Ideas don't need a pulse.

Investment Highlights:

• Massive TVL vs. Tiny Market Cap: Marinade Finance currently secures over 10.5 million SOL (≈$2.0 billion) in staked assets, yet its governance token MNDE has a market cap of only about $56  million – an MC/TVL ratio of roughly 0.028
• Institutional-Grade Platform: Marinade has achieved SOC 2 Type 2 security compliance and is integrated by major custodians like BitGo . In May 2025, Marinade’s institutional staking product was named the exclusive staking provider for Canary Capital’s proposed Solana Staking ETF (a two-year agreement) . If that ETF gets approved, Marinade could see a flood of institutional SOL staking demand.
• Real Revenue, Low Valuation: Marinade’s protocol revenues are on the order of $11.6  million per year, coming purely from staking yield (no retail fees). At the current token price, MNDE’s MC/Revenue is ~5×, less than half of Lido’s and about one-eighth of Jito’s. Despite proven cash flows, the market is pricing MNDE at a steep discount to peers.

1. Introduction

Bittensor (TAO) is emerging as the foundational asset of decentralized artificial intelligence—a network designed not just to secure data, but to produce intelligence itself. By combining blockchain’s incentive structure with open-source machine learning, Bittensor enables anyone to contribute AI compute and earn rewards for valuable outputs. Unlike traditional AI development, which is often siloed within large corporations or academic labs, Bittensor creates a permissionless marketplace where inference, training, and validation are decentralized and economically aligned.

The network’s launch was uniquely fair, like Bitcoin: no venture capital, no premine, and no team allocation. Every TAO in circulation has been earned on-chain. This clean distribution model is paired with an economic engine—known as Dynamic TAO (dTAO)—which governs how emissions flow to productive AI subnets. Introduced on February 13, 2025, dTAO marked a turning point in Bittensor’s architecture, turning TAO into both the economic and governance backbone of a growing ecosystem of AI modules.

Publish Date: April 21, 2025

Thesis Summary

TL;DR 📌

• Real Revenue & Rapid Growth: GEODNET is a decentralized precise positioning network (17,000+ GNSS base stations) monetizing location data. It has grown 4× year-over-year to ~$4M ARR (annual recurring revenue) and is on track for $10M+ ARR in the near term (40+ enterprise clients, $50M sales pipeline). This strong traction differentiates it from many DePIN projects that lacked early revenue.
• Tokenomics – Emissions vs. Burn: ~74 million GEOD/year are emitted as miner rewards (~12 GEOD/day × 17k stations) – at ~$0.20/GEOD, that’s ~$14.8M in annual token issuance, of which an estimated $10M/year hits the market (assuming ~70% of mined tokens sold). Meanwhile, 80% of GEODNET’s revenue is used to buy back and burn GEOD tokens. At ~$10M ARR, ~$8M/year goes to burns, nearly offsetting emissions; “net-burn parity” (full real-world revenue > token issuance) comes at ~$12.5M ARR, making the token effectively inflation-neutral.
• Capital Efficiency – Hyper-Lean Growth: GEODNET bootstrapped a global network of 17k stations with minimal spend (~$1–2M in marketing). Miners bear hardware costs (~$700 devices) but earn ~$4,000/year in GEOD rewards, yielding ~2–3 month payback. This break-even mining model drove rapid adoption at low cost – the foundation avoided tens of millions in infrastructure outlays. The result is a highly capital-efficient network (compare to traditional networks or Helium’s costly scaling with low revenue).

TLDR

• Category-Defining PayFi Network: Huma Protocol is pioneering “Payment Finance” (PayFi) by providing instant stablecoin liquidity for cross-border payments and card settlements. It has processed $4.5B+ in transactions with zero credit defaults, yielding ~$9M annualized revenue to date.
• Scalable Economics: Huma’s Total Active Liquidity (TAL) of ~$100M can realistically scale 5–10x, driving net profit of ~$20–45M to token holders at $500M–$1B TAL. The revenue model is straightforward: TAL × interest yield × net interest margin (NIM). For example, at 10–20% APY gross yield (from ~6–10 bps/day fees charged to institutions) and a ~4% NIM, $500M deployed could generate ~$20M in annual profit to the protocol.
• Undervalued vs. Opportunity: Even after a recent Binance listing (FDV ~$400M), HUMA trades at a single-digit forward P/E relative to its profit potential at scale. This is cheap given high-margin, real-yield revenues and a multi-billion dollar addressable market in global payments. Deep integrations with Circle, Stellar, Solana, and top fintech partners position Huma to capture outsized value as PayFi adoption accelerates.

GeodNet is a precise positioning network that significantly enhances location accuracy. While traditional GPS offers a general sense of location, GeodNet improves accuracy by nearly 100 times, reducing errors from several meters to just a centimeter. This enhanced precision is crucial for applications demanding exact positioning, such as self-driving vehicles, robotics, precision agriculture, and other real-time control systems where consistent operation relies on highly accurate and reliable location data. 

Standard GPS, sufficient for basic navigation, lacks the precision needed for these advanced applications. When GPS is used as a sensor in these systems, accuracy and reliability become paramount. GeodNet directly addresses these challenges by improving both the precision and the stability and resilience of GPS signals. Standard GPS often provides only an approximate location, making it unsuitable for use cases requiring pinpoint accuracy.

Compared to alternative positioning technologies like cameras and LiDAR (Light Detection and Ranging), GPS offers an efficient and cost-effective solution. These alternatives are often expensive, computationally intensive, and susceptible to environmental interference. GeoNet-enhanced GPS, however, provides an absolute position regardless of the surrounding environment. This makes GeoNet a practical and powerful choice for developers and engineers integrating automation into their systems, delivering the necessary accuracy and stability.

Disclaimer: This article was originally created for Artemis Research and is intended for informational purposes only, not as a trade recommendation. With permission from @MapleLeafCap, I am sharing this here because I believe it offers valuable insights into Raydium's activities. I have put it under a “Long” on the platform because I cannot post it without indicating a position but once again, it is not meant to be taken as financial advice.

Another reason why this cannot be taken as financial advice is because Raydium is up 80% since I started writing this article @ $1.8. Contrary to popular belief, assets should be bought low, not high. This piece thus only serves to inform, not to advice. I hope you enjoyed the time & effort I put into this.

Original Piece: https://www.artemis.xyz/research/raydium-king-of-solana-de-fi

[Link to original full post]

Executive Overview

$TrackedBio (CA: 7t1T28iMh5GsW8oTMx52x3u3M3hDbaY8psbL3rZ6BMrn)

Protocol Overview - SYMMIO

Symmio is a trustless hybrid clearing house that combines on-chain and off-chain elements to act as the communication, settlement, and clearing layer for permissionless derivatives. There are four key aspects to understand:

1. It's the first intent-based perps protocol, introducing Automated Markets for Quotes (AMFQs) as an alternative to traditional vAMM or order book models.
2. This enables liquidity sourcing from multiple venues, including other chains and CEXs.
3. It offers Derivatives-as-a-Service (DaaS) for anyone wanting to create a perps trading protocol.

