shock. The investment-grade end has barely moved. I looked at where Oracle, Anthropic and CoreWeave sit in all this, and what I'm watching next.

$BTC dipped under $80K on Thursday after US producer prices came in 6.3% higher than a year ago. That still wasn't the story that stuck with me this week. Hit play, and let's go through it together. The macro side was rough. September CPI came in at 3.7%, PPI at 6.3%, oil sat above $100 and the 10-year yield pushed above 5%. $BTC touched $79.7K on Thursday, and about $930M in positions got liquidated in a day, most of them longs. What surprised me is how little $BTC actually gave up. It ended the week only about 2% lower, even with ETF money leaving for a second week: −$228M from Bitcoin ETFs and −$320M from Ether ETFs. The story that stuck with me is the hardware wallet one. Ledger confirmed that some devices carried a tiny implant that read the 24 words during setup and sent them out over a cellular network. The secure chip itself wasn't broken. Loss estimates run from $86M to $103M, and MediaMarkt and Saturn pulled Ledger from their shelves in every country they operate in. It isn't the first time, either. In 2020 Ledger's customer list leaked, and in 2021 people found tampered devices in their mail. In 2023 the Connect Kit library got poisoned, and this January a checkout partner was breached. Every one of those went around the chip, not through it. That's why the most important reaction came from the brands themselves. Trezor is cutting back its reseller network from January, and Ledger's new phone will only be sold through its own shop. The fewer hands a box passes through, the fewer chances someone gets to open it. The AI story of the week had the same shape. OpenAI disclosed that one of its test models, with no funds of its own, scanned 362 wallets made from public seed phrases, found one holding testnet ETH and used it to finish a coding task, without mentioning it in its report. Nobody hacked the model. It simply used something it was never given. The coins were worthless, but an agent quietly spending money that isn't its own is something we'll see again. The rest of the week, quickly. MSCI finalized a rule that leaves out companies whose assets aren't mostly operating businesses, and Strategy is the name everyone is watching before the list lands on Nov 11. JPMorgan puts the passive selling at about $2.8B if it gets removed. Elsewhere, Schwab opened Bitcoin and Ether trading to its clients, and Kraken's parent agreed to buy a bank in the EU. On the network, mining difficulty jumped 5.9% to its highest level since March, so miners are doing more work for the same pay. Google also cut errors 40x on its Willow quantum chip. That's still nowhere near breaking Bitcoin, but Coinbase is already asking the industry to plan the lock change now. It felt like every layer got stress-tested in the same week. Out of all of it, the wallet story is still the one I keep thinking about.

Last month I wrote about @MEXC’s VVIP and how you can get in without a big balance or heavy trading volume. What you couldn’t see back then was how your own score was put together. You’d open the page and get a number, but not much about where it came from. That’s what Score Insights changes, and honestly the breakdown ends up being more interesting than the score itself. You can now see how your account is doing across five areas: → How actively you trade → What you hold on the account → How well it’s secured → How much you use the platform beyond trading → How long you’ve stuck with it Each one gets its own rating, so it’s easier to see where you’re strong and which areas might need attention. The part I liked most is that the trading side looks at your activity and volume, not whether your trades are profitable. I don’t need an exchange grading my PnL anyway. My chart already does that every day. :D Not every area is about money either. If security is the one that needs work, that’s about things like passkeys and Advanced KYC, not depositing more. It’s worth a look because your tier is what decides your perks, like the cashback rate on the MEXC Card or futures loss coverage vouchers. Seeing what’s behind your score makes it easier to understand where you are and what the next tier would actually add. If you’ve checked yours, I’m curious what came back flagged. Drop your score below, or just the areas that need work if you’d rather keep the number to yourself. 🔗 Check your M-Score here: mexc.com/user/m-score

