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DeFi’s Next Chapter: Perspectives from Leading Builders and Investors (2024 – 2025)

· 11 min read
Dora Noda
Software Engineer

Decentralized Finance (DeFi) matured considerably from the summer‑2020 speculation boom to the 2024‑2025 cycle. Higher interest rates slowed DeFi’s growth in 2022‑2023, but the emergence of high‑throughput chains, token‑driven incentives and a clearer regulatory environment are creating conditions for a new phase of on‑chain finance. Leaders from Hyperliquid, Aave, Ethena and Dragonfly share a common expectation that the next chapter will be driven by genuine utility: efficient market infrastructure, yield‑bearing stablecoins, real‑world asset tokenization and AI‑assisted user experiences. The following sections analyze DeFi’s future through the voices of Jeff Yan (Hyperliquid Labs), Stani Kulechov (Aave Labs), Guy Young (Ethena Labs) and Haseeb Qureshi (Dragonfly).

Jeff Yan – Hyperliquid Labs

Background

Jeff Yan is co‑founder and CEO of Hyperliquid, a decentralized exchange (DEX) that operates a high‑throughput orderbook for perpetuals and spot trading. Hyperliquid gained prominence in 2024 for its community‑driven airdrop and refusal to sell equity to venture capitalists; Yan kept the team small and self‑funded to maintain product focus. Hyperliquid’s vision is to become a decentralized base layer for other financial products, such as tokenized assets and stablecoins.

Vision for DeFi’s Next Chapter

  • Efficiency over hype. At a Token 2049 panel, Yan compared DeFi to a math problem; he argued that markets should be efficient, where users obtain the best prices without hidden spreads. Hyperliquid’s high‑throughput orderbook aims to deliver this efficiency.
  • Community ownership and anti‑VC stance. Yan believes DeFi success should be measured by value delivered to users rather than investor exits. Hyperliquid rejected private market‑maker partnerships and centralized exchange listings to avoid compromising decentralization. This approach resonates with DeFi’s ethos: protocols should be owned by their communities and built for long‑term utility.
  • Focus on infrastructure, not token price. Yan stresses that Hyperliquid’s purpose is to build robust technology; product improvements, such as HIP‑3, aim to mitigate dApp risks through automated audits and better integrations. He avoids setting rigid roadmaps, preferring to adapt to user feedback and technological changes. This adaptability reflects a broader shift from speculation toward mature infrastructure.
  • Vision for a permissionless financial stack. Yan sees Hyperliquid evolving into a foundational layer on which others can build stablecoins, RWAs and new financial instruments. By remaining decentralized and capital‑efficient, he hopes to establish a neutral layer akin to a decentralized Nasdaq.

Takeaways

Jeff Yan’s perspective emphasizes market efficiency, community‑driven ownership and modular infrastructure. He sees DeFi’s next chapter as a consolidation phase in which high‑performance DEXs become the backbone for tokenized assets and yield products. His refusal to take venture funding signals a pushback against excessive speculation; in the next chapter, protocols may prioritize sustainability over headline‑grabbing valuations.

Stani Kulechov – Aave Labs

Background

Stani Kulechov founded Aave, one of the first money‑market protocols and a leader in decentralized lending. Aave’s liquidity markets allow users to earn yield or borrow assets without intermediaries. By 2025, Aave’s TVL and product suite expanded to include stablecoins and a newly launched Family Wallet—a fiat–crypto on‑ramp that debuted at the Blockchain Ireland Summit.

Vision for DeFi’s Next Chapter

  • Rate‑cut catalyst for “DeFi summer 2.0.” At Token 2049, Kulechov argued that falling interest rates would ignite a new DeFi boom similar to 2020. Lower rates create arbitrage opportunities as on‑chain yields remain attractive relative to TradFi, drawing capital into DeFi protocols. He recalls that DeFi's TVL jumped from less than 1billionto1 billion to 10 billion during the 2020 rate cuts and expects a similar dynamic when monetary policy loosens.
  • Integration with fintech. Kulechov envisions DeFi embedding into mainstream fintech infrastructure. He plans to distribute on‑chain yields through consumer‑friendly apps and institutional channels, turning DeFi into a back‑end for savings products. The Family Wallet exemplifies this by offering seamless fiat–stablecoin conversions and everyday payments.
  • Real‑world assets (RWAs) and stablecoins. He regards tokenized real‑world assets and stablecoins as pillars of blockchain’s future. Aave’s GHO stablecoin and RWA initiatives aim to connect DeFi yields to real‑economy collateral, bridging the gap between crypto and traditional finance.
  • Community‑driven innovation. Kulechov credits Aave’s success to its community and expects user‑governed innovation to drive the next phase. He suggests that DeFi will focus on consumer applications that abstract complexity while preserving decentralization.

Takeaways

Stani Kulechov foresees a return of the DeFi bull cycle fueled by lower rates and improved user experience. He stresses integration with fintech and real‑world assets, predicting that stablecoins and tokenized treasuries will embed DeFi yields into everyday financial products. This reflects a maturation from speculative yield farming to infrastructure that coexists with traditional finance.

Guy Young – Ethena Labs

Background

Guy Young is the CEO of Ethena Labs, creator of sUSDe, a synthetic dollar stablecoin that uses delta‑neutral strategies to offer a yield‑bearing dollar. Ethena gained attention for providing attractive yields while using USDT collateral and short perpetual positions to hedge price risk. In 2025, Ethena announced initiatives like iUSDe, a compliant wrapped version for traditional institutions.

Vision for DeFi’s Next Chapter

  • Stablecoins for savings and trading collateral. Young categorizes stablecoin use cases into trading collateral, savings for developing countries, payments and speculation. Ethena focuses on savings and trading because yield makes the dollar attractive and exchange integration drives adoption. He believes a yield‑bearing dollar will become the world’s most important savings asset.
  • Neutral, platform‑agnostic stablecoins. Young argues that stablecoins must be neutral and widely accepted across venues; attempts by exchanges to push proprietary stablecoins harm user experience. Ethena’s use of USDT increases demand for Tether rather than competing with it, illustrating synergy between DeFi stablecoins and incumbents.
  • Integration with TradFi and messaging apps. Ethena plans to issue iUSDe with transfer restrictions to satisfy regulatory requirements and to integrate sUSDe into Telegram and Apple Pay, enabling users to save and spend yield‑bearing dollars like sending messages. Young imagines delivering a neobank‑like experience to a billion users through mobile apps.
  • Shift toward fundamentals and RWAs. He notes that crypto speculation appears saturated—altcoin market caps peaked at $1.2 trillion in both 2021 and 2024—so investors will focus on projects with real revenue and tokenized real‑world assets. Ethena’s strategy of providing yield from off‑chain assets positions it for this transition.

Takeaways

Guy Young’s perspective centers on yield‑bearing stablecoins as DeFi’s killer app. He argues that DeFi’s next chapter involves making dollars productive and embedding them into mainstream payments and messaging, drawing billions of users. Ethena’s platform‑agnostic approach reflects a belief that DeFi stablecoins should complement rather than compete with existing systems. He also anticipates a rotation from speculative altcoins to revenue‑generating tokens and RWAs.

Haseeb Qureshi – Dragonfly

Background

Haseeb Qureshi is managing partner at Dragonfly, a venture capital firm focusing on crypto and DeFi. Qureshi is known for his analytical writing and participation on the Chopping Block podcast. In late 2024 and early 2025, he released a series of predictions outlining how AI, stablecoins and regulatory changes will shape crypto.

Vision for DeFi’s Next Chapter

  • AI‑powered wallets and agents. Qureshi predicts that AI agents will revolutionize crypto by automating bridging, optimizing trade routes, minimizing fees and steering users away from scams. He expects AI‑driven wallets to handle cross‑chain operations seamlessly, reducing the complexity that currently deters mainstream users. AI‑assisted development tools will also make it easier to build smart contracts, solidifying the EVM’s dominance.
  • AI agent tokens vs. meme coins. Qureshi believes that tokens associated with AI agents will outperform meme coins in 2025 but warns that the novelty will fade and real value will come from AI’s impact on software engineering and trading. He views the current excitement as a shift from “financial nihilism to financial over‑optimism,” cautioning against overhyping chat‑bot coins.
  • Convergence of stablecoins and AI. In his 2025 predictions, Qureshi outlines six major themes: (1) the distinction between layer‑1 and layer‑2 chains will blur as AI tools expand EVM share; (2) token distributions will shift from large airdrops to metric‑driven or crowdfunding models; (3) stablecoin adoption will surge, with banks issuing their own stablecoins while Tether retains dominance; (4) AI agents will dominate crypto interactions but their novelty may fade by 2026; (5) AI tools will drastically lower development costs, enabling a wave of dApp innovation and stronger security; and (6) regulatory clarity, particularly in the U.S., will accelerate mainstream adoption.
  • Institutional adoption and regulatory shifts. Qureshi expects Fortune 100 companies to offer crypto to consumers under a Trump administration and believes U.S. stablecoin legislation will pass, unlocking institutional participation. The Gate.io research summary echoes this, noting that AI agents will adopt stablecoins for peer‑to‑peer transactions and that decentralized AI training will accelerate.
  • DeFi as infrastructure for AI‑assisted finance. On The Chopping Block, Qureshi named Hyperliquid as the “biggest winner” of 2024’s cycle and predicted DeFi tokens would see explosive growth in 2025. He attributes this to innovations like liquidity‑guidance pools that make decentralized perpetual trading competitive. His bullishness on DeFi stems from the belief that AI‑powered UX and regulatory clarity will drive capital into on‑chain protocols.

Takeaways

Haseeb Qureshi views DeFi’s next chapter as convergence of AI and on‑chain finance. He anticipates a surge in AI‑powered wallets and autonomous agents, which will simplify user interactions and attract new participants. Yet he cautions that the AI hype may fade; sustainable value will come from AI tools lowering development costs and improving security. He expects stablecoin legislation, institutional adoption and metric‑driven token distributions to professionalize the industry. Overall, he sees DeFi evolving into the foundation for AI‑assisted, regulatory‑compliant financial services.

Comparative Analysis

DimensionJeff Yan (Hyperliquid)Stani Kulechov (Aave)Guy Young (Ethena)Haseeb Qureshi (Dragonfly)
Core FocusHigh‑performance DEX infrastructure; community ownership; efficiencyDecentralized lending; fintech integration; real‑world assetsYield‑bearing stablecoins; trading collateral; payments integrationInvestment perspective; AI agents; institutional adoption
Key Drivers for Next ChapterEfficient order‑book markets; modular protocol layer for RWAs & stablecoinsRate cuts spurring capital inflow and “DeFi summer 2.0”; integration with fintech & RWAsNeutral stablecoins generating yield; integration with messaging apps and TradFiAI‑powered wallets and agents; regulatory clarity; metric‑driven token distributions
Role of StablecoinsUnderpins future DeFi layers; encourages decentralized issuersGHO stablecoin & tokenized treasuries integrate DeFi yields into mainstream financial productssUSDe turns dollars into yield‑bearing savings; iUSDe targets institutionsBanks to issue stablecoins by late 2025; AI agents to use stablecoins for transactions
View on Token IncentivesRejects venture funding & private market‑maker deals to prioritize communityEmphasizes community‑driven innovation; sees DeFi tokens as infrastructure for fintechAdvocates platform‑agnostic stablecoins that complement existing ecosystemsPredicts shift from large airdrops to KPI‑driven or crowdfunding distributions
Outlook on Regulation & InstitutionsMinimal focus on regulation; stresses decentralization & self‑fundingSees regulatory clarity enabling RWA tokenization and institutional useWorking on transfer‑restricted iUSDe to meet regulatory requirementsAnticipates U.S. stablecoin legislation & pro‑crypto administration accelerating adoption
On AI & AutomationN/AN/ANot central (though Ethena may use AI risk systems)AI agents will dominate user experience; novelty will fade by 2026

Conclusion

The next chapter of DeFi will likely be shaped by efficient infrastructure, yield‑bearing assets, integration with traditional finance and AI‑driven user experiences. Jeff Yan focuses on building high‑throughput, community‑owned DEX infrastructure that can serve as a neutral base layer for tokenized assets. Stani Kulechov expects lower interest rates, fintech integration and real‑world assets to catalyze a new DeFi boom. Guy Young prioritizes yield‑bearing stablecoins and seamless payments, pushing DeFi into messaging apps and traditional banks. Haseeb Qureshi anticipates AI agents transforming wallets and regulatory clarity unlocking institutional capital, while cautioning against over‑hyped AI token narratives.

Collectively, these perspectives suggest that DeFi’s future will move beyond speculative farming toward mature, user‑centric financial products. Protocols must deliver real economic value, integrate with existing financial rails, and harness technological advances like AI and high‑performance blockchains. As these trends converge, DeFi may evolve from a niche ecosystem into a global, permissionless financial infrastructure.