Young 02/12 (gm, gm)

https://x.com/yoitsyoung

Treasure $MAGIC – 158M Mcap / 200M FDV (~13.7% of $APE)

Introduction

Geodnet is already widely used in industries where very high positioning accuracy is essential, including agriculture and construction. In farming, tractors rely on centimeter-level GPS for precise steering, planting, fertilizing, and harvesting, while spraying drones use it to apply chemicals accurately, avoid overlaps, and reduce waste. In construction, the same level of precision is used by automated machinery and drones for accurate machine guidance, site layout, and earthworks.

Traditional positioning systems usually rely on closed, proprietary hardware costing around $8,000 per unit. If a user’s location is not covered by an existing network or if no subscription is purchased, the customer must build and maintain their own infrastructure. The largest traditional competitor offers the same RTK correction service for approximately $100 per month for a single location, while Geodnet provides the same service for around $40 per month.

Penpie is a governance layer for Pendle (similar to Convex for Curve). I believe it is set to go on a run soon for the following 3 reasons: 1. Pendle Adoption Pendle is potentially the biggest defi success story of this cycle (at least in the ethereum ecosystem). Over the past 6 months, Pendle has seen: - TVL growth from 270 mil to 6,581 mil: - Daily trading volume from low 7 figs to low-mid 9 figs: - Almost 5x price appreciation: Pendle has found true product market fit with the points trading meta, a meta which I don’t forsee changing anytime soon (most point programs that have finished season 1 continue with a season 2). Defi natives are now comfortable with yield trading, a huge milestone for a sophisticated defi product like Pendle. Pendle has essentially no significant competition in the yield trading space (although some other existing/new protocols are targeting the space, such as apw, ipor, napier). It has also begun to expand beyond L1 and Arbitrum (it’s recent Mantle deployment specifically has received a lot of attention). Pendle is obtaining the reputation as a “kingmaker” for defi protocols and L2s. Pendle is clearly a new defi blue chip. Despite that, it is not even in the coingecko top 100 yet (currently number 106). It has a market cap of 856 mil MC and a 1.42 bil FDV. As the clear leader in a rapidly growing sector of defi, I expect Pendle to continue to perform well. This is especially true with the eth ETF providing tailwinds for eth defi. 2. Relative Value Pendle utilizes Curve style ve-tokenomics, wherein vePendle lockers receive additional yield for their Pendle farms and can also vote on the distribution of Pendle incentives. Penpie is a governance aggregation layer built on top of Pendle that utilizes its treasury vePendle to boost yields on its Pendle pools as well as generate bribe revenue. Penpie’s most obvious comparison is to Convex. Convex currently holds the following governance power, which totals to approximately $258 million, while trading at a market cap of $195 million. Similarly, Penpie (PNP) controls about 12.6 million vePendle, which is about $69 million, while trading at a market cap of $17 million. Comparing these two projects, we can see that Penpie is trading at a significant discount to Convex on a market cap / treasury ve-token value basis. I believe the reason for the relative discount is largely explained in item 3 below. 3. Dramatic Change in Supply Dynamics Penpie has underperformed Pendle, but this dynamic is beginning to shift. I believe this relative underperformance is largely caused by PNP supply dynamics. Penpie launched on June 19, 2023. During its first year of trading, its supply is inflating rapidly (see above graph). The majority of this inflation comes from IDO participants, who are currently receiving about 1.17% of total supply (or about $375k at current price) per month. When combined with the liquidity mining and pendle rush (incentivization for people to lock vePendle with Penpie) allocations, about 1.93% of total supply is likely hitting the market per month. Starting June 20th, 2024 (in ~2 weeks), the rate of inflation that is expected to hit the market each month decreases dramatically from about 1.93% to about 0.58%. After this date, inflation will come only from the Magpie Treasury allocation (sits in Magpie treasury to earn yield for magpie holders but will not be sold), marketing/BD (assume most won’t be sold), and liquidity mining (assume all is sold). This is a reduction from about $616k a month to $187k a month at current prices (into a $2.2 million liquidity pool). This is a dramatic shift in supply dynamics and the main reason I’m excited about this trade. Risks: vlPNP (PNP locked to earn yield...currently ~14%) can be unlocked at any time with a 60-day cooldown. As ~61% of circulating PNP is currently locked, this has the potential to represent a large supply event. That said, it is easy enough to monitor the vesting details to see when large amounts will be vested. For example, currently a total of 182k PNP are expected to be unlocked over the next 60 days. Most of this unlocking supply is to these two wallets: https://debank.com/profile/0xec448f4b62b502ae3343205eecda588f3d7b4b20 https://debank.com/profile/0xee439ee079ac05d9d33a6926a16e0c820fb2713a Another risk is this wallet, which holds ~$1.5 mil of liquid PNP. A good wallet to put on alert if you are a PNP holder. https://debank.com/profile/0x4c8be1d302f60434574ed21a007a8ac0bb24e2bf Conclusion Given the Eth ETF tailwind, the point meta, and the virtual monopoly that Pendle has on the yield trading sector, I expect Pendle will continue to perform well. I believe Penpie is undervalued currently due to its extreme rate of inflation. That rate of inflation will decrease quite dramatically in about 2 weeks. For these reasons, I believe PNP is a good small cap beta play for Pendle. Resources https://dune.com/beaconearly/penpie https://dune.com/beaconearly/pendle-wars