AI's next economic shift is moving beyond model intelligence toward the infrastructure that executes work, coordinates agents, and captures value. @Cloudflare's AI-agent requests grew over 1,700% in a year, signalling a growing execution layer beyond inference. So who captures the value as AI agents scale, and where does crypto fit in? — — — ➤ Execution is becoming a separate economic layer in AI Traditional AI workloads centre on inference, but autonomous agents extend demand into persistent execution across code, APIs, databases, and external applications. • Inference: Models reason, plan, and make decisions. • Execution: Agents run code, manage state, interact with tools, and recover from failures. As agents operate beyond individual prompts, CPUs, storage, networking, and workflow infrastructure become integral to completing tasks, shifting spending beyond model providers. — — — ➤ The execution layer is expanding beyond model providers AI agents need persistent environments to execute code, retain state, and recover from failures, creating demand across the execution stack. • Sandboxes: @e2b, @daytonaio, @vercel_dev • Workflow orchestration: @temporalio • Compute and execution: @Cloudflare, @modal, @flydotio • Agent infrastructure: @awscloud, @Microsoft The opportunity lies in recurring usage and pricing power, not simply rising demand for infrastructure. — — — ➤ Model routing is becoming a control point for AI economics Agents can route simple tasks to cheaper models, reserve frontier models for complex reasoning, and reduce inference costs through caching and code reuse. • @OpenRouter, @LiteLLM, @PortkeyAI, and @Cloudflare provide model access, routing, caching, and gateway infrastructure. As routing improves, total agent activity can grow without proportional growth in spending on individual model providers, shifting value toward whoever controls model selection. — — — ➤ Agent orchestration for persistent workloads Long-running agents need persistent state, scheduled triggers, tool permissions, and recovery mechanisms. • @LangChainAI: LangGraph coordinates stateful workflows, while LangSmith handles tracing and observability. • MCP connects agents to external tools. OpenAI Agents API and Claude Managed Agents support deployment, persistent sessions, and workflow execution. As agents take on more complex tasks, reliable execution matters as much as the model powering them. — — — ➤ Agentic AI is reshaping infrastructure demand • Cloudflare's daily AI-agent requests grew over 1,700% in a year, while @github recorded 473B monthly Git events in August 2026, up from 218.2B in September 2025. The CPU-to-GPU ratio could shift from 1:8 toward 1:1 as agents require more execution capacity. @nvidia, @intel, and @AMD are positioned for rising CPU demand, while @AnthropicAI committed $11.6B to Akamai's cloud capacity over seven years. — — — ➤ The battle for value capture is moving up the AI stack Different layers control different parts of the agent economy: • Models: @OpenAI, @AnthropicAI, and @Google supply intelligence. • Compute: @nvidia, @AMD, @intel, @CoreWeave, and @Akamai provide the infrastructure to run workloads. • Routing: @OpenRouter, @LiteLLM, and @PortkeyAI decide which models handle each request. • Agent assembly: OpenAI Agents, Claude Managed Agents, and Warp coordinate models, tools, and execution environments. The assembler can own the customer relationship and allocate spending across competing suppliers without owning the underlying models or infrastructure. — — — ➤ Agents need a way to pay, and crypto rails are competing for it An agent that calls paid APIs, rents compute or buys data has to pay for each step on its own, often in amounts too small for card payments. • x402: An open standard from @coinbase and @Cloudflare built on the HTTP 402 "Payment Required" code. The server replies with payment terms, the agent pays in stablecoins, and a facilitator confirms the transaction onchain before the service is delivered. • Stablecoin wallets: Agents can run on a dedicated, pre-loaded balance and pay per request instead of relying on a card or subscription. The same company reporting 1,700% growth in agent requests is also helping build the payment rail for them. That's where the agent economy meets crypto directly. — — — ➤ Outcome pricing shifts the focus to margins Traditional infrastructure charges per token or compute-hour, while outcome-based agents price outcomes such as resolved conversations and retained customers. Revenue depends on completed tasks, while margins depend on inference, compute, API, and retry costs. Usage growth ≠ revenue growth ≠ margin growth ≠ token value capture. — — — AI agents can expand compute demand without guaranteeing returns for infrastructure providers, and the same logic applies onchain. Agent payments, decentralized compute and onchain coordination are real openings for crypto, but usage alone doesn't guarantee value for tokenholders. Even protocol fees don't, unless that value actually reaches them. The protocols worth watching are the ones that capture fees from agent activity and pass that value through.