Goldman Sachs and Zoltan Pozsar at TOKEN2049: Inside the Closed-Door Chat on Macro, Crypto, and a New World Order

· 5 min read
Dora Noda
Software Engineer

In the world of high finance, some conversations are so critical they happen behind closed doors. At TOKEN2049 on October 1st, one such session is set to capture the industry's attention: “Goldman Sachs with Zoltan Pozsar: Macro & Crypto.” This isn't just another panel; it's a 30-minute fireside chat governed by Chatham House Rules, ensuring that the insights shared are candid, unfiltered, and unattributable.

The stage will feature two titans of finance: Zoltan Pozsar, founder of Ex Uno Plures and the intellectual architect of the "Bretton Woods III" thesis, alongside Timothy Moe, Partner and Co-Head of Asian Macro Research at Goldman Sachs. For attendees, this is a rare opportunity to hear a visionary macro strategist and a top-tier institutional investor debate the future of money, the waning dominance of the dollar, and the explosive role of digital assets.

The Speakers: A Visionary Meets an Institutional Powerhouse

To understand the weight of this session, one must understand the speakers:

  • Zoltan Pozsar: Widely regarded as one of Wall Street's most influential thinkers, Pozsar is a former senior adviser at the U.S. Treasury and strategist at the New York Fed. He is most famous for mapping the "shadow banking" system and, more recently, for his compelling "Bretton Woods III" thesis, which argues that we are shifting from a dollar-centric financial system to one based on "outside money" like commodities, gold, and potentially, crypto.
  • Timothy Moe: A veteran of Asian markets, Moe leads Goldman Sachs' regional equity strategy, guiding the firm’s institutional clients through the complexities of 11 Asia-Pacific markets. With a career spanning decades at firms like Salomon Brothers and Jardine Fleming before becoming a partner at Goldman in 2006, Moe brings a grounded, practical perspective on how global macro trends translate into real-world investment decisions.

Pozsar’s Thesis: The Dawn of Bretton Woods III

At the heart of the discussion is Pozsar’s transformative vision of the global financial order. He argues the world is moving away from a system built on "inside money" (fiat currencies and government debt) towards one underpinned by "outside money" – tangible assets outside the control of a single sovereign issuer.

His core arguments include:

  • A Multipolar Monetary World: The era of absolute U.S. dollar dominance is ending. Pozsar foresees a system where the Chinese renminbi and the euro play larger roles in trade settlement, with gold re-emerging as a neutral reserve asset.
  • Persistent Inflation and New Portfolios: Forget the inflation of the 1970s. Pozsar believes chronic under-investment in the real economy will keep prices high for the foreseeable future. This renders the traditional 60/40 stock/bond portfolio obsolete, leading him to suggest a new allocation: 20% cash, 40% equities, 20% bonds, and 20% commodities.
  • De-Dollarization is Accelerating: Geopolitical fractures and Western sanctions have pushed nations like China to build parallel financial plumbing, using currency swap lines and gold exchanges to bypass the dollar framework.

Where Does Bitcoin Fit In?

For the TOKEN2049 audience, the key question is how crypto fits into this new world. Pozsar's view is both intriguing and cautious.

He acknowledges that the core thesis of Bitcoin—a scarce, private, non-state form of money—aligns perfectly with his concept of "outside money." He appreciates that its value comes from being outside government control.

However, he raises a critical question: money has always been a public or public-private partnership. A purely private money with no state sanction is historically unprecedented. He humorously notes that Western central bank digital currencies (CBDCs) "miss the point," as they fail to offer the very non-inflatable, non-governmental properties that attract people to Bitcoin in the first place. His primary concern for Bitcoin remains the tail risk of a cryptographic failure, a technical vulnerability that physical gold doesn't share.

Bridging Theory and Action: The Goldman Sachs Perspective

This is where Timothy Moe’s role becomes crucial. As a strategist for Goldman Sachs in Asia, Moe will be the bridge between Pozsar’s grand theories and the actionable questions on investors' minds. The discussion is expected to delve into:

  • Asian Capital Flows: How will a multi-polar currency system affect trade and investment across Asia?
  • Institutional Adoption: How do Asia's institutional investors view Bitcoin versus other commodities like gold?
  • Portfolio Strategy: Does Pozsar’s 20/40/20/20 allocation model hold up under the scrutiny of Goldman's macro research?
  • CBDCs in Asia: With Asian central banks leading the charge on digital currency experiments, how do they view the rise of private crypto?

Final Thoughts

The "Goldman Sachs with Zoltan Pozsar" session is more than just a talk; it's a real-time glimpse into the strategic thinking shaping the future of finance. It brings together a prophet of a new monetary age with a pragmatic leader from the heart of the current system. The conversation promises to offer a nuanced, high-level perspective on whether crypto will be a footnote in financial history or a cornerstone of the emerging Bretton Woods III order. For anyone invested in the future of money, this is a dialogue not to be missed.

The Crypto Endgame: Insights from Industry Visionaries

· 12 min read
Dora Noda
Software Engineer

Visions from Mert Mumtaz (Helius), Udi Wertheimer (Taproot Wizards), Jordi Alexander (Selini Capital) and Alexander Good (Post Fiat)

Overview

Token2049 hosted a panel called “The Crypto Endgame” featuring Mert Mumtaz (CEO of Helius), Udi Wertheimer (Taproot Wizards), Jordi Alexander (Founder of Selini Capital) and Alexander Good (creator of Post Fiat). While there is no publicly available transcript of the panel, each speaker has expressed distinct visions for the long‑term trajectory of the crypto industry. This report synthesizes their public statements and writings—spanning blog posts, articles, news interviews and whitepapers—to explore how each person envisions the “endgame” for crypto.

Mert Mumtaz – Crypto as “Capitalism 2.0”

Core vision

Mert Mumtaz rejects the idea that cryptocurrencies simply represent “Web 3.0.” Instead, he argues that the endgame for crypto is to upgrade capitalism itself. In his view:

  • Crypto supercharges capitalism’s ingredients: Mumtaz notes that capitalism depends on the free flow of information, secure property rights, aligned incentives, transparency and frictionless capital flows. He argues that decentralized networks, public blockchains and tokenization make these features more efficient, turning crypto into “Capitalism 2.0”.
  • Always‑on markets & tokenized assets: He points to regulatory proposals for 24/7 financial markets and the tokenization of stocks, bonds and other real‑world assets. Allowing markets to run continuously and settle via blockchain rails will modernize the legacy financial system. Tokenization creates always‑on liquidity and frictionless trading of assets that previously required clearing houses and intermediaries.
  • Decentralization & transparency: By using open ledgers, crypto removes some of the gate‑keeping and information asymmetries found in traditional finance. Mumtaz views this as an opportunity to democratize finance, align incentives and reduce middlemen.

Implications

Mumtaz’s “Capitalism 2.0” thesis suggests that the industry’s endgame is not limited to digital collectibles or “Web3 apps.” Instead, he envisions a future where nation‑state regulators embrace 24/7 markets, asset tokenization and transparency. In that world, blockchain infrastructure becomes a core component of the global economy, blending crypto with regulated finance. He also warns that the transition will face challenges—such as Sybil attacks, concentration of governance and regulatory uncertainty—but believes these obstacles can be addressed through better protocol design and collaboration with regulators.

Udi Wertheimer – Bitcoin as a “generational rotation” and the altcoin reckoning

Generational rotation & Bitcoin “retire your bloodline” thesis

Udi Wertheimer, co‑founder of Taproot Wizards, is known for provocatively defending Bitcoin and mocking altcoins. In mid‑2025 he posted a viral thesis called “This Bitcoin Thesis Will Retire Your Bloodline.” According to his argument:

  • Generational rotation: Wertheimer argues that the early Bitcoin “whales” who accumulated at low prices have largely sold or transferred their coins. Institutional buyers—ETFs, treasuries and sovereign wealth funds—have replaced them. He calls this process a “full‑scale rotation of ownership”, similar to Dogecoin’s 2019‑21 rally where a shift from whales to retail demand fueled explosive returns.
  • Price‑insensitive demand: Institutions allocate capital without caring about unit price. Using BlackRock’s IBIT ETF as an example, he notes that new investors see a US$40 increase as trivial and are willing to buy at any price. This supply shock combined with limited float means Bitcoin could accelerate far beyond consensus expectations.
  • 400K+targetandaltcoincollapse:HeprojectsthatBitcoincouldexceedUS400K+ target and altcoin collapse:** He projects that Bitcoin could exceed **US400 000 per BTC by the end of 2025 and warns that altcoins will underperform or even collapse, with Ethereum singled out as the “biggest loser”. According to Wertheimer, once institutional FOMO sets in, altcoins will “get one‑shotted” and Bitcoin will absorb most of the capital.

Implications

Wertheimer’s endgame thesis portrays Bitcoin as entering its final parabolic phase. The “generational rotation” means that supply is moving into strong hands (ETFs and treasuries) while retail interest is just starting. If correct, this would create a severe supply shock, pushing BTC price well beyond current valuations. Meanwhile, he believes altcoins offer asymmetric downside because they lack institutional bid support and face regulatory scrutiny. His message to investors is clear: load up on Bitcoin now before Wall Street buys it all.

Jordi Alexander – Macro pragmatism, AI & crypto as twin revolutions

Investing in AI and crypto – two key industries

Jordi Alexander, founder of Selini Capital and a known game theorist, argues that AI and blockchain are the two most important industries of this century. In an interview summarised by Bitget he makes several points:

  • The twin revolutions: Alexander believes the only ways to achieve real wealth growth are to invest in technological innovation (particularly AI) or to participate early in emerging markets like cryptocurrency. He notes that AI development and crypto infrastructure will be the foundational modules for intelligence and coordination this century.
  • End of the four‑year cycle: He asserts that the traditional four‑year crypto cycle driven by Bitcoin halvings is over; instead the market now experiences liquidity‑driven “mini‑cycles.” Future up‑moves will occur when “real capital” fully enters the space. He encourages traders to see inefficiencies as opportunity and to develop both technical and psychological skills to thrive in this environment.
  • Risk‑taking & skill development: Alexander advises investors to keep most funds in safe assets but allocate a small portion for risk‑taking. He emphasizes building judgment and staying adaptable, as there is “no such thing as retirement” in a rapidly evolving field.

Critique of centralized strategies and macro views

  • MicroStrategy’s zero‑sum game: In a flash note he cautions that MicroStrategy’s strategy of buying BTC may be a zero‑sum game. While participants might feel like they are winning, the dynamic could hide risks and lead to volatility. This underscores his belief that crypto markets are often driven by negative‑sum or zero‑sum dynamics, so traders must understand the motivations of large players.
  • Endgame of U.S. monetary policy: Alexander’s analysis of U.S. macro policy highlights that the Federal Reserve’s control over the bond market may be waning. He notes that long‑term bonds have fallen sharply since 2020 and believes the Fed may soon pivot back to quantitative easing. He warns that such policy shifts could cause “gradually at first … then all at once” market moves and calls this a key catalyst for Bitcoin and crypto.

Implications

Jordi Alexander’s endgame vision is nuanced and macro‑oriented. Rather than forecasting a singular price target, he highlights structural changes: the shift to liquidity‑driven cycles, the importance of AI‑driven coordination and the interplay between government policy and crypto markets. He encourages investors to develop deep understanding and adaptability rather than blindly following narratives.

Alexander Good – Web 4, AI agents and the Post Fiat L1

Web 3’s failure and the rise of AI agents

Alexander Good (also known by his pseudonym “goodalexander”) argues that Web 3 has largely failed because users care more about convenience and trading than owning their data. In his essay “Web 4” he notes that consumer app adoption depends on seamless UX; requiring users to bridge assets or manage wallets kills growth. However, he sees an existential threat emerging: AI agents that can generate realistic video, control computers via protocols (such as Anthropic’s “Computer Control” framework) and hook into major platforms like Instagram or YouTube. Because AI models are improving rapidly and the cost of generating content is collapsing, he predicts that AI agents will create the majority of online content.

Web 4: AI agents negotiating on the blockchain

Good proposes Web 4 as a solution. Its key ideas are:

  • Economic system with AI agents: Web 4 envisions AI agents representing users as “Hollywood agents” negotiate on their behalf. These agents will use blockchains for data sharing, dispute resolution and governance. Users provide content or expertise to agents, and the agents extract value—often by interacting with other AI agents across the world—and then distribute payments back to the user in crypto.
  • AI agents handle complexity: Good argues that humans will not suddenly start bridging assets to blockchains, so AI agents must handle these interactions. Users will simply talk to chatbots (via Telegram, Discord, etc.), and AI agents will manage wallets, licensing deals and token swaps behind the scenes. He predicts a near‑future where there are endless protocols, tokens and computer‑to‑computer configurations that will be unintelligible to humans, making AI assistance essential.
  • Inevitable trends: Good lists several trends supporting Web 4: governments’ fiscal crises encourage alternatives; AI agents will cannibalize content profits; people are getting “dumber” by relying on machines; and the largest companies bet on user‑generated content. He concludes that it is inevitable that users will talk to AI systems, those systems will negotiate on their behalf, and users will receive crypto payments while interacting primarily through chat apps.