Only Possible On Solana The saying “only possible on solana” or “OPOS” is a testament to the many advantages Solana has when it comes to decentralized application development. Its fast, cheap transaction fees and smooth UX unlocks capabilities many couldn’t envision 1-2 years ago. In the DEX space specifically, Solana’s efficiency has given rise to concepts such as automated liquidity strategies (Kamino), orderbooks (Phoenix) and aggregators (Jupiter) - ideas that have been tried elsewhere but with minimal success due to scaling limits. One ingenious DEX that utilizes the strengths of Solana’s scaling capabilities and extensive ecosystem better than anything else is Lifinity. And it seems to have gone somewhat under the radar, despite unbelievable capital efficiency and earnings. The oracle-based AMM Lifinity is the creation of Luffy and Zoro, two developers with a combined 28 years of product experience and 6 years of market making experience. Like most DEXs, Lifinity applies liquidity to an automated, concentrated xy=k model as opposed to an order book with market makers. However, unlike most DEXs, it does not rely solely on the xy=k curve to determine prices, but rather uses oracles to prevent the impermanent loss dilemma that plagues AMMs today. To further illustrate, below is an excerpt from Lifinity’s debut medium post. The critical drawback of AMMs is impermanent loss, which is a symptom of their dependence on traders adjusting their price rather than them determining their own price the way a market maker would. This creates a dynamic where an AMM’s price routinely lags the market, enabling arbitrageurs to capitalize on the spread at the expense of the liquidity providers. But by basing prices via oracles rather than its pools’ ratio of assets, Lifinity is able to offer prices in line with the market, preventing arbitrageurs from eating their lunch, so to speak. What does this enable? Oracle-based pricing allows Lifinity to apply algorithmic trading concepts that emulate the methods market makers use. Done right, they can go from getting their lunch eaten by arbitrageurs to eating the lunches of their biggest competitors, Raydium and Orca. To understand how this works, we first need to understand how most orders on Solana are executed. Unlike other ecosystems, where users trade directly on a DEX like Uniswap, most traders on Solana use a DEX aggregator called Jupiter. Jupiter, because of Solana’s cheap fees, is able to split up transactions and execute them across multiple DEXs to give traders the best prices with the lowest slippage. Jupiter itself is an example of OPOS. What this means is DEXs don’t have to source their own volume, but instead have to directly compete with one another to offer the best prices with the lowest slippage. This allows Lifinity to use its informational advantage via oracles to “outsmart” and frontrun its competitors. How Lifinity does this is by comparing the price of the oracles to the price of other AMMs (Raydium, Orca) to not only match the oracle price, but position themselves on the opposite side of the amms. Typically, in a scenario where SOL is falling in price, traders are net selling their SOL for USDC causing AMMs to accumulate SOL as the price depreciates. Lifinity on the other hand, adjusts their price of SOL to be lower than other DEXs so that sellers get the worst rate and buyers get the best. This means that as traders make moves on Jupiter, only the buy trades route through Lifinity, while the sell trades route through the other DEXs. Therefore, Lifinity accumulates USDC rather than SOL, inversing the AMMs. Once the selling is over and the price settles, the oracles and AMMs once again show similar prices. At this point, Lifinity has significantly more USDC than SOL in its pool and has to rebalance to a 50:50 ratio, meaning it buys SOL at its potential pico bottom. This allows Lifinity to have both more USDC and SOL than before as it bought SOL at a lower price than it sold at. If SOL then rebounds, Lifinity does the opposite and offers buyers the worst price and sellers the best price, allowing it to wholly earn the price appreciation of its newly bought SOL while accumulating SOL rather than USDC. The profit it earns through this process is labeled “market making profit” (MMP). To further illustrate this point, below is an excerpt from its initial testing results in February, 2022. As mentioned elsewhere in the test results, AMMs are typically short volatility as they accumulate the worst performing asset between the pair. However, Lifinity is long volatility as it accumulates the best performing asset and frontruns the AMMs the way an arbitrageur would. Performance/Traction If you look through its monthly updates and pool aprs, the returns are consistently staggering. Lifinity not only routinely outperforms other AMMs, but outperforms holders of the pool’s assets, even when excluding the trading fees it earns. Below is a graph showing Lifinity’s primary SOL-USDC liquidity pool performance vs holding 50% SOL and 50% USDC. This pool, in less than a year and a half, has managed to 13x in performance vs the holdings themselves. Furthermore, with its unique mechanisms, it’s able to maintain incredibly thin liquidity ranges, so much so that it’s achieved $20B in volume YTD with less than $20m in TVL, setting a new bar for capital efficiency. In fact, it’s so efficient that its sol-usdc pool is Jupiter’s most used pool seeing well above $500m in weekly volume. Its sol-usdt pool is 4th, well above any other sol-usdt pool in Solana. Tokenomics - Protocol Owned Liquidity The Lifinity team could’ve concluded their vision at “oracle-based AMM” and called it a day. However, they addressed another crippling failure of today’s DEXs that turns Lifinity from a great product to a great investment. Today’s DEXs have terrible tokenomics. The reason they release tokens is to boost yield for their liquidity providers (LPs). By boosting yield, they can help LPs overcome their impermanent loss and can attract further liquidity by providing better yield than other DEXs. This obviously creates an unsustainable model where the DEX needs to keep emitting tokens to sustain liquidity. This also makes it difficult for DEXs to take a cut of the trading fees as LP’ing is already on razor thin margins. Fortunately for Lifinity, it doesn't suffer from impermanent loss, at least not to the degree of their competitors. So it doesn't need to inflate its token to remain afloat. Furthermore, because of its tight spreads and rebalancing mechanism, it doesn't need a lot of liquidity to offer competitive prices. Because of this, Lifinity is able to do two things. First, it doesn’t source liquidity from LPs but rather owns its own liquidity, known quite simply as