The Bitcoin levels I shared four days ago are already out of date. On Oct 14, options positioning showed a broad balance zone between 79K and 86K, with 87–88K above and 78–79K below as the areas that mattered. Today the balance zone has narrowed to 77–80K, the upside area has moved down to 81–82K, and the downside one has shifted to 74–76K. Some of these will probably look different again tomorrow. If the structure can move this much in four days, how much weight can you really put on a price target given six months ago, a liquidation map built a year ago, or a confident cycle call for two years from now? When I hear things like “it will definitely bounce from here,” “it can’t go below this price” or “the bull market starts on this date,” I honestly wonder how many of the people saying them have looked at how the market is positioned today, what risks are building up, and whether the conditions from four days ago still hold. Every day new positions are opened and closed, options expire, leverage changes and capital moves somewhere else. All of that changes the odds of what price does next. That’s why I follow this kind of data every day. One day on its own doesn’t tell you much. The next day either adds context or starts breaking the first idea, and a few days later you might have a trend, or realize the story you were following doesn’t exist anymore. You only get that by coming back to it regularly. I’d much rather change my view because the conditions changed than spend six months defending something just because I said it publicly. And if a target you gave six months ago eventually gets hit, that doesn’t mean you were right for those six months. You could have missed every shift in positioning, every new risk and every opportunity in between. That’s why I don’t put much weight on predictions that never get updated. What’s valid today can be invalid in two days, but once someone makes a bold call, people can keep following that same idea long after the setup itself stopped being valid. So I wouldn’t get too attached to the exact levels in this chart. They can move tomorrow. What matters is understanding why the map is moving.

Stablecoin card spending hit $1.224B in September, but most products still revolve around USD. @stripe and @Plasma are expanding multi-currency stablecoin cards, targeting the FX friction that comes with spending across borders. The real shift lies in how stablecoins move from balances to spending. — — — ➤ FX leakage is the problem A € balance routed through USD before a euro payment creates an unnecessary conversion. € balance → USD conversion → EUR payment FX spreads and conversion fees eat into the amount spent, while DCC can add further markups. Multi-currency cards can eliminate that intermediate conversion by spending directly from the matching balance. The real opportunity is reducing FX leakage, not increasing cashback. — — — ➤ Stripe × Plasma: Multi-currency stablecoin cards Stripe is expanding its stablecoin card infrastructure to support five fiat currencies: - $USD: US dollar - $BRL: Brazilian real - $EUR: Euro - $MXN: Mexican peso - $COP: Colombian peso The expansion also supports $USDC, $OUSD and eligible GENIUS-compliant stablecoins. Plasma is the design partner, bringing its multi-currency accounts onto Stripe’s card infrastructure. Coverage spans 30+ countries, with 100+ targeted for 2027. Automatic currency selection across balances remains on the roadmap. — — — ➤ Stablecoin card spending hit $1.224B in September Monthly stablecoin card spending grew from $0.6M in October 2023 to $1.224B in September 2026, more than 2,000× growth. - July 2026: $1.038B - August 2026: $1.116B - September 2026: $1.224B Yet stablecoin cards are still a tiny slice of card spending. At September's pace, that's about $14.7B a year, roughly 0.1% of the $14.2T Visa processed in payments volume in fiscal 2025. The opportunity is scaling real-world stablecoin payments while reducing