Mapping the ecosystem and introducing Post Fiat

Good categorizes existing projects into Web 4 infrastructure or composability plays. He notes that protocols like Story, which create on‑chain governance for IP claims, will become two‑sided marketplaces between AI agents. Meanwhile, Akash and Render sell compute services and could adapt to license to AI agents. He argues that exchanges like Hyperliquid will benefit because endless token swaps will be needed to make these systems user‑friendly.

His own project, Post Fiat, is positioned as a “kingmaker in Web 4.” Post Fiat is a Layer‑1 blockchain built on XRP’s core technology but with improved decentralization and tokenomics. Key features include:

  • AI‑driven validator selection: Instead of relying on human-run staking, Post Fiat uses large language models (LLMs) to score validators on credibility and transaction quality. The network distributes 55% of tokens to validators through a process managed by an AI agent, with the goal of “objectivity, fairness and no humans involved”. The system’s monthly cycle—publish, score, submit, verify and select & reward—ensures transparent selection.
  • Focus on investing & expert networks: Unlike XRP’s transaction‑bank focus, Post Fiat targets financial markets, using blockchains for compliance, indexing and operating an expert network composed of community members and AI agents. AGTI (Post Fiat’s development arm) sells products to financial institutions and may launch an ETF, with revenues funding network development.
  • New use cases: The project aims to disrupt the indexing industry by creating decentralized ETFs, provide compliant encrypted memos and support expert networks where members earn tokens for insights. The whitepaper details technical measures—such as statistical fingerprinting and encryption—to prevent Sybil attacks and gaming.

Web 4 as survival mechanism

Good concludes that Web 4 is a survival mechanism, not just a cool ideology. He argues that a “complexity bomb” is coming within six months as AI agents proliferate. Users will have to give up some upside to AI systems because participating in agentic economies will be the only way to thrive. In his view, Web 3’s dream of decentralized ownership and user privacy is insufficient; Web 4 will blend AI agents, crypto incentives and governance to navigate an increasingly automated economy.

Comparative analysis

Converging themes

  1. Institutional & technological shifts drive the endgame.
    • Mumtaz foresees regulators enabling 24/7 markets and tokenization, which will mainstream crypto.
    • Wertheimer highlights institutional adoption via ETFs as the catalyst for Bitcoin’s parabolic phase.
    • Alexander notes that the next crypto boom will be liquidity‑driven rather than cycle‑driven and that macro policies (like the Fed’s pivot) will provide powerful tailwinds.
  2. AI becomes central.
    • Alexander emphasises investing in AI alongside crypto as twin pillars of future wealth.
    • Good builds Web 4 around AI agents that transact on blockchains, manage content and negotiate deals.
    • Post Fiat’s validator selection and governance rely on LLMs to ensure objectivity. Together these visions imply that the endgame for crypto will involve synergy between AI and blockchain, where AI handles complexity and blockchains provide transparent settlement.
  3. Need for better governance and fairness.
    • Mumtaz warns that centralization of governance remains a challenge.
    • Alexander encourages understanding game‑theoretic incentives, pointing out that strategies like MicroStrategy’s can be zero‑sum.
    • Good proposes AI‑driven validator scoring to remove human biases and create fair token distribution, addressing governance issues in existing networks like XRP.

Diverging visions

  1. Role of altcoins. Wertheimer sees altcoins as doomed and believes Bitcoin will capture most capital. Mumtaz focuses on the overall crypto market including tokenized assets and DeFi, while Alexander invests across chains and believes inefficiencies create opportunity. Good is building an alt‑L1 (Post Fiat) specialized for AI finance, implying he sees room for specialized networks.
  2. Human agency vs AI agency. Mumtaz and Alexander emphasize human investors and regulators, whereas Good envisions a future where AI agents become the primary economic actors and humans interact through chatbots. This shift implies fundamentally different user experiences and raises questions about autonomy, fairness and control.
  3. Optimism vs caution. Wertheimer’s thesis is aggressively bullish on Bitcoin with little concern for downside. Mumtaz is optimistic about crypto improving capitalism but acknowledges regulatory and governance challenges. Alexander is cautious—highlighting inefficiencies, zero‑sum dynamics and the need for skill development—while still believing in crypto’s long‑term promise. Good sees Web 4 as inevitable but warns of the complexity bomb, urging preparation rather than blind optimism.

Conclusion

The Token2049 “Crypto Endgame” panel brought together thinkers with very different perspectives. Mert Mumtaz views crypto as an upgrade to capitalism, emphasizing decentralization, transparency and 24/7 markets. Udi Wertheimer sees Bitcoin entering a supply‑shocked generational rally that will leave altcoins behind. Jordi Alexander adopts a more macro‑pragmatic stance, urging investment in both AI and crypto while understanding liquidity cycles and game‑theoretic dynamics. Alexander Good envisions a Web 4 era where AI agents negotiate on blockchains and Post Fiat becomes the infrastructure for AI‑driven finance.

Although their visions differ, a common theme is the evolution of economic coordination. Whether through tokenized assets, institutional rotation, AI‑driven governance or autonomous agents, each speaker believes crypto will fundamentally reshape how value is created and exchanged. The endgame therefore seems less like an endpoint and more like a transition into a new system where capital, computation and coordination converge.

Vlad Tenev: Tokenization Will Eat the Financial System

· 21 min read
Dora Noda
Software Engineer

Vlad Tenev has emerged as one of traditional finance's most bullish voices on cryptocurrency, declaring that tokenization is an unstoppable "freight train" that will eventually consume the entire financial system. Throughout 2024-2025, the Robinhood CEO delivered increasingly bold predictions about crypto's inevitable convergence with traditional finance, backed by aggressive product launches including a $200 million acquisition of Bitstamp, tokenized stock trading in Europe, and a proprietary Layer 2 blockchain. His vision centers on blockchain technology offering an "order of magnitude" cost advantage that will eliminate the distinction between crypto and traditional finance within 5-10 years, though he candidly admits the U.S. will lag behind Europe due to "sticking power" of existing infrastructure. This transformation accelerated dramatically after the 2024 election, with Robinhood's crypto business quintupling post-election as regulatory hostility shifted to enthusiasm under the Trump administration.

The freight train thesis: Tokenization will consume everything

At Singapore's Token2049 conference in October 2025, Tenev delivered his most memorable statement on crypto's future: "Tokenization is like a freight train. It can't be stopped, and eventually it's going to eat the entire financial system." This wasn't hyperbole but a detailed thesis he's been building throughout 2024-2025. He predicts most major markets will establish tokenization frameworks within five years, with full global adoption taking a decade or more. The transformation will expand addressable financial markets from single-digit trillions to tens of trillions of dollars.

His conviction rests on structural advantages of blockchain technology. "The cost of running a crypto business is an order of magnitude lower. There's just an obvious technology advantage," he told Fortune's Brainstorm Tech conference in July 2024. By leveraging open-source blockchain infrastructure, companies can eliminate expensive intermediaries for trade settlement, custody, and clearing. Robinhood is already using stablecoins internally to power weekend settlements, experiencing firsthand the efficiency gains from 24/7 instant settlement versus traditional rails.

The convergence between crypto and traditional finance forms the core of his vision. "I actually think cryptocurrency and traditional finance have been living in two separate worlds for a while, but they're going to fully merge," he stated at Token2049. "Crypto technology has so many advantages over the traditional way we're doing things that in the future there's going to be no distinction." He frames this not as crypto replacing finance, but as blockchain becoming the invisible infrastructure layer—like moving from filing cabinets to mainframes—that makes the financial system dramatically more efficient.

Stablecoins represent the first wave of this transformation. Tenev describes dollar-pegged stablecoins as the most basic form of tokenized assets, with billions already in circulation reinforcing U.S. dollar dominance abroad. "In the same way that stablecoins have become the default way to get digital access to dollars, tokenized stocks will become the default way for people outside the U.S. to get exposure to American equities," he predicted. The pattern will extend to private companies, real estate, and eventually all asset classes.

Building the tokenized future with stock tokens and blockchain infrastructure

Robinhood backed Tenev's rhetoric with concrete product launches throughout 2024-2025. In June 2025, the company hosted a dramatic event in Cannes, France titled "To Catch a Token," where Tenev presented a metal cylinder containing "keys to the first-ever stock tokens for OpenAI" while standing by a reflecting pool overlooking the Mediterranean. The company launched over 200 tokenized U.S. stocks and ETFs in the European Union, offering 24/5 trading with zero commissions or spreads, initially on the Arbitrum blockchain.

The launch wasn't without controversy. OpenAI immediately distanced itself, posting "We did not partner with Robinhood, were not involved in this, and do not endorse it." Tenev defended the product, acknowledging the tokens aren't "technically" equity but maintain they give retail investors exposure to private assets that would otherwise be inaccessible. He dismissed the controversy as part of broader U.S. regulatory delays, noting "the obstacles are legal rather than technical."

More significantly, Robinhood announced development of a proprietary Layer 2 blockchain optimized for tokenized real-world assets. Built on Arbitrum's technology stack, this blockchain infrastructure aims to support 24/7 trading, seamless bridging between chains, and self-custody capabilities. Tokenized stocks will eventually migrate to this platform. Johann Kerbrat, Robinhood's crypto general manager, explained the strategy: "Crypto was built by engineers for engineers, and has not been accessible to most people. We're onboarding the world to crypto by making it as easy to use as possible."

Tenev's timeline projections reveal measured optimism despite his bold vision. He expects the U.S. to be "among the last economies to actually fully tokenize" due to infrastructure inertia. Drawing an analogy to transportation, he noted: "The biggest challenge in the U.S. is that the financial system basically works. It's why we don't have bullet trains—medium-speed trains get you there well enough." This candid assessment acknowledges that working systems have greater sticking power than in regions where blockchain offers more dramatic improvement over dysfunctional alternatives.

Bitstamp acquisition unlocks institutional crypto and global expansion

Robinhood completed its 200millionacquisitionofBitstampinJune2025,markingastrategicinflectionpointfrompureretailcryptotradingtoinstitutionalcapabilitiesandinternationalscale.Bitstampbrought50+activecryptolicensesacrossEurope,theUK,U.S.,andAsia,plus5,000institutionalclientsand200 million acquisition of Bitstamp** in June 2025, marking a strategic inflection point from pure retail crypto trading to institutional capabilities and international scale. Bitstamp brought **50+ active crypto licenses** across Europe, the UK, U.S., and Asia, plus **5,000 institutional clients** and **8 billion in cryptocurrency assets under custody. This acquisition addresses two priorities Tenev repeatedly emphasized: international expansion and institutional business development.

"There's two interesting things about the Bitstamp acquisition you should know. One is international. The second is institutional," Tenev explained on the Q2 2024 earnings call. The global licenses dramatically accelerate Robinhood's ability to enter new markets without building regulatory infrastructure from scratch. Bitstamp operates in over 50 countries, providing instant global footprint that would take years to replicate organically. "The goal is for Robinhood to be everywhere, anywhere where customers have smartphones, you should be able to open up a Robinhood account," he stated.

The institutional dimension proves equally strategic. Bitstamp's established relationships with institutional clients, lending infrastructure, staking services, and white-label crypto-as-a-service offerings transform Robinhood from retail-only to a full-stack crypto platform. "Institutions also want low-cost market access to crypto," Tenev noted. "We're really excited about bringing the same sort of Robinhood effect that we've brought to retail to the institutional space with crypto."

Integration proceeded rapidly through 2025. By Q2 2025 earnings, Robinhood reported Bitstamp exchange crypto notional trading volumes of 7billion,complementingtheRobinhoodapps7 billion, complementing the Robinhood app's 28 billion in crypto volumes. The company also announced plans to hold its first crypto-focused customer event in France around midyear, signaling international expansion priorities. Tenev emphasized that unlike the U.S. where they started with stocks then added crypto, international markets might lead with crypto depending on regulatory environments and market demand.

Crypto revenue explodes from 135milliontoover135 million to over 600 million annually

Financial metrics underscore the dramatic shift in crypto's importance to Robinhood's business model. Annual crypto revenue surged from 135millionin2023to135 million in 2023 to 626 million in 2024—a 363% increase. This acceleration continued into 2025, with Q1 alone generating 252millionincryptorevenue,representingoveronethirdoftotaltransactionbasedrevenues.Q42024provedparticularlyexplosive,with252 million in crypto revenue, representing over one-third of total transaction-based revenues. Q4 2024 proved particularly explosive, with **358 million in crypto revenue, up over 700% year-over-year**, driven by the post-election "Trump pump" and expanding product capabilities.

These numbers reflect both volume growth and strategic pricing changes. Robinhood's crypto take rate expanded from 35 basis points at the start of 2024 to 48 basis points by October 2024, as CFO Jason Warnick explained: "We always want to have great prices for customers, but also balance the return that we generate for shareholders on that activity." Crypto notional trading volumes reached approximately 28billionmonthlybylate2024,withassetsundercustodytotaling28 billion monthly by late 2024, with assets under custody totaling **38 billion** as of November 2024.