protocol owned liquidity (PoL). By doing so, it earns all of the trading fees instead of having to share it with liquidity providers. Second, its token, $LFNTY, is not an inflationary, yield boosting product, but a fundraising tool with sustainable utility. In order to raise the funds to provide its own liquidity, it sells its tokens at a discount with a vesting schedule. With the trading fees it earns using the liquidity, 50% goes to stakers of the token, 40% goes to token buybacks and 10% goes to the team, giving $LFNTY a clear, sustainable value accrual mechanism. With the market making profit it earns, the proceeds initially are reinvested into the pools to increase liquidity. However, once tvl reaches a certain point where additional liquidity produces marginal gains, the excess will be realized as earnings and distributed similarly to the trading fees. Of the 100M tokens, 20M were sold at TGE to bootstrap the initial liquidity. Another 20M was allocated to the team, 1M to Lifinity’s NFT collection and 59M to the DAO. There is no VC involvement/allocation. At the moment, 35M tokens are circulating, of which, 27M are staked using a vote escrow (VE) model to earn the trading fees. Despite the 3:1 FDV to market cap ratio, the inflation rate is minimal, limited only to the team’s allocation, of which 11M tokens remain unvested. The DAOs holdings, currently 52M LFNTY, is reserved for raising further liquidity in order to increase scale. In the event where a fundraise takes place, inflation would be offset by a significant increase in book value and its ability to process more volume. Therefore, I believe token inflation is a negligible concern and could contrarily drive price appreciation as the emissions would directly improve the project’s fundamentals. Price analysis Determining a fair valuation for Lifinity is relatively straightforward. Just figure out the fees it earns, annualize them, and compare them to the price to get an estimated P/E. The main complexity comes from whether market making profit should be considered as earnings when it’s being reinvested as opposed to distributed to holders. Although traditionally it would be included as retained earnings, Lifinity doesn’t include it in its revenue metrics so I won’t either. The current price of LFNTY on April 30th, 2024 is $1.40 with a market cap of $50M and FDV of $140M. Year to Date, as shown in the graphic below, Lifinity has earned $4.9M in trading fees, which annualizes to $14.7M. If we account for 10% of the revenue going to the team, that leaves $13.2M in earnings accrued to holders via yield and buybacks. When compared to the market cap, this nets a P/E of 3.79. When compared to FDV, the P/E is 10.61. Considering the growth potential of Solana DeFi, the prospect of earning excess market making profit and the ability for token emissions to accrue value to the protocol, LFNTY seems heavily undervalued. Catalysts - When Solana Wins, Lifinity Wins Big The “Only Possible on Solana” narrative has been a prominent one over the last year, and Lifinity is a great example of that. Not only is it only possible on Solana, it also makes money from every narrative that Solana sees. During the recent meme coin run, Lifinity was a top 3 DEX for both WIF and BONK. Furthermore, often when traders bought a meme coin on Jupiter using USDC, Jupiter would first route through Lifinity to swap to SOL before purchasing the memecoin. As mentioned earlier, Lifinity’s SOL-USDC pool remains as Jupiter’s most used pool across all AMM’s. This means as Telegram bots, AI agents and now Coinbase themself integrate Jupiter in their backend, they’re integrating Lifinity. It is the ultimate pick and shovel in Solana. Catalysts - Pendle on Solana One overlooked development that’s being closely guarded by Solana bulls is the upcoming launch of a Pendle on Solana. With Sanctum’s recent breakthrough in LST liquidity, allowing for validator specific LSTs, demand for yield trading is growing. And once again, the Lifinity team is there to capture the value, as they are the ones building the Pendle on Solana, known as Sandglass. Currently in beta, Sandglass is using a portion of Lifinity’s POL to bootstrap their first pool, mSOL, and conduct testing. In return for using this liquidity, the team plans to reward Lifinity holders, presumably via a portion of Sandglass’s tokens. The current FDV of Pendle is $1.1B with a TVL of $4.1B. If Sandglass is able to capitalize on Sanctum’s momentum and amass significant TVL, it should be able to attain a strong FDV and reward LFNTY holders handsomely. Limitations Although Lifinity is, in my opinion, an s-tier project, it’s not without its drawbacks. The first is its dependance on oracles. Although Pyth is as reliable as it gets in the industry, it and other oracles are subject to mispricings, especially when market manipulation or low liquidity assets are involved. In general, I’m of the opinion that oracle-based products are easier to game than oracle-less ones. The second is the rise of order books within the Solana ecosystem. Because of Solana’s speed and affordability, order books are more viable than in other ecosystems. And we’re beginning to see their prevalence with Open Book and Phoenix. The problem order books pose for Lifinity is that they’re much more efficient than Orca and Raydium. Right now, Lifinity earns much of its revenue through market making profit, where it skews its prices to take the other side of its competition’s losing trades, aka impermanent loss. But if it has to compete with order books and the professional market makers that utilize them, it could have a difficult time outcompeting. My expectation is that AMMs will continue to see the majority of DEX volume for the next 1-2 years, especially with swaps, however as order books increase in market share, Lifinity’s market making profit may deteriorate. I expect its volume and trading fees to maintain their trajectory, however. Conclusion When analyzing the “only possible on Solana” narrative, it’s important to look for projects that utilize Solana’s capabilities to unlock new mechanisms and its ecosystem to position themselves for meteoric success. Lifinity may be the best example of that. Lifinity’s repricing and rebalancing mechanisms, alongside its industry leading capital efficiency are only possible through the efficiencies of Solana and Pyth. It also takes advantage of the most effective and dominant DEX aggregator to capitalize on DeFi’s biggest inefficiencies - impermanent loss and poor liquidity management. And then through thoughtful, innovative tokenomics, it brings those benefits to the holders. As Solana continues to prove the naysayers wrong, positioning itself for mass adoption, Lifinity will be there to make the most of it.