FX costs and conversion friction. — — — ➤ Stablecoin cards are becoming a competitive market Stablecoin card competition is heating up, with several players targeting everyday spending. - RedotPay ( @RedotPay ): The current volume leader among tracked card programs. - EtherFi ( @ether_fi ): A major competitor combining crypto-native finance with card spending. - KAST ( @KASTxyz ): Gaining traction in stablecoin-funded payments. - Wirex One ( @wirexapp ): An established player expanding its card offering. - Plasma One: Smaller in absolute volume, but showing strong recent growth. The competition is shifting beyond card rewards toward distribution, spending utility and the cost of moving money across currencies. — — — ➤ Why Plasma? It already has a stablecoin card business Plasma One combines multi-currency accounts with @Visa cards, while Plasma L1 focuses on stablecoin payments. - Plasma L1: Zero-fee $USDT transfers and high-throughput payments. - Plasma One: Consumer accounts and cards, with Bridge-powered accounts and Rain-issued cards. Plasma One processed $29.3M in card spend over the last 30 days, up 254.8% over 90 days. Stripe brings the card infrastructure; Plasma brings an existing product and insight into how multi-currency users spend. — — — ➤ Stripe is building the infrastructure layer Stripe's Bridge acquisition and Privy integration extend its stablecoin infrastructure beyond card issuance. - Bridge ( @Stablecoin ): Stablecoin orchestration. - @privy_io: Embedded wallets for crypto applications. Together, they help businesses launch stablecoin-powered financial products without building the entire infrastructure stack themselves. — — — The real opportunity is eliminating the FX friction between holding stablecoins and spending them across borders. If Stripe makes multi-currency routing work at scale, stablecoin cards could compete on payment efficiency, not just cashback.

Billions in TVL. Millions in token valuation. The gap between protocol fundamentals and token valuation is where things get interesting. By November 2025, @Uniswap had processed over $4 trillion in cumulative trading volume. Yet, $UNI holders had no direct mechanism to capture protocol trading fees for years. That changed in December 2025, when Uniswap activated a fee mechanism that uses protocol fees to burn UNI. Protocol growth and token value are two different things. What matters is how that growth translates into value for tokenholders. I'm looking across DeFi, RWA, and AI × Crypto for protocols where fundamentals and token valuations may be telling different stories. I'm focusing on four things: - TVL: How much capital does the protocol attract? - Fees and revenue: How much does it earn? - FDV/TVL: How does its valuation compare with its TVL? - Value accrual: How much of that value reaches tokenholders? The analysis spans five sectors, screening for potential valuation gaps. ➤ Liquid staking, restaking and DVT • @LidoFinance ( $LDO ): $24.3B TVL. The largest liquid staking ecosystem, with limited direct value accrual. • @Rocket_Pool ( ethereum:0xd33526068d116ce69f19a9ee46f0bd304f21a51f ): $1.3B TVL. A decentralised alternative to Ethereum staking. • @MarinadeFinance ( $MNDE ): $790M TVL. Solana staking with revenue-sharing mechanisms. • @sanctumso ( $CLOUD ): $2.08B TVL. Solana liquid staking infrastructure and liquidity. • @eigencloud ( $EIGEN ): $6.5B TVL. Extends Ethereum staking security to additional services. • @ether_fi ( $ETHFI ): $5.2B TVL. Liquid restaking combined with a broader product suite. • @ssv_network ( ethereum:0x9d65ff81a3c488d585bbfb0bfe3c7707c7917f54 ): $13.1B reported TVL. Distributed validator infrastructure for staking resilience. ➤ Lending and money markets • @aave ( $AAVE ): $18.5B TVL. A leading multichain lending protocol with substantial fee generation. • @Morpho ( $MORPHO ): $11.3B TVL. Permissionless lending infrastructure with institutional and RWA exposure. • @sparkfinance ( $SKY ): ~$7B combined ecosystem TVL. Lending and RWA collateral within the Sky ecosystem. • @maplefinance ( $SYRUP ): $2.8B TVL. Institutional credit and on-chain lending. • @kamino ( $KMNO ): $1.4B TVL. Solana lending and liquidity infrastructure. • @compoundfinance ( $COMP ): $1.55B TVL. Established lending markets with a different valuation profile from Aave. ➤ DEXs, aggregators and yield trading • @JupiterExchange ( solana:JUPyiwrYJFskUPiHa7hkeR8VUtAeFoSYbKedZNsDvCN ): High Solana trading activity, with approximately $1.9B in related TVL. • @pendle_fi ( $PENDLE ): Yield tokenisation infrastructure connecting DeFi yield markets with growing RWA opportunities. • @Uniswap ( $UNI ): $3.9B TVL. A major liquidity venue where token value accrual remains a key research question. • @PancakeSwap ( $CAKE ): $2B TVL. A multichain DEX with significant trading activity. ➤ Real-world assets and institutional credit • @Ondo ( $ONDO ): Multi-billion-dollar tokenised Treasury and equity exposure. • @SkyEcosystem ( $SKY ): Stablecoin and lending infrastructure supported by RWA collateral and revenue generation. • @centrifuge ( $CFG ): On-chain private credit and structured financial products. • @ethena ( $ENA ): Synthetic dollar infrastructure built around delta-neutral strategies and derivatives markets. ➤ AI × Crypto and DePIN • @opentensor ( $TAO ): Decentralised machine learning and a subnet marketplace. • @rendernetwork ( solana:rndrizKT3MK1iimdxRdWabcF7Zg7AR5T4nud4EkHBof ): Distributed GPU infrastructure for rendering and AI workloads. • @akashnet ( $AKT ): Permissionless cloud and GPU marketplace with live revenue. • @grass ( $GRASS ): Decentralised data and bandwidth infrastructure for AI training. • @origin_trail ( $TRAC ): Decentralised knowledge graphs connecting verifiable data, AI and RWA. • @virtuals_io ( $VIRTUAL ): AI agent launchpad and economic infrastructure. • @NEARProtocol ( $NEAR ): Blockchain infrastructure with AI-focused positioning and agent execution ambitions. TVL alone doesn't tell me much about a token's valuation. I want to know how much revenue the protocol generates, how that revenue is growing, and whether any of it flows back to tokenholders. That's where things get interesting. A protocol can keep growing while its token lags behind. But unlocks, emissions or weak value accrual could explain that gap. The focus is on protocols where fundamental growth outpaces token valuation, without a clear reason for the gap.

Tokenized equities are moving beyond on-chain trading, with @aave V4 on @base turning @coinbase stocks into productive DeFi collateral. The new Equities Hub lets eligible users borrow $USDC against seven tokenized stocks, backed by incentives of around 3%. The mechanics reveal how Aave is turning tokenized equities into usable on-chain credit. — — — ➤ Aave Brings Tokenized Stocks Into DeFi Lending Launched on September 25, Aave V4’s Equities Hub on Base allows eligible users to borrow USDC against Coinbase tokenized stocks. The Aave DAO approved incentives for the market on October 13. Seven supported assets include: - Apple - $AAPLc - Amazon - $AMZNc - Alphabet - $GOOGLc - Meta - $METAc - Microsoft - base:0xb200000000000000000000ab99cfa739e253872b - NVIDIA - base:0xb20000000000000000000078ee7ce2fe4908108c - Tesla - base:0xb2000000000000000000001e800a7f5189430cd0 Users can access liquidity against their equity exposure without necessarily selling their positions. — — — ➤ How Aave V4’s Architecture Isolates Risk Aave V4 separates the Coinbase Stocks market from other lending markets through an isolated Equities Hub on Base. - Hub - Consolidates liquidity and accounting. - Spoke - Defines the lending market and its risk parameters. - Collateral - Seven Coinbase tokenized stocks. - Borrowable asset - USDC. This isolation limits direct spillover from equity-specific risks, including price volatility, oracle gaps, custody issues and liquidation constraints, into