Tenev described the post-election environment on CNBC as producing "basically what people are calling the 'Trump Pump,'" noting "widespread optimism that the Trump administration, which has stated that they wish to embrace cryptocurrencies and make America the center of cryptocurrency innovation worldwide, is going to have a much more forward-looking policy." On the Unchained podcast in December 2024, he revealed Robinhood's crypto business "quintupled post-election."

The Bitstamp acquisition adds significant scale. Beyond the $8 billion in crypto assets and institutional client base, Bitstamp's 85+ tradable crypto assets and staking infrastructure expand Robinhood's product capabilities. Cantor Fitzgerald analysis noted Robinhood's crypto volume spiked 36% in May 2025 while Coinbase's fell, suggesting market share gains. With crypto representing 38% of projected 2025 revenues, the business has evolved from speculative experiment to core revenue driver.

From regulatory "carpet bombing" to playing offense under Trump

Tenev's commentary on crypto regulation represents one of the starkest before-and-after narratives in his 2024-2025 statements. Speaking at the Bitcoin 2025 conference in Las Vegas, he characterized the previous regulatory environment bluntly: "Under the previous administration, we have been subject to…it was basically a carpet bombing of the entire industry." He expanded on a podcast: "In the previous administration with Gary Gensler at the SEC, we were very much in a defensive posture. There was crypto, which was, as you guys know, basically they were trying to delete crypto from the U.S."

This wasn't abstract criticism. Robinhood Crypto received an SEC Wells Notice in May 2024 signaling potential enforcement action. Tenev responded forcefully: "This is a disappointing development. We firmly believe U.S. consumers should have access to this asset class. They deserve to be on equal footing with people all over the world." The investigation eventually closed in February 2025 with no action, prompting Chief Legal Officer Dan Gallagher to state: "This investigation never should have been opened. Robinhood Crypto always has and will always respect federal securities laws and never allowed transactions in securities."

The Trump administration's arrival transformed the landscape. "Now suddenly, you're allowed to play some offense," Tenev told CBS News at the Bitcoin 2025 conference. "And we have an administration that's open to the technology." His optimism extended to specific personnel, particularly Paul Atkins' nomination to lead the SEC: "This administration has been hostile to crypto. Having people that understand and embrace it is very important for the industry."

Perhaps most significantly, Tenev revealed direct engagement with regulators on tokenization: "We've actually been engaging with the SEC crypto task force as well as the administration. And it's our belief, actually, that we don't even need congressional action to make tokenization real. The SEC can just do it." This represents a dramatic shift from regulation-by-enforcement to collaborative framework development. He told Bloomberg Businessweek: "Their intent appears to be to ensure that the US is the best place to do business and the leader in both of the emergent technology industries coming to the fore: crypto and AI."

Tenev also published a Washington Post op-ed in January 2025 advocating for specific policy reforms, including creating security token registration regimes, updating accredited investor rules from wealth-based to knowledge-based certification, and establishing clear guidelines for exchanges listing security tokens. "The world is tokenizing, and the United States should not get left behind," he wrote, noting the EU, Singapore, Hong Kong, and Abu Dhabi have advanced comprehensive frameworks while the U.S. lags.

Bitcoin, Dogecoin, and stablecoins: Selective crypto asset views

Tenev's statements reveal differentiated views across crypto assets rather than blanket enthusiasm. On Bitcoin, he acknowledged the asset's evolution: "Bitcoin's gone from largely being ridiculed to being taken very seriously," citing Federal Reserve Chair Powell's comparison of Bitcoin to gold as institutional validation. However, when asked about following MicroStrategy's strategy of holding Bitcoin as a treasury asset, Tenev declined. In an interview with Anthony Pompliano, he explained: "We have to do the work of accounting for it, and it's essentially on the balance sheet anyway. So there's a real reason for it [but] it could complicate things for public market investors"—potentially casting Robinhood as a "quasi Bitcoin-holding play" rather than a trading platform.

Notably, he observed that "Robinhood stock is already highly correlated to Bitcoin" even without holding it—HOOD stock rose 202% in 2024 versus Bitcoin's 110% gain. "So I would say we wouldn't rule it out. We haven't done it thus far but those are the kind of considerations we have." This reveals pragmatic rather than ideological thinking about crypto assets.

Dogecoin holds special significance in Robinhood's history. On the Unchained podcast, Tenev discussed "how Dogecoin became one of Robinhood's biggest assets for user onboarding," acknowledging that millions of users came to the platform through meme coin interest. Johann Kerbrat stated: "We don't see Dogecoin as a negative asset for us." Despite efforts to distance from 2021's meme stock frenzy, Robinhood continues offering Dogecoin, viewing it as a legitimate entry point for crypto-curious retail investors. Tenev even tweeted in 2022 asking whether "Doge can truly be the future currency of the Internet," showing genuine curiosity about the asset's properties as an "inflationary coin."

Stablecoins receive Tenev's most consistent enthusiasm as practical infrastructure. Robinhood invested in the Global Dollar Network's USDG stablecoin, which he described on the Q4 2024 earnings call: "We have USDG that we partner with a few other great companies on...a stablecoin that passes back yield to holders, which we think is the future. I think many of the leading stablecoins don't have a great way to pass yield to holders." More significantly, Robinhood uses stablecoins internally: "We see the power of that ourselves as a company...there's benefits to the technology and the 24-hour instant settlements for us as a business. In particular, we're using stablecoin to power a lot of our weekend settlements now." He predicted this internal adoption will drive broader institutional stablecoin adoption industrywide.

For Ethereum and Solana, Robinhood launched staking services in both Europe (enabled by MiCA regulations) and the U.S. Tenev noted "increasing interest in crypto staking" without it cannibalizing traditional cash-yield products. The company expanded its European crypto offerings to include SOL, MATIC, and ADA after these faced SEC scrutiny in the U.S., illustrating geographic arbitrage in regulatory approaches.

Prediction markets emerge as hybrid disruption opportunity

Prediction markets represent Tenev's most surprising crypto-adjacent bet, launching event contracts in late 2024 and rapidly scaling to over 4 billion contracts traded by October 2025, with 2 billion contracts in Q3 2025 alone. The 2024 presidential election proved the concept, with Tenev revealing "over 500 million contracts traded in right around a week leading up to the election." But he emphasized this isn't cyclical: "A lot of people had skepticism about whether this would only be an election thing...It's really much bigger than that."

At Token2049, Tenev articulated prediction markets' unique positioning: "Prediction markets has some similarities with traditional sports betting and gambling, there's also similarities with active trading in that there are exchange-traded products. It also has some similarities to traditional media news products because there's a lot of people that use prediction markets not to trade or speculate, but because they want to know." This hybrid nature creates disruption potential across multiple industries. "Robinhood will be front and center in terms of giving access to retail," he declared.

The product expanded beyond politics to sports (college football proving particularly popular), culture, and AI topics. "Prediction markets communicate information more quickly than newspapers or broadcast media," Tenev argued, positioning them as both trading instruments and information discovery mechanisms. On the Q4 2024 earnings call, he promised: "What you should expect from us is a comprehensive events platform that will give access to prediction markets across a wide variety of contracts later this year."

International expansion presents challenges due to varying regulatory classifications—futures contracts in some jurisdictions, gambling in others. Robinhood initiated talks with the UK's Financial Conduct Authority and other regulators about prediction market frameworks. Tenev acknowledged: "As with any new innovative asset class, we're pushing the boundaries here. And there's not regulatory clarity across all of it yet in particular sports which you mentioned. But we believe in it and we're going to be a leader."

AI-powered tokenized one-person companies represent convergence vision

At the Bitcoin 2025 conference, Tenev unveiled his most futuristic thesis connecting AI, blockchain, and entrepreneurship: "We're going to see more one-person companies. They're going to be tokenized and traded on the blockchain, just like any other asset. So it's going to be possible to invest economically in a person or a project that that person is running." He explicitly cited Satoshi Nakamoto as the prototype: "This is essentially like Bitcoin itself. Satoshi Nakamoto's personal brand is powered by technology."

The logic chains together several trends. "One of the things that AI makes possible is that it produces more and more value with fewer and fewer resources," Tenev explained. If AI dramatically reduces the resources required to build valuable companies, and blockchain provides instant global investment infrastructure through tokenization, entrepreneurs can create and monetize ventures without traditional corporate structures, employees, or venture capital. Personal brands become tradable assets.

This vision connects to Tenev's role as executive chairman of Harmonic, an AI startup focused on reducing hallucinations through Lean code generation. His mathematical background (Stanford BS, UCLA MS in Mathematics) informs optimism about AI solving complex problems. In an interview, he described the aspiration of "solving the Riemann hypothesis on a mobile app"—referencing one of mathematics' greatest unsolved problems.

The tokenized one-person company thesis also addresses wealth concentration concerns. Tenev's Washington Post op-ed criticized current accredited investor laws restricting private market access to high-net-worth individuals, arguing this concentrates wealth among the top 20%. If early-stage ventures can tokenize equity and distribute it globally via blockchain with appropriate regulatory frameworks, wealth creation from high-growth companies becomes more democratically accessible. "It's time to update our conversation about crypto from bitcoin and meme coins to what blockchain is really making possible: A new era of ultra-inclusive and customizable investing fit for this century," he wrote.

Robinhood positions at the intersection of crypto and traditional finance

Tenev consistently describes Robinhood's unique competitive positioning: "I think Robinhood is uniquely positioned at the intersection of traditional finance and DeFi. We're one of the few players that has scale, both in traditional financial assets and cryptocurrencies." This dual capability creates network effects competitors struggle to replicate. "What customers really love about trading crypto on Robinhood is that they not only have access to crypto, but they can trade equities, options, now futures, soon a comprehensive suite of event contracts all in one place," he told analysts.

The strategy involves building comprehensive infrastructure across the crypto stack. Robinhood now offers: crypto trading with 85+ assets via Bitstamp, staking for ETH and SOL, non-custodial Robinhood Wallet for accessing thousands of additional tokens and DeFi protocols, tokenized stocks and private companies, crypto perpetual futures in Europe with 3x leverage, proprietary Layer 2 blockchain under development, USDG stablecoin investment, and smart exchange routing allowing active traders to route directly to exchange order books.

This vertical integration contrasts with specialized crypto exchanges lacking traditional finance integration or traditional brokerages dabbling in crypto. "Tokenization once permissible in the U.S., I think, is going to be a huge opportunity that Robinhood is going to be front and center in," Tenev stated on the Q4 2024 earnings call. The company launched 10+ product lines each on track for $100 million+ annual revenue, with crypto representing a substantial pillar alongside options, stocks, futures, credit cards, and retirement accounts.

Asset listing strategy reflects balancing innovation with risk management. Robinhood lists fewer cryptocurrencies than competitors—20 in the U.S., 40 in Europe—maintaining what Tenev calls a "conservative approach." After receiving the SEC Wells Notice, he emphasized: "We've operated our crypto business in good faith. We've been very conservative in our approach in terms of coins listed and services offered." However, regulatory clarity is changing this calculus: "In fact, we've added seven new assets since the election. And as we continue to get more and more regulatory clarity, you should expect to see that continue and accelerate."

The competitive landscape includes Coinbase as the dominant U.S. crypto exchange, plus traditional brokerages like Schwab and Fidelity adding crypto. CFO Jason Warnick addressed competition on earnings calls: "While there may be more competition over time, I do expect that there will be greater demand for crypto as well. I think we're beginning to see that crypto is becoming more mainstream." Robinhood's crypto volume spike of 36% in May 2025 while Coinbase's declined suggests the integrated platform approach is winning share.

Timeline and predictions: Five years to frameworks, decades to completion

Tenev provides specific timeline predictions rare among crypto optimists. At Token2049, he stated: "I think most major markets will have some framework in the next five years," targeting roughly 2030 for regulatory clarity across major financial centers. However, reaching "100% adoption could take more than a decade," acknowledging the difference between frameworks existing and complete migration to tokenized systems.

His predictions break down by geography and asset class. Europe leads on regulatory frameworks through MiCA regulations and will likely see tokenized stock trading go mainstream first. The U.S. will be "among the last economies to actually fully tokenize" due to infrastructure sticking power, but the Trump administration's crypto-friendly posture accelerates timelines versus previous expectations. Asia, particularly Singapore, Hong Kong, and Abu Dhabi, advances rapidly due to both regulatory clarity and less legacy infrastructure to overcome.

Asset class predictions show staggered adoption. Stablecoins already achieved product-market fit as the "most basic form of tokenized assets." Stocks and ETFs enter tokenization phase now in Europe, with U.S. timelines depending on regulatory developments. Private company equity represents near-term opportunity, with Robinhood already offering tokenized OpenAI and SpaceX shares despite controversy. Real estate comes next—Tenev noted tokenizing real estate is "mechanically no different from tokenizing a private company"—assets placed into corporate structures, then tokens issued against them.