This is a discretionary long investment thesis on Mariande Finance. The opinions expressed are my own and not influenced by Outlier Ventures. This investment thesis does not constitute investment advice. Parts of this were written with the help of AI language models to improve clarity and save time. The thesis is written using publicly available, non-material information.

Written: July 22, 2025 | Published: Aug 7, 2025

Executive Summary

EXECUTIVE SUMMARY TON is a Proof-of-Stake blockchain indirectly backed by Telegram Inc through the TON Foundation. It boasts horizontal scaling through a schema called infinite dynamic sharding and as a result managed in a test environment to garner over 100k tps (vs Solana 60k). We believe the native token for this chain is currently undervalued given its: 1. Concentrated Supply and Scarcity Value in being a Comparatively Underowned L1 2. Sound Circulating Tokenomics 3. Clear Go-to-Market Strategy and Greenfield Growth Opportunities 4. Plenty of Greenfield Growth given Current KPIs 5. Tangible Crypto-Specific Catalysts I. CONCENTRATED SUPPLY AND SCARCITY VALUE IN BEING AN UNDEROWNED L1 After a shakey start following an SEC run-in between 2018-2020, TON was relaunched and by June of 2020 all TON coins became available for mining via ‘Giver’ smart contracts using a Proof of Work (PoW) system, with CPU mining continuing from 2020 to 2022. We note that whilst this distribution method was meant to promote decentralisation and increase fairness, research clearly indicates that a vast portion of the supply was mined by insiders or TON-foundation related addresses, with only 248 strongly connected addresses mining 85% of the coins in a space of 2 months (Jul-Aug 2020). Token Distribution by Giver Smart Contract Type Large Miner Groups Split by Mining Duration TON therefore has a lower float than advertised given that ~50% of the supply locked in both the Believers Fund (see below) and inactive miner wallets. Given the nature of the launch, nearly ~86% of mined coins are controlled or at least affiliated to the TON foundation. Couple this with the fact that majority of attention as well as locked OTC coin investments were done by Asian participants suggesting that EU/US participants are offside - TON therefore makes for a great opportunistic long. (See figure below for cumulative futures returns) The large run up over the last few months was fundamentally Asia driven From a technical perspective, the coin is now trading between 2-3x from the start of the year and the 2023 lows. Compared to gains in similar comps such as SOL, AVAX and NEAR, the run up has been fairly muted which allows for much more defined downside risk. SOUND TOKENOMICS IN A SEA OF LOW-FLOAT, OVERVALUED NEW LAUNCHES Fundamental to the thesis are the sound tokenomics featured. Whilst the valuation is relatively high at FDV $24bn and circulating market cap of $16bn, the large supply currently tightly held by TON foundation and affiliates, the low inflation rate for validating the network and the methodical OTC sales used to distribute supply to investors are positives. The current total supply is 5,105,734,318 (5bn issued at launch) with an initial split of 85% tokens to users and 5% to validators. The chain inflates at a rate of 0.6% annually, with the rewards being paid to validators to maintain consensus. Digging a little deeper, we note that ~1.3bn coins are in the Locker Smart Contract (named the Believers Fund), locking over >20% of TON supply until 12 Oct 2025, vesting every month for another 3 years post cliff period. The total comprises ~1 billion TON locked by users and 284 million TON donated for rewards. Locker Smart Contract on TON In addition to the locker contract, the TON foundation also deactivated ~1.1bn TON held by large early miner wallets that have not had a single outgoing transaction for 48 months. The result of both of these initiatives is the removal of ~47% (2.4bn coins) TON’s supply from circulation for the foreseeable future. Effective circulating market cap therefore is ~$8.5bn. On the other hand, it is much harder to place a dollar value on the amount of locked OTC coins that have been sold however, based on public announcements there seems to have been at least $30m worth of tokens at least that have been sold to venture and professional investors: MEXC Ventures making an ‘eight figure’ investment in TON - October 2023 Animoca Brands invests in TON Network becoming the largest validator - November 2023 Mirana Ventures backs TON coin with $8m - March 2024 Pantera ~$250m - May 2024 Given that TON remains in a nascent stage in terms of adoption, the coin has a somewhat weak value accrual narrative around it. However, this should pick up as on-chain activity continues to grow through the burn mechanism in which 50% of all TON fees are burned. Fee Burn Mechanism akin to EIP-1559 Live on TON More importantly, Telegram is actively developing utility features for the TON token, which serve as "token sinks" to enhance its value. For instance, Telegram recently announced that it will exclusively use the TON token for ad payments. In this setup, advertisers fund their marketing campaigns using TON, with revenues being split equally between Telegram and content creators. Additionally, Telegram has begun to accept TON for payments related to Telegram Premium, which boasts 5 million subscribers, through the Fragment Store,. These initiatives demonstrate a deliberate effort by the Telegram team to ensure that TON remains a token with practical utility and clear mechanisms for value accrual directly linked to Telegram’s services. CLEAR GO-TO-MARKET STRATEGY AND GREENFIELD GROWTH OPPORTUNITIES TON’s grand vision of building the Web3 SuperApp straight from the convenience of your own phone can potentially compete with WeChat. This marks a fundamental shift away from the status quo of the slew of crypto blockchains and DApps serving speculators and the tech savvy, which by their very nature are a much smaller TAM and as a result should garner lower valuations. TON has also garnered strong backing by Tether with their integration announcement and of course de facto backed by Telegram with a robust roadmap across TON Blockchain, TON Proxy, TON Payments and TON Storage. Goal of the Open League Incentive Programme is to Funnel and Maintain a Sticky On-chain TON User-base Whilst traction thus far has been immense, there is considerably more potential for growth given that currently there are ~3.5m on-chain activated wallets compared to Telegram boasting 800 million monthly active users (MAUs), with projections to reach 1.5 billion in the next five years. This represents a substantial yet natural upper bound total addressable market (TAM). TON Foundation is strategically aiming to onboard 30% of Telegram’s MAUs within the next 3-5 years. If Telegram manages to convert even 0.2% of its 200m daily active users), it would surpass Ethereum's current DAU count of approximately 400,000. There’s clearly a huge opportunity for user base expansion. The result of TON Foundation’s current efforts is an increase in block-chain activity across all metrics including (see figures below): Transactions increased by 10x: Since March 2024 transactions have ranged between 2-4m tx/day up from 200k tx/day last year Number of on-chain activated wallets increased by 3.6x: From 600k addresses in January 2024 to 3.5m in end of April 2024. Daily Active Wallets (DAWs) increased to six figures: DAWs are now ~160k up from 30k earlier this year TON fees per day ranging between $50k-$250k: Half of the TON fee is burned CRYPTO-SPECIFIC POSITIVE CATALYSTS TON has been doing daily $170m+ of volume over the past few months, a spot Binance listing could derisk the investment significantly and provides some upside as well as more downside protection given increased liquidity. Also as ETH continues on its sharding roadmap expect TON to gain further mindshare, given its dynamic sharding architecture, although this is more of a tenuous narrative trade. RISKS AND MITIGANTS Questions surrounding whether the project can sustain its current valuation. It’s an ambitious project that seems to be almost fully valued. At these levels, the chain and native gas token should act as money rather than as a vehicle for tech speculation. Monetary premiums are much harder to obtain than tech premia which are inherently more fleeting. Details around TON’s OTC deals would need to be explored further as funds that could potentially be marginal price setters opt into buying discounted OTC tokens instead, reducing open market buy pressure Developer engagement is lower than other chains given the somewhat esoteric programming language (FunC) with 39 FT developers, and around 120 monthly active Devs. By comparison ETH has 2.4k FT devs and 7.8k monthly active developers.. Supply unlocks with the Believers Fund beginning to unlock October 2025 albeit this vests over the course of three years. * Regulatory risk remains a factor. However, we believe much of that has been derisked given the prior run in with the SEC. Telegram are clearly looking to integrate the token into the platform, there is a reasonable expectation that Telegram has conducted thorough legal due diligence to ensure that their current and future operations with TON abide by necessary legal rules.. N.B. I wrote a full piece on TON originally mid-late April, and all numbers are correct at that time. I think TON is still pertinent two months on given it is my belief that it is a full cycle hold or at least until locked coins begin vesting (post October-2025). Hence I am presenting this summarised outlook as my application to BidClub. The full article can be found here: https://mirror.xyz/0x0d2065e3Ed3E36919b2AD12FDA8E428Da91bb28D/EJvHq4OqZqhtuqbF0zhRNl5ZQRYFa6U9rdRI1bIQ6yA

The Hidden AI Infrastructure Play: Boring Monopolies in an Extraordinary Era

Investment Thesis: Southern Company, Duke Energy, and Waste Management

A contrarian deep-dive into the AI revolution's most overlooked beneficiaries

October 11, 2024Jonah Weinstein

We introduce a novel “monetary store of value” (MSOV) framework to value native tokens of Layer 1 blockchains. Our framework implies that at today’s prices, Ethereum (ETH) and Solana (SOL) are expected to grow their MSOV totals by $142 billion and $85 billion respectively, as they currently trade at 2.1x and 6.7x multiples to their MSOV totals. We hope this paper can be a resource to help investors understand long-term value drivers and implied expectations for Layer 1 (L1) tokens.