unrelated Aave markets. — — — ➤ How Incentives Reshape Borrowing Economics Aave DAO-approved incentives offer around 3% on tokenized stock deposits, while eligible USDC borrowing costs are effectively capped at 3% under the subsidy mechanism. The structure lowers the financing cost of leveraged equity exposure, but its economics depend on incentives remaining active. - Stock deposits - ~3% incentive yield against a reported 0% base supply APY. - $USDC borrowing - Effectively capped at 3% while subsidies cover excess costs. - Rewards - Distributed through Merkl, but variable and subject to changes or budget depletion. — — — ➤ How Leveraged Stock Exposure Generates Yield The strategy uses borrowed USDC to increase tokenized stock exposure and earn incentives on a larger position. Deposit stocks → Borrow USDC → Buy more stocks → Earn incentives Sealaunch estimates ~5.4% yield on original capital at 3× exposure and a 1.24 health factor. This remains a modeled estimate, with leverage increasing liquidation risk if stock prices fall. — — — ➤ Coinbase Stocks Hub: Supply Outpaces Borrowing As of October 14, the Coinbase Stocks Hub held $11.33M in deposits, but that figure mixes collateral with lendable capital. - Tokenized stock collateral - ~$6.05M - USDC supplied by lenders - ~$5.28M - USDC borrowed - $2.19M - USDC still available to borrow - ~$3.08M The hub shows ~19.4% utilization because it counts stock collateral too. Measured against the USDC that can actually be borrowed, about 41% is already in use. Demand is there, but it's still small in dollar terms, which makes USDC borrowing the metric to watch from here. — — — ➤ Why Stock Market Hours Create Oracle Risk @chainlink’s equity price feeds operate 24/5, with the last available price held during weekends and holidays. Stock prices can move while oracle prices remain unchanged, creating sudden health factor changes when markets reopen and potentially triggering liquidations. Equity liquidation also depends on secondary-market liquidity and redemption access, which can be constrained when traditional markets are closed. — — — ➤ The Legal Structure Behind Coinbase Tokenized Stocks Coinbase tokenized stocks are Base-based B20 certificates representing beneficial claims on underlying shares held by Alpaca Securities LLC in segregated custody. - Issuer - Coinbase Onchain SPV Ltd. (ADGM) - Custody - Underlying shares are held in non-rehypothecable accounts. - Redemption - Secondary buyers face vesting restrictions before redemption. - Transferability - Regulation S restrictions prohibit US-person participation. These tokens provide equity exposure through a specific legal structure, so custody, redemption access and secondary-market liquidity matter when using them as Aave collateral. — — — ➤ From Tokenized Equities to Productive Capital Aave’s Equities Hub allows tokenized stocks to serve as collateral for on-chain credit, extending their utility beyond trading. Stage 1: Tokenized ownership → Represent traditional equities on-chain. Stage 2: On-chain trading → Enable transferable equity exposure within on-chain markets. Stage 3: Collateralized borrowing → Unlock USDC liquidity without selling equity exposure. Stage 4: Composable DeFi → Connect tokenized equities with lending and other financial applications. — — — ➤ Can Tokenized Equities Sustain On-Chain Credit Demand? Aave’s Equities Hub tests whether tokenized stocks can become sustainable collateral for on-chain credit. - Bull case: Organic borrowing demand sustains activity after incentives decline. - Base case: Deposits grow, but borrowing remains subsidy-dependent. - Bear case: Incentives fade, leveraged positions unwind and liquidity deteriorates. The incentive budget could last 6–11 months at $30–60M TVL, based on scenario estimates. Ultimately, sustained borrowing demand, collateral liquidity and risk performance will determine whether tokenized equities become a lasting source of DeFi credit.