His boldest claim suggests crypto entirely absorbs traditional finance architecture: "In the future, everything will be on-chain in some form" and "the distinction between crypto and TradFi will disappear." The transformation occurs not through crypto replacing finance but blockchain becoming the invisible settlement and custody layer. "You don't have to squint too hard to imagine a world where stocks are on blockchains," he told Fortune. Just as users don't think about TCP/IP when browsing the web, future investors won't distinguish between "crypto" and "regular" assets—blockchain infrastructure simply powers all trading, custody, and settlement invisibly.

Conclusion: Technology determinism meets regulatory pragmatism

Vlad Tenev's cryptocurrency vision reveals a technology determinist who believes blockchain's cost and efficiency advantages make adoption inevitable, combined with a regulatory pragmatist who acknowledges legacy infrastructure creates decade-long timelines. His "freight train" metaphor captures this duality—tokenization moves with unstoppable momentum but at measured speed requiring regulatory tracks to be built ahead of it.

Several insights distinguish his perspective from typical crypto boosterism. First, he candidly admits the U.S. financial system "basically works," acknowledging working systems resist replacement regardless of theoretical advantages. Second, he doesn't evangelize blockchain ideologically but frames it pragmatically as infrastructure evolution comparable to filing cabinets giving way to computers. Third, his revenue metrics and product launches back rhetoric with execution—crypto grew from 135milliontoover135 million to over 600 million annually, with concrete products like tokenized stocks and a proprietary blockchain under development.

The dramatic regulatory shift from "carpet bombing" under the Biden administration to "playing offense" under Trump provides the catalyst Tenev believes enables U.S. competitiveness. His direct SEC engagement on tokenization frameworks and public advocacy through op-eds position Robinhood as a partner in writing rules rather than evading them. Whether his prediction of convergence between crypto and traditional finance within 5-10 years proves accurate depends heavily on regulators following through with clarity.

Most intriguingly, Tenev's vision extends beyond speculation and trading to structural transformation of capital formation itself. His AI-powered tokenized one-person companies and advocacy for reformed accredited investor laws suggest belief that blockchain plus AI democratizes wealth creation and entrepreneurship fundamentally. This connects his mathematical background, immigrant experience, and stated mission of "democratizing finance for all" into a coherent worldview where technology breaks down barriers between ordinary people and wealth-building opportunities.

Whether this vision materializes or falls victim to regulatory capture, entrenched interests, or technical limitations remains uncertain. But Tenev has committed Robinhood's resources and reputation to the bet that tokenization represents not just a product line but the future architecture of the global financial system. The freight train is moving—the question is whether it reaches the destination on his timeline.

Hyperliquid in 2025: A High-Performance DEX Building the Future of Onchain Finance

· 43 min read
Dora Noda
Software Engineer

Decentralized exchanges (DEXs) have matured into core pillars of crypto trading, now capturing roughly 20% of total market volumes. Within this space, Hyperliquid has emerged as the undisputed leader in on-chain derivatives. Launched in 2022 with the ambitious goal of matching centralized exchange (CEX) performance on-chain, Hyperliquid today processes billions in daily trading and controls about 70–75% of the DEX perpetual futures market. It achieves this by combining CEX-grade speed and deep liquidity with DeFi’s transparency and self-custody. The result is a vertically integrated Layer-1 blockchain and exchange that many now call “the blockchain to house all finance.” This report delves into Hyperliquid’s technical architecture, tokenomics, 2025 growth metrics, comparisons with other DEX leaders, ecosystem developments, and its vision for the future of on-chain finance.

Technical Architecture: A Vertically Integrated, High-Performance Chain

Hyperliquid is not just a DEX application – it is an entire Layer-1 blockchain built for trading performance. Its architecture consists of three tightly coupled components operating in a unified state:

  • HyperBFT (Consensus): A custom Byzantine Fault Tolerant consensus mechanism optimized for speed and throughput. Inspired by modern protocols like HotStuff, HyperBFT provides sub-second finality and high consistency to ensure all nodes agree on the order of transactions. This Proof-of-Stake consensus is designed to handle the intense load of a trading platform, supporting on the order of 100,000–200,000 operations per second in practice. By early 2025, Hyperliquid had around 27 independent validators securing the network, a number that is steadily growing to decentralize consensus.
  • HyperCore (Execution Engine): A specialized on-chain engine for financial applications. Rather than using generic smart contracts for critical exchange logic, HyperCore implements built-in central limit order books (CLOBs) for perpetual futures and spot markets, as well as other modules for lending, auctions, oracles, and more. Every order placement, cancellation, trade match, and liquidation is processed on-chain with one-block finality, yielding execution speeds comparable to traditional exchanges. By eschewing AMMs and handling order matching within the protocol, Hyperliquid achieves deep liquidity and low latency – it has demonstrated <1s trade finality and throughput that rivals centralized venues. This custom execution layer (written in Rust) can reportedly handle up to 200k orders per second after recent optimizations, eliminating the bottlenecks that previously made on-chain order books infeasible.
  • HyperEVM (Smart Contracts): A general-purpose Ethereum-compatible execution layer introduced in Feb 2025. HyperEVM allows developers to deploy Solidity smart contracts and dApps on Hyperliquid with full EVM compatibility, similar to building on Ethereum. Crucially, HyperEVM is not a separate shard or rollup – it shares the same unified state with HyperCore. This means that dApps on HyperEVM can natively interoperate with the exchange’s order books and liquidity. For example, a lending protocol on HyperEVM can read live prices from HyperCore’s order book or even post liquidation orders directly into the order book via system calls. This composability between smart contracts and the high-speed exchange layer is a unique design: no bridges or off-chain oracles are needed for dApps to leverage Hyperliquid’s trading infrastructure.

Figure: Hyperliquid's vertically integrated architecture showing the unified state between consensus (HyperBFT), exchange engine (HyperCore), smart contracts (HyperEVM), and asset bridging (HyperUnit).

Integration with On-Chain Infrastructure: By building its own chain, Hyperliquid tightly integrates normally siloed functions into one platform. HyperUnit, for instance, is Hyperliquid’s decentralized bridging and asset tokenization module enabling direct deposits of external assets like BTC, ETH, and SOL without custodial wrappers. Users can lock native BTC or ETH and receive equivalent tokens (e.g. uBTC, uETH) on Hyperliquid for use as trading collateral, without relying on centralized custodians. This design provides “true collateral mobility” and a more regulatory-aware framework for bringing real-world assets on-chain. Thanks to HyperUnit (and Circle’s USDC integration discussed later), traders on Hyperliquid can seamlessly move liquidity from other networks into Hyperliquid’s fast exchange environment.

Performance and Latency: All parts of the stack are optimized for minimal latency and maximal throughput. HyperBFT finalizes blocks within a second, and HyperCore processes trades in real time, so users experience near-instant order execution. There are effectively no gas fees for trading actions – HyperCore transactions are feeless, enabling high-frequency order placement and cancellation without cost to users. (Normal EVM contract calls on HyperEVM do incur a low gas fee, but the exchange’s operations run gas-free on the native engine.) This zero-gas, low-latency design makes advanced trading features viable on-chain. Indeed, Hyperliquid supports the same advanced order types and risk controls as top CEXs, such as limit and stop orders, cross-margining, and up to 50× leverage on major markets. In sum, Hyperliquid’s custom L1 chain eliminates the traditional trade-off between speed and decentralization. Every operation is on-chain and transparent, yet the user experience – in terms of execution speed and interface – parallels that of a professional centralized exchange.

Evolution and Scalability: Hyperliquid’s architecture was born from first principles engineering. The project launched quietly in 2022 as a closed-alpha perpetuals DEX on a custom Tendermint-based chain, proving the CLOB concept with ~20 assets and 50× leverage. By 2023 it transitioned into a fully sovereign L1 with the new HyperBFT consensus, achieving 100K+ orders per second and introducing zero-gas trading and community liquidity pools. The addition of HyperEVM in early 2025 opened the floodgates for developers, marking Hyperliquid’s evolution from a single-purpose exchange into a full DeFi platform**. Notably, all these enhancements have kept the system stable – Hyperliquid reports** 99.99% uptime historically[25]_. This track record and vertical integration_ give Hyperliquid a significant technical moat: it controls the entire stack (consensus, execution, application), allowing continuous optimization. As demand grows, the team continues to refine the node software for even higher throughput, ensuring scalability for the next wave of users and more complex on-chain markets.

Tokenomics of $HYPE: Governance, Staking, and Value Accrual

Hyperliquid’s economic design centers on its native token $HYPE, introduced in late 2024 to decentralize ownership and governance of the platform. The token’s launch and distribution were notably community-centric: in November 2024, Hyperliquid conducted an airdrop Token Generation Event (TGE), allocating 31% of the 1 billion fixed supply to early users as a reward for their participation. An even larger portion (≈38.8%) was set aside for future community incentives like liquidity mining or ecosystem development. Importantly, $HYPE had zero allocations to VCs or private investors, reflecting a philosophy of prioritizing community ownership. This transparent distribution aimed to avoid the heavy insider ownership seen in many projects and instead empower the actual traders and builders on Hyperliquid.

The $HYPE token serves multiple roles in the Hyperliquid ecosystem:

  • Governance: $HYPE is a governance token enabling holders to vote on Hyperliquid Improvement Proposals (HIPs) and shape the protocol’s evolution. Already, critical upgrades like HIP-1, HIP-2, and HIP-3 have been passed, which established permissionless listing standards for spot tokens and perpetual markets. For example, HIP-3 opened up the ability for community members to permissionlessly deploy new perp markets, much like Uniswap did for spot trading, unlocking long-tail assets (including traditional market perps) on Hyperliquid. Governance will increasingly decide listings, parameter tweaks, and the use of community incentive funds.
  • Staking & Network Security: Hyperliquid is a Proof-of-Stake chain, so staking $HYPE to validators secures the HyperBFT network. Stakers delegate to validators and earn a portion of block rewards and fees. Shortly after launch, Hyperliquid enabled staking with an annual yield ~2–2.5% to incentivize participation in consensus. As more users stake, the chain’s security and decentralization improve. Staked $HYPE (or derivative forms like upcoming beHYPE liquid staking) may also be used in governance voting, aligning security participants with decision-making.
  • Exchange Utility (Fee Discounts): Holding or staking $HYPE confers trading fee discounts on Hyperliquid’s exchange. Similar to how Binance’s BNB or dYdX’s DYDX token offer reduced fees, active traders are incentivized to hold $HYPE to minimize their costs. This creates a natural demand for the token among the exchange’s user base, especially high-volume traders.
  • Value Accrual via Buybacks: The most striking aspect of Hyperliquid's tokenomics is its aggressive fee-to-value mechanism. Hyperliquid uses the vast majority of its trading fee revenue to buy back and burn $HYPE on the open market, directly returning value to token holders. In fact, 97% of all protocol trading fees are allocated to buying back $HYPE (and the remainder to an insurance fund and liquidity providers). This is one of the highest fee return rates in the industry. By mid-2025, Hyperliquid was generating over $65 million in protocol revenue per month from trading fees – and virtually all of that went toward $HYPE repurchases, creating constant buy pressure. This deflationary token model, combined with a fixed 1B supply, means $HYPE's tokenomics are geared for long-term value accrual for loyal stakeholders. It also signals that Hyperliquid's team forgoes short-term profit (no fee revenue is taken as profit or distributed to insiders; even the core team presumably only benefits as token holders), instead funneling revenue to the community treasury and token value.
  • Liquidity Provider Rewards: A small portion of fees (≈3–8%) is used to reward liquidity providers in Hyperliquid’s unique HyperLiquidity Pool (HLP). HLP is an on-chain USDC liquidity pool that facilitates market-making and auto-settlement for the order books, analogous to an “LP vault.” Users who provide USDC to HLP earn a share of trading fees in return. By early 2025, HLP was offering depositors an ~11% annualized yield from accrued trading fees. This mechanism lets community members share in the exchange’s success by contributing capital to backstop liquidity (similar in spirit to GMX’s GLP pool, but for an orderbook system). Notably, Hyperliquid’s insurance Assistance Fund (denominated in $HYPE) also uses a portion of revenue to cover any HLP losses or unusual events – for instance, a “Jelly” exploit in Q1 2025 incurred a $12M shortfall in HLP, which was fully reimbursed to pool users. The fee buyback model was so robust that despite that hit, $HYPE buybacks continued unabated and HLP remained profitable, demonstrating strong alignment between the protocol and its community liquidity providers.

In summary, Hyperliquid’s tokenomics emphasize community ownership, security, and long-term sustainability. The absence of VC allocations and the high buyback rate were decisions that signaled confidence in organic growth. The early results have been positive – since its TGE, $HYPE’s price climbed 4× (as of mid-2025) on the back of real adoption and revenue. More importantly, users remained engaged after the airdrop; trading activity actually accelerated post-token launch, rather than suffering the typical post-incentive drop-off. This suggests the token model is successfully aligning user incentives with the platform’s growth, creating a virtuous cycle for Hyperliquid’s ecosystem.