Executive Summary Akash is a decentralized compute marketplace that aims to connect underutilized GPU supply with users that need GPU compute, with the goal of becoming the “Airbnb” for GPU compute. Unlike other competitors, they are largely focused on general purpose, enterprise-grade GPU compute. Post their GPU mainnet launch in September 2023, they have gotten to 150-200 GPUs on their network reaching 50-70% utilization, annualizing at $500K-1M of GMV. In-line with internet marketplaces, Akash charges a 20% take rate on USDC payments. We are at the start of tectonic shift in infrastructure, with a shift to parallel processing driven by GPUs. Artificial intelligence is forecasted to add $7 trillion to GDP while automating away 300M jobs. Nvidia, which makes the GPUs that power these AI workloads, is forecasted to ramp revenues from $27B in 2022 to $60B in 2023 and to ~$100B in 2025. Cloud hyperscaler (AWS, GCP, Azure, etc.) capital expenditures on Nvidia chips have grown from mid-single digits to 25% today and are expected to reach 50%+ over the next few years. (Source: Koyfin) Morgan Stanley estimates that the GPU Infrastructure-as-a-Service (IaaS) opportunity for hyperscalers will reach $40-50B by 2025. Illustratively, if 30% of GPU compute is resold through secondary marketplaces at a 30% discount, this would be a $10B revenue opportunity. Adding in another $5B revenue opportunity from non-hyperscaler sources, that would be $15B revenue opportunity. Assuming Akash is able to capture 33% market share of the opportunity ($5B of GMV) and at a 20% take rate, this would translate to $1B of net revenue. Applying a 10x multiple yields a nearly $10B market cap outcome. [1] Market Overview When OpenAI launched ChatGPT in November 2022, it set the record for the fastest growing user base, hitting 100 million users by January and 200 million users by May 2023. The ramifications were enormous, with estimates of a $7 trillion increase to GDP through productivity increases and automating away 300 million jobs. AI quickly emerged from a niche area of R&D into the biggest spending priority for companies. The cost of creating GPT-4 was $100M and cost $250M to run annually. GPT-5 required 25,000 A100 (equating to $225M of Nvidia hardware) and likely $1B of total hardware investment. This created an arms race among companies to secure enough GPUs to power AI-driven enterprise workloads. This AI revolution has ushered in a tectonic shift in infrastructure, accelerating the move from CPUs to parallel processing with GPUs. Historically, GPUs have been used to render and process images simultaneously at scale while CPUs, which are designed to run serially, could not. With high memory bandwidth, GPUs evolved to tackle other calculations with parallel problems, such as training, refining and improving AI models. Nvidia, which pioneered GPUs in the 1990s, has combined best-in-class hardware with its CUDA software stack, building a multi-year lead versus the competition (largely AMD and Intel). Nvidia’s CUDA stack, developed in 2006, allows developers to optimize Nvidia GPUs to accelerate their workloads while streamlining GPU programming. There are 4M CUDA users and over 50K+ developers working on CUDA, with a robust ecosystem of programming languages, libraries, tooling, apps and frameworks. We expect Nvidia GPUs will flip Intel and AMD CPUs within the data center over time. The hyperscalers and big tech are rapidly spending more on Nvidia GPUs, ramping from low-single digit percentage of capex in early 2010’s to mid-to-single digit in 2015-2022 to 25% in 2023. We believe Nvidia will represent 50%+ of cloud capex spend in the next few years. This is expected to catalyze Nvidia’s revenue from $25B in 2022 to $100B by 2025 (Source: Koyfin). Morgan Stanley has sized the GPU IaaS opportunity for the hyperscalers at $40-50 billion by 2025. This is a still a fraction of total hyperscaler revenue, with the three largest hyperscalers doing ~$250B+ of revenue today. Given the strong demand for GPUs, there has been a massive supply shortage of GPUs, which has been well-documented by the New York Times and Wall Street Journal. AWS CEO has said “demand is outstripping supply, and that's true for everybody”. Elon Musk said on 2Q23 Telsa earnings call “We'll continue to use -- we'll actually take Nvidia hardware as fast as Nvidia will deliver it to us”. Index Ventures has resorted to buying chips for its portfolio companies. Outside of the major tech companies, it is nearly impossible to buy chips from Nvidia and there are long wait times to access chips from hyperscalers. Below highlights the GPU pricing at AWS and Azure. As shown below, reserving for 1-3 years yields discounts of 30-65%. As hyperscalers are investing billions of capex ramping capacity, they are looking for revenue visibility to make those investments. Customers are better off paying for 1-year reserved pricing if they expect 60%+ utilization and 3-year if they expect 35%+ utilization. Any unused capacity that they could resell would dramatically reduce their overall total cost. If hyperscalers build a $50B business leasing GPU compute, there will be a significant opportunity to resell unutilized compute. Assuming there is 30% capacity to resell at a 30% discount, that is a $10B market reselling hyperscaler GPU compute. However, there are other sources of supply as well outside the hyperscalers, whether large enterprises (e.g. Meta, Tesla), private competitors (CoreWeave, Llambda, etc.) as well as well-funded AI startups. From 2022 to 2025, Nvidia would have generated ~$300 billion of revenue. Assuming there is $70B of chips outside of hyperscalers at a 20% capacity to resell at a 30% discount, that adds another $10B to the TAM, totaling $20 billion. Akash Overview Akash is a decentralized compute marketplace that was founded in 2015 and launched mainnet in September 2020 as a Cosmos app chain. The vision was to democratize cloud computing by offering underutilized compute priced significantly cheaper than the hyperscalers. The blockchain handles coordination and settlement, storing records of requests, bids, leases and settlement, while execution is done off-chain. Akash hosts containers where users can run any cloud-native application. Akash is built with a set of cloud management services including Kubernetes to orchestrate and manage these containers. The deployment is transferred from a private peer to peer network isolated from the blockchain. The first iteration of Akash was focused on CPU compute. At its peak, the business scaled to ~$200K annually of GMV and had 4-5K CPUs leased. However, the two largest pain points were onboarding (having to spin up a Cosmos wallet and pay for workloads in AKT tokens) and churn (had to fund a wallet with AKT and if AKT ran out or prices changed, the workloads went down with no backup provider). Over the last year, Akash has transitioned from focusing on CPU to GPU compute, taking advantage of this paradigm shift in computing infrastructure and the supply shortage. Akash GPU Supply Side Akash’s GPU network went live on mainnet in September 2023. Since then, Akash has scaled to 150-200 GPUs reaching 50-70% utilization. Below compares the price for Nvidia A100 with several of the leading providers and Akash is 30-60% cheaper than the competition. There are around 19 unique providers on Akash network across 7 countries supplying over 15 types of chips. The largest provider is Foundry, which is a DCG backed company that also does crypto mining & staking. Akash has largely been focused on enterprise grade chips (A100s), which have been traditionally used to power AI-workloads. While they have also offered some consumer grade chips, those have been historically difficult to use for AI due to power, software and latency issues. There are several companies, such as FedML, io.net and Gensyn that are trying to build an orchestration layer that will allow for AI edge compute. As more and more of the market moves to inference vs. training, consumer-grade GPUs could become more viable, but today the market is largely centered around training with enterprise grade chips.. On the supply side, Akash is focused on public hyperscalers, private GPU providers, crypto miners and enterprises that hold underutilized GPUs. •Public hyperscalers. The biggest unlock would be for the public hyperscalers (Azure, AWS, GCP) to allow their customers to resell unutilized capacity to the Akash marketplace. This would allow them to have revenue visibility to make their capital investments. Once one hyperscaler allows this, the others would likely need to follow to maintain competitive share. As mentioned earlier, hyperscalers will likely have a $50B IaaS opportunity, creating a large resale opportunity for Akash’s marketplace. •Private competitors. In addition to the public hyperscalers, there exists several private companies (CoreWeave, Lambda Labs, etc.) who also lease GPUs. Given the competitive dynamics with hyperscalers attempting to build their own ASICs as alternative hardware, Nvidia has shifted more of their supply to some of these private companies. The pricing at the private competitors are often cheaper than the hyperscalers (e.g. A100 up to 50% cheaper). CoreWeave, which is the most high-profile private competitor, was once a crypto mining company that pivoted to building data centers and offering GPU infrastructure in 2019. They are raising at a $7 billion valuation and is backed by Nvidia. CoreWeave is growing rapidly, generating $500M of revenue in 2023 and expecting $1.5-2B of revenue in 2024. CoreWeave has 45K Nvidia chips and estimates show that these private competitors could have a total of 100K+ GPUs. Enabling a secondary marketplace to their customer base could allow these private competitors to gain share versus the public hyperscalers. •Crypto miners. Crypto miners have historically been large consumers of Nvidia GPUs. Given the computational complexity of solving cryptographic proofs, GPUs had emerged to be the dominant hardware for Proof-of-Work networks. As Ethereum moved from Proof-of-Work to Proof-of-Stake, this created a lot of excess capacity. ~20% of the freed-up chips are estimated to be able to be repurposed for AI workloads. Furthermore, Bitcoin miners are also looking to diversify their revenue streams. Over the past few months, Hut 8, Applied Digital, Iris Energy, Hive and other Bitcoin miners have all announced AI/ML strategies. The largest supplier on Akash is Foundry, which is one of the largest Bitcoin miners. •Enterprises. As shown before, Meta has one of the largest stockpiles of GPUs with 15,000 A100s with 5% utilization. A Similarly, Telsa also holds 15,000 A100s. Enterprise compute utilization is typically <50%. Given the amount of venture funding into the space, a lot of AI/ML startups also have bought ahead of their chip consumption. Being able to resell unused capacity will reduce the total cost of ownership for these smaller companies. Interestingly enough, there is also a potential tax advantage of leasing old GPUs and tax harvesting the depreciation versus selling older chips outright. Akash GPU Demand Side For most of 2022 and 2023, prior to the launch of the GPU network, CPU GMV had been ~$50K annualized. Since the launch of the GPU network, GMV has reached $500K-1M annualized with 50-70% utilization of GPUs on the network. Akash has been working on reducing user friction, improving user experience, and broadening use cases. •USDC Payments: Akash has recently allowed stable payments in USDC such that customers are no longer subject to the friction of buying AKT and the price volatility of holding AKT until payment. •Metamask Wallet Support: Akash has also implemented Metamask Snap for easier onboarding versus spinning up a Cosmos specific wallet. •Enterprise Level Support: Overclock Labs, the creators of the Akash Network, has launched AkashML, a frontend to make it easier to onboard users onto the Akash network with enterprise level support. •Self-Serve: Cloudmos, recently acquired by Akash, has also launched an easy-to-use self-serve interface for deploying GPUs. Previously, deployments had to be done through command line code. •Choice: While the focus has predominantly been on Nvidia enterprise-grade chips, Akash also offers consumer grade chips and, as of late 2023, added for support for AMD chips Akash is also proving out use cases with the network. During GPU testnet, the community demonstrated that it could use the network to deploy and run inference on many popular AI models. Both the Akash Chat and Stable Diffusion XL applications showcase the ability of Akash to run inference. We believe that over time, the inference market will be significantly larger than the training market. Today, the cost of an AI powered search is $0.02 (10x higher than Google’s current cost). Given there are 3T searches a year, this would be $60B annually. To put that in context, the cost of training an OpenAI model was ~$100M. While costs will likely go down for both, this highlights the significant difference in revenue pools longer term. Given most of the demand for high end chips today is on training, Akash is also currently working on showing they can use the Akash network to train a model, with a goal to launch the model by early 2024. After using homogenous chips from a single vendor, the next project will be to use heterogenous chips from multiple vendors. The roadmap for Akash is robust. Some product features that are being worked on include secret management support, on-demand/reserved instances and better discoverability. Tokenomic and Incentives Akash charges 4% for payments in AKT and 20% in USDC. The 20% take rate is similar to what we have seen in traditional internet marketplaces (e.g. Uber 30%). Akash has ~58% tokens circulating (225M circulating with 388M max supply). Inflation per year has been raised from 8% to 13%. 60% of the circulating tokens currently are staked, with a 21 day unbonding period. Both 40% (formerly 25%) of the inflation and the take rate on GMV will also go into the community pool, which currently has $10M of AKT tokens. The uses for these sources of capital are still be determined but will be split between public funding, provider incentives, staking, a potential burn and the community pool. On Jan 19, Akash launched a proposal for a $5M pilot incentive program to bring on 1,000 A100s onto the platform. Over time, the goal would be giving supply side revenue visibility (e.g. 95% effective utilization) for providers that onboard to the marketplace. Valuation & Scenario Analysis Below, we present a few scenarios and illustrative assumptions for Akash’s key drivers: •Near-Term Case: We estimate if Akash is able to get to 15,000 A100’s this would generate close to $150M of GMV. At a 20% take rate, that would be $30M of protocol fees to Akash. Given the growth trajectory at a 100x multiple (which takes into account the valuations for AI), that would be worth $3B outcome. •Base Case: We assume the IaaS market opportunity is in-line with Morgan Stanley’s estimates of $50B. Assuming 70% utilization, there is $15B of capacity to resell. Assuming this capacity is discounted by 30% yields $10B, with an additional $10B from other non-hyperscaler sources. Given marketplaces typically enjoy strong moats, we assume Akash is able to achieve 33% share (Airbnb 20% share of vacation rental market, Uber 75% share of ride hailing market, Doordash 65% share). At a 20% take rate, which is also in-line with internet marketplaces, this yields $1B of protocol fees. At a 10x multiple, Akash would be a $10B outcome. •Upside Case: Our upside case uses the same framework as our base case. We assume $20B resell opportunity due to being able to penetrate more unique sources of GPUs and higher share gain at 50%. For context, Nvidia is a $1.2T public market cap company, while OpenAI was valued at $80B, Anthropic $20B and CoreWeave $7B in the private markets. Within crypto, Render and TAO are valued at $2B+ and $5.5B+, respectively. Risks & Mitigants There are a few key risks we are actively monitoring for our investment in Akash: •Concentration of both supply and demand: Today, the majority of GPU demand is for training extremely large, complex LLMs by large tech companies (GPT4 had 1.5T parameters vs. GPT3 with 175B vs. GPT2 at 1.5B). The majority of supply is concentrated at the large public hyperscalers. Over time, we believe there will be more interest in training smaller AI models, which are cheaper and can better handle private data. Fine-tuning will become more and more important as models shift from general purpose to vertical specific. Lastly, inference will become more and more critical as usage and adoption accelerates. •Competition: There are a number of crypto and non-crypto companies that are trying to unlock underutilized GPUs. Some of the more notable crypto protocols: Render and Nosana are unlocking consumer-grade GPUs for inference Together is building open-source training models that allows developers to build upon Ritual is building a hosted network of models •Latency issues and technological challenges: Given training is a very resource intensive task, with all chips sitting in one data center, it is still unclear if you can train a model on a dispersed, non-collocated stack of GPUs. OpenAI’s next training facility is planned to have 75K+ GPUs in a singular location in Arizona. These are problems that orchestration layers such as FedML, Io.net and Gensyn are trying to solve. Special thanks to Greg Osuri (Co-Founder, Akash), Arthur Cheong & Bryan Tan (DeFiance) and Zach Ross (Foundry) for their review and input. [1] All forecasts and assumptions are hypothetical. See “Valuation & Scenario Analysis” section for details