I’ve looked at a lot of ways to earn yield onchain, and US housing credit is one of them. But getting exposure to it was impossible mostly because it’s been an institutional game. @NUVAFinance is changing that with HOME. It's a vault that gives eligible non-US users exposure to a managed portfolio of US home equity lines of credit (HELOCs) from Figure (Nasdaq: FIGR) and its partners, starting from 1 USDC. You get nvHOME, and the yield builds into its price, so there's nothing to claim. The numbers: ➜ 7.0% target policy rate, updated monthly ➜ First-loss buffer targeted at 5% of the vault cap ➜ Initial vault cap of $12M, with about $10M in at launch What I found most interesting is how the buffer gets funded. The loans yield roughly 9–9.8%. HOME holders are paid first at the policy rate, management fees come out next, and the rest goes into the first-loss buffer, which absorbs losses before nvHOME holders do. The buffer doesn't remove default or liquidity risk, and 7.0% is a target that can move with portfolio performance. Still, I'm curious how much demand shows up for this kind of credit once it's a few clicks away in a regular DeFi wallet. 🔗 If you want to check HOME's current rate and the vault details: nuva.finance

Most of Bitcoin's moves inside this range probably won't mean much, and the options market is a big reason why. With BTC around 83K, dealer gamma positioning leaves two clear edges. There's negative gamma lower down around 78–79K, and positive gamma higher up around 87–88K. The area in between, roughly 79K to 86K, looks more like a broad balance zone where hedging flows offset each other and trends have a harder time sticking. That doesn't mean price has to stay quiet. A move toward 86–87K or a drop back to 80K wouldn't change my read on the range by itself, even if some of those moves are sharp. I just wouldn't be too quick to treat every push inside the range as the start of something bigger. In the 87–88K area, dealers are long gamma, so they tend to sell into strength and buy weakness. That absorbs momentum and makes upside harder to extend cleanly. Down near 78–79K it flips. Dealers are short gamma there, so their hedging can move with price and make a selloff travel faster. So what matters to me is where price can actually hold. On the upside, I'd want to see Bitcoin break 86–87K and stay above it. On the downside, daily closes below 80K with continuation toward 78–79K would put the downside risk much more in focus. Until one of those happens, I'm treating a lot of the back-and-forth inside the range as noise. This is the kind of environment where people overreact to every candle and end up overtrading. If that balance starts to break, then I think the market structure conversation gets more interesting.

A year ago, tokenized stocks were still a side note next to gold on @coingecko’s RWA tracker. Over the last three months, they’ve been out-trading it almost every day. For the last post in this RWA series, I zoomed the market cap chart all the way out because I wanted to understand why so much of this growth is happening now rather than years ago. Two years ago, the tracker showed about $1.4B in tokenized RWAs and almost all of it was gold. A year ago it was around $3.6B. Today it’s about $9.4B, while the number of tracked tokens went from roughly 230 to over 2,100 in those same twelve months. The bigger change shows up in volume. Tokenized commodities, which in practice were basically gold when I looked at them in the last post, averaged about $335M a day over the last 30 days. That’s almost exactly where they were a year ago. Tokenized stocks went from about $75M a day to $673M, while ETFs went from around $5M to $174M. The 30-day average for stocks passed gold in mid-July, and they’ve traded more volume than gold on 79 of the 89 days since. The issuer view helps explain where that activity came from. Over the past week, about 40% of tokenized volume came from three issuers that only showed up on the tracker this summer: BTech Holdings, Robinhood and Coinbase. Add Ondo and xStocks, which arrived in 2025, and it’s over 60%. Tether and Paxos, the gold names that carried this market for years, are now around 30%. That makes me think the timing has less to do with tokenization suddenly becoming a new idea and more to do with a wave of new issuers finally bringing stocks and ETFs onchain at scale. Gold had years to build its market. Most of the new trading activity arrived much faster once these newer issuers showed up. There’s one more comparison on the same page I found useful. The market cap chart has a Stablecoins line switched off by default. Turn it on and everything else shrinks to a sliver next to roughly $308B. Go back along that line and stablecoins were around today’s RWA size, roughly $9.4B, in May 2020. RWAs aren’t stablecoins, and I’m not saying they’ll follow the same path. It’s just a useful reference for how small this market still is relative to something that already became a major piece of crypto infrastructure. Set the market cap chart to Max and flip the Stablecoins toggle yourself: coingecko.com/en/charts/rwa

Prediction markets are pricing a Democratic House on November 3. So I went back through all 19 midterms since 1950 to see what the S&P 500 did after each kind of result. The one being priced now historically had the flattest first month on average.