Trading Volume, Adoption, and Liquidity in 2025

Hyperliquid by the Numbers: In 2025, Hyperliquid stands out not just for its technology but for the sheer scale of its on-chain activity. It has rapidly become the largest decentralized derivatives exchange by a wide margin, setting new benchmarks for DeFi. Key metrics illustrating Hyperliquid’s traction include:

  • Market Dominance: Hyperliquid handles roughly 70–77% of all DEX perpetual futures volume in 2025 – an 8× larger share than the next competitor. In other words, Hyperliquid by itself accounts for well over three-quarters of decentralized perp trading worldwide, making it the clear leader in its category. (For context, as of Q1 2025 this equated to about 56–73% of decentralized perp volume, up from ~4.5% at the start of 2024 – a stunning rise in one year.)
  • Trading Volumes: Cumulative trading volume on Hyperliquid blew past $1.5 trillion in mid-2025, highlighting how much liquidity has flowed through its markets. By late 2024 the exchange was already seeing daily volumes around $10–14 billion, and volume continued to climb with new user influxes in 2025. In fact, during peak market activity (e.g. a memecoin frenzy in May 2025), Hyperliquid’s weekly trading volume reached as high as $780 billion in one week – averaging well over $100B per day – rivaling or exceeding many mid-sized centralized exchanges. Even in steady conditions, Hyperliquid was averaging roughly $470B in weekly volume in the first half of 2025. This scale is unprecedented for a DeFi platform; by mid-2025 Hyperliquid was executing about 6% of *all* crypto trading volume globally (including CEXs), narrowing the gap between DeFi and CeFi.
  • Open Interest and Liquidity: The depth of Hyperliquid’s markets is also evident in its open interest (OI) – the total value of active positions. OI grew from ~3.3B at 2024’s end to around **\15** billion by mid-2025. For perspective, this OI is about 60–120% of the levels on major CEXs like Bybit, OKX, or Bitget, indicating that professional traders are as comfortable deploying large positions on Hyperliquid as on established centralized venues. Order book depth on Hyperliquid for major pairs like BTC or ETH is reported to be comparable to top CEXs, with tight bid-ask spreads. During certain token launches (e.g. the popular PUMP meme coin), Hyperliquid even achieved the deepest liquidity and highest volume of any venue, beating out CEXs for that asset. This showcases how an on-chain order book, when well-designed, can match CEX liquidity – a milestone in DEX evolution.
  • Users and Adoption: The platform’s user base has expanded dramatically through 2024–2025. Hyperliquid surpassed 500,000 unique user addresses in mid-2025. In the first half of 2025 alone, the count of active addresses nearly doubled (from ~291k to 518k). This 78% growth in six months was fueled by word-of-mouth, a successful referral & points program, and the buzz around the $HYPE airdrop (which interestingly retained users rather than just attracting mercenaries – there was no drop-off in usage after the airdrop, and activity kept climbing). Such growth indicates not just one-time curiosity but genuine adoption by traders. A significant portion of these users are believed to be “whales” and professional traders who migrated from CEXs, drawn by Hyperliquid’s liquidity and lower fees. Indeed, institutions and high-volume trading firms have begun treating Hyperliquid as a primary venue for perpetuals trading, validating DeFi’s appeal when performance issues are solved.
  • Revenue and Fees: Hyperliquid’s robust volumes translate into substantial protocol revenue (which, as noted, largely accrues to $HYPE buybacks). In the last 30 days (as of mid-2025), Hyperliquid generated about $65.45 million in protocol fees. On a daily basis that’s roughly $2.0–2.5 million in fees earned from trading activity. Annualized, the platform is on track for $800M+ in revenue – an astonishing figure that approaches revenues of some major centralized exchanges, and far above typical DeFi protocols. It underscores how Hyperliquid’s high volume and fee structure (small per-trade fees that add up at scale) produce a thriving revenue model to support its token economy.
  • Total Value Locked (TVL) and Assets: Hyperliquid’s ecosystem TVL – representing assets bridged into its chain and liquidity in its DeFi protocols – has climbed rapidly alongside trading activity. At the start of Q4 2024 (pre-token) Hyperliquid’s chain TVL was around $0.5B, but after the token launch and HyperEVM expansion, TVL soared to $2+ billion by early 2025. By mid-2025, it reached approximately $3.5 billion (June 30, 2025) and continued upward. The introduction of native USDC (via Circle) and other assets boosted on-chain capital to an estimated $5.5 billion AUM by July 2025. This includes assets in the HLP pool, DeFi lending pools, AMMs, and users’ collateral balances. Hyperliquid’s HyperLiquidity Pool (HLP) itself held a TVL around $370–500 million** in H1 2025, providing a deep USDC liquidity reserve for the exchange. Additionally, the **HyperEVM DeFi TVL** (excluding the core exchange) surpassed **\1 billion within a few months of launch, reflecting rapid growth of new dApps on the chain. These figures firmly place Hyperliquid among the largest blockchain ecosystems by TVL, despite being a specialized chain.

In summary, 2025 has seen Hyperliquid scale to CEX-like volumes and liquidity. It consistently ranks as the top DEX by volume, and even measures as a significant fraction of overall crypto trading. The ability to sustain half a trillion dollars in weekly volume on-chain, with half a million users, illustrates that the long-held promise of high-performance DeFi is being realized. Hyperliquid’s success is expanding the boundaries of what on-chain markets can do: for instance, it became the go-to venue for fast listing of new coins (it often is first to list perps for trending assets, attracting huge activity) and has proven that on-chain order books can handle blue-chip trading at scale (its BTC and ETH markets have liquidity comparable to leading CEXs). These achievements underpin Hyperliquid’s claim as a potential foundation for all on-chain finance going forward.

Comparison with Other Leading DEXs (dYdX, GMX, UniswapX, etc.)

The rise of Hyperliquid invites comparisons to other prominent decentralized exchanges. Each of the major DEX models – from order-book-based derivatives like dYdX, to liquidity pool-based perps like GMX, to spot DEX aggregators like UniswapX – takes a different approach to balancing performance, decentralization, and user experience. Below, we analyze how Hyperliquid stacks up against these platforms:

  • Hyperliquid vs. dYdX: dYdX was the early leader in decentralized perps, but its initial design (v3) relied on a hybrid approach: an off-chain order book and matching engine, combined with an L2 settlement on StarkWare. This gave dYdX decent performance but came at the cost of decentralization and composability – the order book was run by a central server, and the system was not open to general smart contracts. In late 2023, dYdX launched v4 as a Cosmos app-chain, aiming to fully decentralize the order book within a dedicated PoS chain. This is philosophically similar to Hyperliquid’s approach (both built custom chains for on-chain order matching). Hyperliquid’s key edge has been its unified architecture and head start in performance tuning. By designing HyperCore and HyperEVM together, Hyperliquid achieved CEX-level speed entirely on-chain before dYdX’s Cosmos chain gained traction. In fact, Hyperliquid’s performance surpassed dYdX – it can handle far more throughput (hundreds of thousands of tx/sec) and offers cross-contract composability that dYdX (an app-specific chain without an EVM environment) currently lacks. Artemis Research notes: earlier protocols either compromised on performance (like GMX) or on decentralization (like dYdX), but Hyperliquid delivered both, solving the deeper challenge. This is reflected in market share: by 2025 Hyperliquid commands ~75% of the perp DEX market, whereas dYdX’s share has dwindled to single digits. In practical terms, traders find Hyperliquid’s UI and speed comparable to dYdX (both offer pro exchange interfaces, advanced orders, etc.), but Hyperliquid offers greater asset variety and on-chain integration. Another difference is fee and token models: dYdX’s token is mainly a governance token with indirect fee discounts, while Hyperliquid’s $HYPE directly accrues exchange value (via buybacks) and offers staking rights. Lastly, on decentralization, both are PoS chains – dYdX had ~20 validators at launch vs Hyperliquid’s ~27 by early 2025 – but Hyperliquid’s open builder ecosystem (HyperEVM) arguably makes it more decentralized in terms of development and usage. Overall, Hyperliquid can be seen as the spiritual successor to dYdX: it took the order book DEX concept and fully on-chain-ified it with greater performance, which is evidenced by Hyperliquid pulling significant volume even from centralized exchanges (something dYdX v3 struggled to do).
  • Hyperliquid vs. GMX: GMX represents the AMM/pool-based model for perpetuals. It became popular on Arbitrum in 2022 by allowing users to trade perps against a pooled liquidity (GLP) with oracle-based pricing. GMX’s approach prioritized simplicity and zero price impact for small trades, but it sacrifices some performance and capital efficiency. Because GMX relies on price oracles and a single liquidity pool, large or frequent trades can be challenging – the pool can incur losses if traders win (GLP holders take the opposite side of trades), and oracle price latency can be exploited. Hyperliquid’s order book model avoids these issues by matching traders peer-to-peer at market-driven prices, with professional market makers providing deep liquidity. This yields far tighter spreads and better execution for big trades compared to GMX’s model. In essence, GMX’s design compromises on high-frequency performance (trades only update when oracles push prices, and there’s no rapid order placement/cancellation) whereas Hyperliquid’s design excels at it. The numbers reflect this: GMX’s volumes and OI are an order of magnitude smaller, and its market share has been dwarfed by Hyperliquid’s rise. For example, GMX typically supported under 20 markets (mostly large caps), whereas Hyperliquid offers 100+ markets including many long-tail assets – the latter is possible because maintaining many order books is feasible on Hyperliquid’s chain, whereas in GMX adding new asset pools is slower and riskier. From a user experience standpoint, GMX offers a simple swap-style interface (good for DeFi novices), while Hyperliquid provides a full exchange dashboard with charts and order books catering to advanced traders. Fees: GMX charges a ~0.1% fee on trades (which goes to GLP and GMX stakers) and has no token buyback; Hyperliquid charges very low maker/taker fees (on the order of 0.01–0.02%) and uses fees to buy back $HYPE for holders. Decentralization: GMX runs on Ethereum L2s (Arbitrum, Avalanche), inheriting strong base security, but its dependency on a centralized price oracle (Chainlink) and single liquidity pool introduces different centralized risks. Hyperliquid runs its own chain, which is newer/less battle-tested than Ethereum, but its mechanisms (order book + many makers) avoid centralized oracle dependence. In summary, Hyperliquid offers superior performance and institutional-grade liquidity relative to GMX, at the cost of more complex infrastructure. GMX proved there is demand for on-chain perps, but Hyperliquid’s order books have proven far more scalable for high-volume trading.
  • Hyperliquid vs. UniswapX (and Spot DEXs): UniswapX is a recently introduced trade aggregator for spot swaps (built by Uniswap Labs) that finds the best price across AMMs and other liquidity sources. While not a direct competitor on perpetuals, UniswapX represents the cutting-edge of spot DEX user experience. It enables gas-free, aggregation-optimized token swaps by letting off-chain “fillers” execute trades for users. By contrast, Hyperliquid’s spot trading uses its own on-chain order books (and also has a native AMM called HyperSwap in its ecosystem). For a user looking to trade tokens spot, how do they compare? Performance: Hyperliquid’s spot order books offer immediate execution with low latency, similar to a centralized exchange, and thanks to no gas fees on HyperCore, taking an order is cheap and fast. UniswapX aims to save users gas on Ethereum by abstracting execution, but ultimately the trade settlement still happens on Ethereum (or other underlying chains) and may incur latency (waiting for fillers and block confirmations). Liquidity: UniswapX sources liquidity from many AMMs and market makers across multiple DEXs, which is great for long-tail tokens on Ethereum; however, for major pairs, Hyperliquid’s single order book often has deeper liquidity and less slippage because all traders congregate in one venue. Indeed, after launching spot markets in March 2024, Hyperliquid quickly saw spot volumes surge to record levels, with large traders bridging assets like BTC, ETH, and SOL into Hyperliquid for spot trading due to the superior execution, then bridging back out. UniswapX excels at breadth of token access, whereas Hyperliquid focuses on depth and efficiency for a more curated set of assets (those listed via its governance/auction process). Decentralization and UX: Uniswap (and X) leverage Ethereum’s very decentralized base and are non-custodial, but aggregators like UniswapX do introduce off-chain actors (fillers relaying orders) – albeit in a permissionless way. Hyperliquid’s approach keeps all trading actions on-chain with full transparency, and any asset listed on Hyperliquid gets the benefits of native order book trading plus composability with its DeFi apps. The user experience on Hyperliquid is closer to a centralized trading app (which advanced users prefer), while UniswapX is more like a “meta-DEX” for one-click swaps (convenient for casual trades). Fees: UniswapX’s fees depend on the DEX liquidity used (typically 0.05–0.3% on AMMs) plus possibly a filler incentive; Hyperliquid’s spot fees are minimal and often offset by $HYPE discounts. In short, Hyperliquid competes with Uniswap and other spot DEXs by offering a new model: an order-book-based spot exchange on a custom chain. It has carved out a niche where high-volume spot traders (especially for large-cap assets) prefer Hyperliquid for its deeper liquidity and CEX-like experience, whereas retail users swapping obscure ERC-20s may still prefer Uniswap’s ecosystem. Notably, Hyperliquid’s ecosystem even introduced Hyperswap (an AMM on HyperEVM with ~$70M TVL) to capture long-tail tokens via AMM pools – acknowledging that AMMs and order books can coexist, serving different market segments.