Summary: Metalpha (NASDAQ: MATH) is transitioning from a small-cap Nasdaq-listed, Chinese supply chain business to a complex OTC underwriter focused on crypto derivatives via a reverse-merger over the past 12-18 months. It is in our opinion the only listed, non-exchange, non-mining APAC exposure one can get in the stock market; it also happens to be one of the smallest, if not the smallest market cap crypto company. No one perceives this stock as a “crypto” play, the stock trades 50k USD / day and doesn’t show up on any comp sheets. We believe as the cycle gets underway, discovery of the stock, and with the team’s delivery, Metalpha should rerate rapidly and is set to deliver 4-17x return to its shareholders over the next 24-36 months. Metalpha is mispriced as the reverse-merger dynamics, lack of earning-power show-through, and lack of liquidity obfuscated its potential. The core OTC derivative franchise is a solid 1-2% take-rate business where lends itself well to oligopoly. The team is highly experienced in TradFi + Web3 connections to capture this blue-ocean, which is currently completely unoccupied. Valuation in-line with private seed deals as a listCo, but traction + team quality materially ahead from top traditional finance firms + strategic backing of Bitmain (both bringing business as well as potentially injecting assets via reverse-merger) We believe the setup in transactional volume will allow Metalpha to deliver ~35-50 cents of EPS by 2024/25. Pricing the business at 12x multiple and 80 cents / share of cash balance gets us at least $5.60 / share or 4x upside. Higher multiples or industry frenzy can easily deliver 10-15x upside to the stock with a potential strategic take-out. Why the opportunity exists: Target is undergoing a major transition via a reverse-merger into a preeminent Web3 derivative powerhouse. Target is transitioning from a small-cap Nasdaq-listed, Chinese supply chain business to a complex OTC underwriter focused on crypto derivatives via a reverse-merger in the past 12-18 months. We believe the complexity around reverse-merger dynamics, lack of updated financials, its mere size as an illiquid microcap, and lack of disclosure roadshows / disclosure around the team’s caliber are the main reason of its mispricing. What the business is + Upside: Complex derivative underwriting as a scaled player can be a highly lucrative business with a potentially oligopolistic industry structure. Top players can command 90% of market share. The operation of an OTC, esoteric derivatives desk is straight-forward but not simple: Client posts collateral and wants to make a trade. Structurer / trader posts a price with spreads embedded; client places the order. Target confirms the order and underwrites the risk, traders hedges the exposure internally throughout the lifespan of the order. Client posts more collateral if needed. Option expires / terminates. Client reaps PnL, trader unwinds hedges. The operation is a decent business because: Relationship & inertia driven: a client-base of institutions and HNW are generally sticky and recurring customers, whereby good technical sales can drive significant, lasting volume that helps the desk’s exposure – much similar to a good private banker. Sizable margins: the complexity makes it easy to embed spreads and margins. A typical order typically translates to 1-2% take-rate on the notional, while clients largely don’t feel the impact. Scale advantage with diversification: a larger book (up to a point) with 2-way, highly diversified derivative flow allows for perfect hedge (more margin, less risk), less slippage in hedging, more margin to give (more order won), and better market color (better hedge). In traditional OTC derivative markets, the top players typically commands 90% market share; but The competitive landscape for Crypto OTC derivatives is wide-open today with no major players owning it. Compared to other matured markets (such as US equities), crypto exotics option is severely under-developed. A small pickup would translate to meaningful upside to Target’s financials. Crypto’s option notional has a 5x gap to the US stock market, and as much as 50x gap vs. the US exotics options market. Getting to similar ratio of activity, every 1% market share in crypto exotic options translates to 1.8 Bn of annualized volume, or roughly 9x Target’s FY22 result. Experienced management team in executing: We believe Target is composed of a team of Rockstars highly experienced & connected in both Web3 + complex derivatives. Importantly, Bitmain owning 40% of Metalpha means it can direct meaningful derivative flow when it’s selling the mining rigs to the buyers. Additionally, we believe that as Bitmain goes into the 2024-2026 cycle, Metalpha remains a very interesting target for it to inject assets into for a direct reverse-listing into Nasdaq. Attractive valuation: We believe Target’s valuation is highly attractive vs. VC deals we see in the space today. It is a rare case where a publicly listed company offers a better deal than a private investment. Simple business model driving to 30-50 cents of earnings and 4-7x upside: Target’s current business model and its respective income statement, therefore, is relatively straightforward as below: Step-up in Target’s earning power, more visible financials, and more prominent NDR / marketing will be a major catalyst rerating the story in the next 12-18 months. Over the next 24-36 months with significant ramp in the underwriting business, Target could see 4 – 17x upside depending on crypto enthusiasm and market cycle. Additionally, given the following blockchain comps as of Aug 2021. Note that all companies had market cap of > 300 mm USD. With a median EV/Sales of 25x, Target could trade to 1Bn + in the next bull cycle. Risk and Mitigants: Regulatory risk in dealing with crypto derivatives Target is an offshore company dealing with OTC instruments not regulated by the financial bodies and does not serve US clients, while abiding to the highest standards of counterparty risk as per the team’s historical TradFi experience. Counterparties w/ ISDA need no license to operate in Hong Kong, thereby posting no regulatory overhang. Competition w/ everyone getting into the business / growth miss + fee compression We believe that once Target is at scale, its listed status gives it additional layer of trust amongst its customers, while the scale / diversity advantage as well as customer relationship allows it to have a head-start in delivering solid results at least in the next 2-3 years. Counterparty / credit risk We believe Target will continue to diversify its custodians while expanding its banking relationships. It is true, however, that Target is exposed to Binance risk that is unhedgeable. Expense overrun risk – no earning show-through We believe that keeping a tight expense structure and showing EPS growth is key in getting the stock rerating, therefore delivering returns to execs, thereby giving us comfort in cost control. Staff turnover risk + business operational risk in exposures / hedging We believe that making key executive shareholders as well as drafting solid compensation structures with clawbacks the way they had is a good solution to the agency problem. Majority shareholder risk Assuming the crypto market recovers, the key strategic partner is set to profit tremendously and should not pose risk to Target’s growth and operations. As target grows, its concentration on its key strategic partner should also decline. Bad capital allocation Target’s operation is very cash-generative, we will be working with Target to responsibly allocate capital. We will likely have more specificity as the cycle evolves. Multiples may be capped to “bad business” without rerating We believe as the cycle gets underway and as market sees blockchain exposure, Target will no longer be valued purely as a bank / broker but will catch a strategic premium as upside optionality to crypto as a whole (as we have observed in the last cycle). In the worse case, its earnings growth and cash-generation is enough to deliver a solid return to shareholders. Exit risk – stock is illiquid currently and may not have strategic buyer What is illiquid today will not be so given our experience once the company delivers results. We also believe that upon more awareness and better valuation, the company can place a strategic round with blue-chip investors to dramatically improve liquidity while furthering the growth of the company.