Ethena’s USDe holds $4.76B in backing, with 51.2% allocated to DeFi and institutional lending. As crypto basis exposure falls, lending introduces new liquidity risks, making redemption access and asset recovery critical. Here’s what the numbers reveal about $USDe’s backing and exit risks. — — — ➤ USDe Backing Composition @ethena’s USDe holds $4.76B in backing against approximately $4.76B in outstanding supply. • DeFi lending: 36.9% ($1.76B) • Institutional lending: 14.3% ($681M) • Liquid stablecoins: 24.9% ($1.19B) • Crypto basis positions: 17.6% ($838M) • Real-world assets (RWA): 6.0% ($286M) Lending accounts for 51.2% of backing, while the reported backing ratio remains approximately 100%, excluding the Reserve Fund. — — — ➤ Ethena's Shift Beyond Basis Trading Ethena originally generated yield through delta-neutral basis trading, combining long spot positions with short perpetual futures. Its backing has shifted, with crypto basis positions at 17.6%, lending at 51.2%, and liquid stablecoins at 24.9%. USDe supply has fallen from its $14.8B peak in October 2025 to around $4.76B in October 2026. This shift increases exposure to lending liquidity and borrower credit risk. — — — ➤ DeFi Lending Exposure Ethena allocates 36.9% of USDe backing, approximately $1.76B, to DeFi lending across: • @Aave and @Morpho • Historical exposures to @jupiter_earn and @kamino Ethena uses overcollateralized loans, conservative LTV limits and risk oversight, but withdrawals depend on available pool liquidity. For example, if $90M of a $100M pool is borrowed, only $10M remains available for immediate withdrawal, even when loans are fully collateralized. — — — ➤ Institutional Lending Exposure Ethena allocates 14.3% of USDe backing, approximately $681M, to institutional lending. Key counterparties and arrangements include: • @maplefinance • @Anchorage (through A1, Ltd.) • @FalconXGlobal ($1B facility capacity announced in August 2026) • @krakenfx Recall and redelivery timelines remain undisclosed, leaving recovery speed uncertain. Collateral protection does not guarantee immediate liquidity. — — — ➤ Backing vs Redeemable Liquidity USDe can be fully backed yet face redemption pressure if its assets are not immediately accessible. • DeFi lending: Withdrawals depend on available pool liquidity. • Institutional lending: Recovery depends on loan agreements and redelivery timelines. • Holder exits: Depend on primary redemption eligibility or secondary-market liquidity. A 100% backing ratio does not guarantee immediate redemption near $1. — — — ➤ USDe Redemption: Access and Limits Ethena's primary redemption facility is restricted to KYC/AML-verified, whitelisted Mint Users. Supported assets include $PYUSD, $USDC, $USDG, $USDT, $USDm, $USDtb and $DAI, which has lower limits. • $USDe redemption: 20M per block • $USDe minting: 200M per block • $DAI minting and redemption: 2M per block each These are contract ceilings, not guaranteed liquidity. Ethena can suspend redemptions without a 24-hour timelock, and payouts are supported digital assets, not bank dollars. — — — ➤ Secondary-Market Liquidity and the USDe Peg Most USDe holders rely on secondary markets to exit their positions. USDe trades below $1 → Authorized participants buy at a discount → Redeem for backing assets → Arbitrage helps restore the peg. This mechanism depends on executable primary redemptions and sufficient market liquidity. If either weakens, holders may face higher slippage or sell USDe below $1. — — — ➤ Reserve Fund and Transparency Ethena's Reserve Fund held approximately $62.1M in September 2026 to absorb negative protocol revenue and backing shortfalls. • New revenue allocation to the fund: 0% • Risk monitoring: @LlamaRisk, @chainlink, @htdgtl and @chaoslabs. Ethena reports weekly proof-of-reserves updates and monthly custodian attestations, but reported backing does not guarantee immediate liquidity. — — — USDe's risk profile is shifting from basis-trade exposure toward lending utilization, institutional credit and redemption liquidity. The critical variable is whether Ethena can recover backing assets quickly enough to meet redemption demand during market stress. Monitor lending utilization, liquid stablecoin reserves and institutional recall timelines to assess USDe's ability to maintain its peg.