Summary of Key Differences: The table below outlines a high-level comparison:

DEX PlatformDesign & ChainTrading ModelPerformanceDecentralizationFee Mechanism
HyperliquidCustom L1 (HyperBFT PoS, ~27 validators)On-chain CLOB for perps/spot; also EVM apps~0.5s finality, 100k+ tx/sec, CEX-like UIPoS chain (community-run, unified state for dApps)Tiny trading fees, ~97% of fees buy back $HYPE (indirectly rewarding holders)
dYdX v4Cosmos SDK app-chain (PoS, ~20 validators)On-chain CLOB for perps only (no general smart contracts)~1-2s finality, high throughput (order matching by validators)PoS chain (decentralized matching, but not EVM-composable)Trading fees paid in USDC; DYDX token for governance & discounts (no fee buyback)
GMXArbitrum & Avalanche (Ethereum L2/L1)AMM pooled liquidity (GLP) with oracle pricing for perpsDependent on oracle update (~30s); good for casual trades, not HFTSecured by Ethereum/Avax L1; fully on-chain but relies on centralized oracles~0.1% trading fee; 70% to liquidity providers (GLP), 30% to GMX stakers (revenue sharing)
UniswapXEthereum mainnet (and cross-chain)Aggregator for spot swaps (routes across AMMs or RFQ market makers)~12s Ethereum block time (fills abstracted off-chain); gas fees abstractedRuns on Ethereum (high base security); uses off-chain filler nodes for executionUses underlying AMM fees (0.05–0.3%) + potential filler incentive; UNI token not required for use

In essence, Hyperliquid has set a new benchmark by combining the strengths of these approaches without the usual weaknesses: it offers the sophisticated order types, speed, and liquidity of a CEX (surpassing dYdX’s earlier attempt), without sacrificing the transparency and permissionless nature of DeFi (improving on GMX’s performance and Uniswap’s composability). As a result, rather than simply stealing market share from dYdX or GMX, Hyperliquid actually expanded the on-chain trading market by attracting traders who previously stayed on CEXs. Its success has spurred others to evolve – for example, even Coinbase and Robinhood have eyed entering the on-chain perps market, though with much lower leverage and liquidity so far. If this trend continues, we can expect a competitive push where both CEXs and DEXs race to combine performance with trustlessness – a race where Hyperliquid currently enjoys a strong lead.

Ecosystem Growth, Partnerships, and Community Initiatives

One of Hyperliquid’s greatest achievements in 2025 is growing from a single-product exchange into a thriving blockchain ecosystem. The launch of HyperEVM unlocked a Cambrian explosion of projects and partnerships building around Hyperliquid’s core, making it not just a trading venue but a full DeFi and Web3 environment. Here we explore the ecosystem’s expansion and key strategic alliances:

Ecosystem Projects and Developer Traction: Since early 2025, dozens of dApps have deployed on Hyperliquid, attracted by its built-in liquidity and user base. These span the gamut of DeFi primitives and even extend to NFTs and gaming:

  • Decentralized Exchanges (DEXs): Besides Hyperliquid’s native order books, community-built DEXs have appeared to serve other needs. Notably, Hyperswap launched as an AMM on HyperEVM, quickly becoming the leading liquidity hub for long-tail tokens (it amassed >70M TVL and \2B volume within 4 months). Hyperswap’s automated pools complement Hyperliquid’s CLOB by allowing permissionless listing of new tokens and providing an easy venue for projects to bootstrap liquidity. Another project, KittenSwap (a Velodrome fork with ve(3,3) tokenomics), also went live to offer incentivized AMM trading for smaller assets. These DEX additions ensure that even meme coins and experimental tokens can thrive on Hyperliquid via AMMs, while the major assets trade on order books – a synergy that drives overall volume.
  • Lending and Yield Protocols: The Hyperliquid ecosystem now features money markets and yield optimizers that interlink with the exchange. HyperBeat is a flagship lending/borrowing protocol on HyperEVM (with ~145M TVL as of mid-2025). It allows users to deposit assets like \HYPE, stablecoins, or even LP tokens to earn interest, and to borrow against collateral to trade on Hyperliquid with extra leverage. Because HyperBeat can read Hyperliquid’s order book prices directly and even trigger on-chain liquidations via HyperCore, it operates more efficiently and safely than cross-chain lending protocols. Yield aggregators are emerging too – HyperBeat’s “Hearts” rewards program and others incentivize providing liquidity or vault deposits. Another notable entrant is Kinetiq, a liquid staking project for $HYPE that drew over $400M in deposits on day one, indicating huge community appetite for earning yield on HYPE. Even external Ethereum-based protocols are integrating: EtherFi, a major liquid staking provider (with ~$9B in ETH staked) announced a collaboration to bring staked ETH and new yield strategies into Hyperliquid via HyperBeat. This partnership will introduce beHYPE, a liquid staking token for HYPE, and potentially bring EtherFi’s staked ETH as collateral to Hyperliquid’s markets. Such moves show confidence from established DeFi players in the Hyperliquid ecosystem’s potential.
  • Stablecoins and Crypto Banking: Recognizing the need for stable on-chain currency, Hyperliquid has attracted both external and native stablecoin support. Most significantly, Circle (issuer of USDC) formed a strategic partnership to launch native USDC on Hyperliquid in 2025. Using Circle’s Cross-Chain Transfer Protocol (CCTP), users will be able to burn USDC on Ethereum and mint 1:1 USDC on Hyperliquid, eliminating wrappers and enabling direct stablecoin liquidity on the chain. This integration is expected to streamline large transfers of capital into Hyperliquid and reduce reliance on only bridged USDT/USDC. In fact, by the time of announcement, Hyperliquid’s assets under management surged to $5.5B, partly on anticipation of native USDC support. On the native side, projects like Hyperstable have launched an over-collateralized stablecoin (USH) on HyperEVM with yield-bearing governance token PEG – adding diversity to the stablecoin options available for traders and DeFi users.
  • Innovative DeFi Infrastructure: Hyperliquid’s unique capabilities have spurred innovation in DEX design and derivatives. Valantis, for example, is a modular DEX protocol on HyperEVM that lets developers create custom AMMs and “sovereign pools” with specialized logic. It supports advanced features like rebase tokens and dynamic fees, and has $44M TVL, showcasing that teams see Hyperliquid as fertile ground for pushing DeFi design forward. For perpetuals specifically, the community passed HIP-3 which opened Hyperliquid’s Core engine to anyone who wants to launch a new perpetual market. This is a game-changer: it means if a user wants a perp market for, say, a stock index or a commodity, they can deploy it (subject to governance parameters) without needing Hyperliquid’s team – a truly permissionless derivative framework much like Uniswap did for ERC20 swaps. Already, community-launched markets for novel assets are appearing, demonstrating the power of this openness.
  • Analytics, Bots, and Tooling: A vibrant array of tools has emerged to support traders on Hyperliquid. For instance, PvP.trade is a Telegram-based trading bot that integrates with Hyperliquid’s API, enabling users to execute perp trades via chat and even follow friends’ positions for a social trading experience. It ran a points program and token airdrop that proved quite popular. On the analytics side, AI-driven platforms like Insilico Terminal and Katoshi AI have added support for Hyperliquid, providing traders with advanced market signals, automated strategy bots, and predictive analytics tailored to Hyperliquid’s markets. The presence of these third-party tools indicates that developers view Hyperliquid as a significant market – worth building bots and terminals for – similar to how many tools exist for Binance or Uniswap. Additionally, infrastructure providers have embraced Hyperliquid: QuickNode and others offer RPC endpoints for the Hyperliquid chain, Nansen has integrated Hyperliquid data into its portfolio tracker, and blockchain explorers and aggregators are supporting the network. This infrastructure adoption is crucial for user experience and signifies that Hyperliquid is recognized as a major network in the multi-chain landscape.
  • NFTs and Gaming: Beyond pure finance, Hyperliquid’s ecosystem also dabbles in NFTs and crypto gaming, adding community flavor. HypurrFun is a meme coin launchpad that gained attention by using a Telegram bot auction system to list jokey tokens (like $PIP and $JEFF) on Hyperliquid’s spot market. It provided a fun, Pump.win-style experience for the community and was instrumental in testing Hyperliquid’s token auction mechanisms pre-HyperEVM. NFT projects like Hypio (an NFT collection integrating DeFi utility) have launched on Hyperliquid, and even an AI-powered game (TheFarm.fun) is leveraging the chain for minting creative NFTs and planning a token airdrop. These may be niche, but they indicate an organic community forming – traders who also engage in memes, NFTs, and social games on the same chain, increasing user stickiness.

Strategic Partnerships: Alongside grassroots projects, Hyperliquid’s team (via the Hyper Foundation) has actively pursued partnerships to extend its reach:

  • Phantom Wallet (Solana Ecosystem): In July 2025, Hyperliquid announced a major partnership with Phantom, the popular Solana wallet, to bring in-wallet perpetuals trading to Phantom’s users. This integration allows Phantom’s mobile app (with millions of users) to trade Hyperliquid perps natively, without leaving the wallet interface. Over 100+ markets with up to 50× leverage became available in Phantom, covering BTC, ETH, SOL and more, with built-in risk controls like stop-loss orders. The significance is twofold: it gives Solana community users easy access to Hyperliquid’s markets (bridging ecosystems), and it showcases Hyperliquid’s API and backend strength – Phantom wouldn’t integrate a DEX that couldn’t handle large user flow. Phantom’s team highlighted that Hyperliquid’s liquidity and quick settlement were key to delivering a smooth mobile trading UX. This partnership essentially embeds Hyperliquid as the “perps engine” inside a leading crypto wallet, dramatically lowering friction for new users to start trading on Hyperliquid. It’s a strategic win for user acquisition and demonstrates Hyperliquid’s intent to collaborate rather than compete with other ecosystems (Solana in this case).
  • Circle (USDC): As mentioned, Circle’s partnership to deploy native USDC via CCTP on Hyperliquid is a cornerstone integration. It not only legitimizes Hyperliquid as a first-class chain in the eyes of a major stablecoin issuer, but it also solves a critical piece of infrastructure: fiat liquidity. When Circle turns on native USDC for Hyperliquid, traders will be able to transfer dollars in/out of Hyperliquid’s network with the same ease (and trust) as moving USDC on Ethereum or Solana. This streamlines arbitrage and cross-exchange flows. Additionally, Circle’s Cross-Chain Transfer Protocol v2 will allow USDC to move between Hyperliquid and other chains without intermediaries, further integrating Hyperliquid into the multi-chain liquidity network. By July 2025, anticipation of USDC and other assets coming on board had already driven Hyperliquid’s total asset pools to $5.5B. We can expect this number to grow once the Circle integration is fully live. In essence, this partnership addresses one of the last barriers for traders: easy fiat on/off ramps into Hyperliquid’s high-speed environment.
  • Market Makers and Liquidity Partners: While not always publicized, Hyperliquid has likely cultivated relationships with professional market-making firms to bootstrap its order book liquidity. The depth observed (often rivaling Binance on some pairs) suggests that major crypto liquidity providers (possibly firms like Wintermute, Jump, etc.) are actively making markets on Hyperliquid. One indirect indicator: Auros Global, a trading firm, published a “Hyperliquid listing 101” guide in early 2025 noting Hyperliquid averaged $6.1B daily perps volume in Q1 2025, which implies market makers are paying attention. Additionally, Hyperliquid’s design (with incentives like maker rebates or HLP yields) and the no-gas benefit are very attractive to HFT firms. Although specific MM partnerships aren’t named, the ecosystem clearly benefits from their participation.
  • Others: The Hyper Foundation, which stewards protocol development, has begun initiatives like a Delegation Program to incentivize reliable validators and global community programs (a Hackathon with $250k prizes was held in 2025). These help strengthen the network’s decentralization and bring in new talent. There’s also collaboration with oracle providers (Chainlink or Pyth) for external data when needed – e.g. if any synthetic real-world asset markets launch, those partnerships will be important. Given that Hyperliquid is EVM-compatible, tooling from Ethereum (like Hardhat, The Graph, etc.) can be relatively easily extended to Hyperliquid as developers demand.

Community and Governance: Community engagement in Hyperliquid has been high due to the early airdrop and ongoing governance votes. The Hyperliquid Improvement Proposal (HIP) framework has seen important proposals (HIP-1 to HIP-3) passed in its first year, signaling an active governance process. The community has played a role in token listings via Hyperliquid’s auction model – new tokens launch through an on-chain auction (often facilitated by HypurrFun or similar), and successful auctions get listed on the order book. This process, while permissioned by a fee and vetting, has allowed community-driven tokens (like meme coins) to gain traction on Hyperliquid without centralized gatekeeping. It also helped Hyperliquid avoid spam tokens since there’s a cost to list, ensuring only serious projects or enthusiastic communities pursue it. The result is an ecosystem that balances permissionless innovation with a degree of quality control – a novel approach in DeFi.

Moreover, the Hyper Foundation (a non-profit entity) was set up to support ecosystem growth. It has been responsible for initiatives like the $HYPE token launch and managing the incentive funds. The Foundation’s decision to not issue incentives recklessly (as noted in The Defiant, they provided no extra liquidity mining after the airdrop) may have initially tempered some yield-farmers, but it underscores a focus on organic usage over short-term TVL boosts. This strategy appears to have paid off with steady growth. Now, moves like EtherFi’s involvement and others show that even without massive liquidity mining, real DeFi activity is taking root on Hyperliquid due to its unique opportunities (like high yields from actual fee revenue and access to an active trading base).

To summarize, Hyperliquid in 2025 is surrounded by a flourishing ecosystem and strong alliances. Its chain is home to a comprehensive DeFi stack – from perps and spot trading, to AMMs, lending, stablecoins, liquid staking, NFTs, and beyond – much of which sprung up just in the past year. Strategic partnerships with the likes of Phantom and Circle are expanding its user reach and liquidity access across the crypto universe. The community-driven aspects (auctions, governance, hackathons) show an engaged user base that is increasingly invested in Hyperliquid's success. All these factors reinforce Hyperliquid's position as more than an exchange; it's becoming a holistic financial layer.

Future Outlook: Hyperliquid’s Vision for Onchain Finance (Derivatives, RWAs, and Beyond)

Hyperliquid’s rapid ascent begs the question: What’s next? The project’s vision has always been ambitious – to become the foundational infrastructure for all of onchain finance. Having achieved dominance in on-chain perps, Hyperliquid is poised to expand into new products and markets, potentially reshaping how traditional financial assets interact with crypto. Here are some key elements of its forward-looking vision:

  • Expanding the Derivatives Suite: Perpetual futures were the initial beachhead, but Hyperliquid can extend to other derivatives. The architecture (HyperCore + HyperEVM) could support additional instruments like options, interest rate swaps, or structured products. A logical next step might be an on-chain options exchange or an options AMM launching on HyperEVM, leveraging the chain’s liquidity and fast execution. With unified state, an options protocol on Hyperliquid could directly hedge via the perps order book, creating efficient risk management. We haven’t seen a major on-chain options platform emerge on Hyperliquid yet, but given the ecosystem’s growth, it’s plausible for 2025-26. Additionally, traditional futures and tokenized derivatives (e.g. futures on stock indices, commodities, or FX rates) could be introduced via HIP proposals – essentially bringing traditional finance markets on-chain. Hyperliquid’s HIP-3 already paved the way for listing “any asset, crypto or traditional” as a perp market so long as there’s an oracle or price feed. This opens the door for community members to launch markets on equities, gold, or other assets in a permissionless way. If liquidity and legal considerations allow, Hyperliquid could become a hub for 24/7 tokenized trading of real-world markets, something even many CEXs don’t offer at scale. Such a development would truly realize the vision of a unified global trading platform on-chain.
  • Real-World Assets (RWAs) and Regulated Markets: Bridging real-world assets into DeFi is a major trend, and Hyperliquid is well-positioned to facilitate it. Through HyperUnit and partnerships like Circle, the chain is integrating with real assets (fiat via USDC, BTC/SOL via wrapped tokens). The next step might be tokenized securities or bonds trading on Hyperliquid. For example, one could imagine a future where government bonds or stocks are tokenized (perhaps under regulatory sandbox) and traded on Hyperliquid’s order books 24/7. Already, Hyperliquid’s design is “regulatory-aware” – the use of native assets instead of synthetic IOUs can simplify compliance. The Hyper Foundation could explore working with jurisdictions to allow certain RWAs on the platform, especially as on-chain KYC/whitelisting tech improves (HyperEVM could support permissioned pools if needed for regulated assets). Even without formal RWA tokens, Hyperliquid’s permissionless perps could list derivatives that track RWAs (for instance, a perpetual swap on the S&P 500 index). That would bring RWA exposure to DeFi users in a roundabout but effective way. In summary, Hyperliquid aims to blur the line between crypto markets and traditional markets – to house all finance, you eventually need to accommodate assets and participants from the traditional side. The groundwork (in tech and liquidity) is being laid for that convergence.
  • Scaling and Interoperability: Hyperliquid will continue to scale vertically (more throughput, more validators) and likely horizontally via interoperability. With Cosmos IBC or other cross-chain protocols, Hyperliquid might connect to wider networks, allowing assets and messages to flow trustlessly. It already uses Circle’s CCTP for USDC; integration with something like Chainlink’s CCIP or Cosmos’s IBC could extend cross-chain trading possibilities. Hyperliquid could become a liquidity hub that other chains tap into (imagine dApps on Ethereum or Solana executing trades on Hyperliquid via trustless bridges – getting Hyperliquid’s liquidity without leaving their native chain). The mention of Hyperliquid as a “liquidity hub” and its growing open interest share (already ~18% of the entire crypto futures OI by mid-2025) indicates it might anchor a larger network of DeFi protocols. The Hyper Foundation’s collaborative approach (e.g. partnering with wallets, other L1s) suggests they see Hyperliquid as part of a multi-chain future rather than an isolated island.
  • Advanced DeFi Infrastructure: By combining a high-performance exchange with general programmability, Hyperliquid could enable sophisticated financial products that were not previously feasible on-chain. For example, on-chain hedge funds or vault strategies can be built on HyperEVM that execute complex strategies directly through HyperCore (arbitrage, automated market making on order books, etc.) all on one chain. This vertical integration eliminates inefficiencies like moving funds across layers or being front-run by MEV bots during cross-chain arbitrage – everything can happen under HyperBFT consensus with full atomicity. We may see growth in automated strategy vaults that use Hyperliquid’s primitives to generate yield (some early vaults likely exist already, possibly run by HyperBeat or others). Hyperliquid’s founder summarized the strategy as “polish a native application and then grow into general-purpose infrastructure”. Now that the native trading app is polished and a broad user base is present, the door is open for Hyperliquid to become a general DeFi infrastructure layer. This could put it in competition not just with DEXs but with Layer-1s like Ethereum or Solana for hosting financial dApps – albeit Hyperliquid’s specialty will remain anything requiring deep liquidity or low latency.
  • Institutional Adoption and Compliance: Hyperliquid’s future likely involves courting institutional players – hedge funds, market makers, even fintech firms – to use the platform. Already, institutional interest is rising given the volumes and the fact that firms like Coinbase, Robinhood, and others are eyeing perps. Hyperliquid might position itself as the infrastructure provider for institutions to go on-chain. It could offer features like sub-accounts, compliance reporting tools, or whitelisted pools (if needed for certain regulated users) – all while preserving the public, on-chain nature for retail. The regulatory climate will influence this: if jurisdictions clarify the status of DeFi derivatives, Hyperliquid could either become a licensed venue in some form or remain a purely decentralized network that institutions plug into indirectly. The mention of “regulatory-aware design” suggests the team is mindful of striking a balance that allows real-world integration without falling afoul of laws.
  • Continuous Community Empowerment: As the platform grows, more decision-making may shift to token holders. We can expect future HIPs to cover things like adjusting fee parameters, allocating the incentive fund (the ~39% of supply set aside), introducing new products (e.g. if an options module were proposed), and expanding validator sets. The community will play a big role in guiding Hyperliquid’s trajectory, effectively acting as the shareholders of this decentralized exchange. The community treasury (funded by any tokens not yet distributed and possibly by any revenue not used in buybacks) could be directed to fund new projects on Hyperliquid or provide grants, further bolstering ecosystem development.

Conclusion: Hyperliquid in 2025 has achieved what many thought impossible: a fully on-chain exchange that rivals centralized platforms in performance and liquidity. Its technical architecture – HyperBFT, HyperCore, HyperEVM – has proven to be a blueprint for the next generation of financial networks. The $HYPE token model aligns the community tightly with the platform’s success, creating one of the most lucrative and deflationary token economies in DeFi. With massive trading volumes, a ballooning user base, and a fast-growing DeFi ecosystem around it, Hyperliquid has positioned itself as a premier layer-1 for financial applications. Looking ahead, its vision of becoming “the blockchain to house all finance” does not seem far-fetched. By bringing more asset classes on-chain (potentially including real-world assets) and continuing to integrate with other networks and partners, Hyperliquid could serve as the backbone for a truly global, 24/7, decentralized financial system. In such a future, the lines between crypto and traditional markets blur – and Hyperliquid’s blend of high performance and trustless architecture may well be the model that bridges them, building the future of onchain finance one block at a time.

Sources:

  1. QuickNode Blog – “Hyperliquid in 2025: A High-Performance DEX...” (Architecture, metrics, tokenomics, vision)
  2. Artemis Research – “Hyperliquid: A Valuation Model and Bull Case” (Market share, token model, comparisons)
  3. The Defiant – “EtherFi Expands to HyperLiquid…HyperBeat” (Ecosystem TVL, institutional interest)
  4. BlockBeats – “Inside Hyperliquid’s Growth – Semiannual Report 2025” (On-chain metrics, volume, OI, user stats)
  5. Coingape – “Hyperliquid Expands to Solana via Phantom Partnership” (Phantom wallet integration, mobile perps)
  6. Mitrade/Cryptopolitan – “Circle integrates USDC with Hyperliquid” (Native USDC launch, $5.5B AUM)
  7. Nansen – “What is Hyperliquid? – Blockchain DEX & Trading Explained” (Technical overview, sub-second finality, token uses)
  8. DeFi Prime – “Exploring the Hyperliquid Chain Ecosystem: Deep Dive” (Ecosystem projects: DEXs, lending, NFTs, etc.)
  9. Hyperliquid Wiki/Docs – Hyperliquid GitBook & Stats (Asset listings via HIPs, stats dashboard)
  10. CoinMarketCap – Hyperliquid (HYPE) Listing (Basic info on Hyperliquid L1 and on-chain order book design)

Quantitative Trading: How to Build Your Own Algorithmic Trading Business

· 28 min read
Dora Noda
Software Engineer

1. Overall Overview

Quantitative Trading: How to Build Your Own Algorithmic Trading Business is a practical guide written by quantitative trading expert Dr. Ernest P. Chan (often called Ernie Chan), designed to help independent traders build and operate their own algorithmic trading businesses. The first edition was published by Wiley in 2009 as part of its Wiley Trading series, spanning approximately 200 pages. More than a decade after the first edition, the author released a second edition in 2021 (ISBN: 9781119800064, 256 pages), updating and expanding its content.

  • Target Audience: The book is aimed at individual investors and small trading teams who wish to use quantitative methods for trading, as well as readers aspiring to work in quantitative trading at financial institutions. The author assumes readers have a basic knowledge of mathematics, statistics, an d programming but does not require an advanced degree. He emphasizes that even a high school-level background in math, statistics, programming, or economics is sufficient to get started with basic quantitative strategies. As the book states: "If you have taken a few high school-level courses in mathematics, statistics, computer programming, or economics, you are probably as qualified as anyone to try your hand at some basic statistical arbitrage strategies." This accessible positioning significantly lowers the barrier to entry for quantitative trading, reflecting the book's mission of "democratizing quantitative trading."

  • Main Content: The book is structured around the complete process of developing, testing, and executing quantitative trading strategies, from idea conception to business setup. The author begins by explaining what quantitative trading is and why individual traders can compete with institutions in this field. He then delves into topics such as finding ideas for trading strategies, conducting historical backtests to validate strategy effectiveness, building trading infrastructure and execution systems, and implementing proper money and risk management. The book discusses not only technical details (like data processing, model selection, and backtesting pitfalls) but also business-level considerations (such as the organizational structure of a trading business, broker selection, and hardware/software configuration). Furthermore, the author uses examples and case studies to demonstrate the implementation of specific strategies like mean-reversion, momentum, factor models, and seasonal effects, providing corresponding code or pseudocode to aid reader comprehension.

  • Impact and Influence: As one of the classic introductory texts in the quantitative trading field, the book has been widely acclaimed since its publication and is regarded as one of the "bibles for independent quantitative traders." Many readers believe that among the numerous books and articles on quantitative trading, Dr. Chan's work stands out for its practical value. As one industry insider commented: "Many books on quantitative trading are written by authors with no practical experience, or they hold back from revealing their trading secrets. Ernie adheres to a different philosophy: sharing meaningful information and engaging deeply with the quantitative community. He has successfully distilled a vast amount of detailed and complex subject matter into a clear and comprehensive resource from which both novices and professionals can benefit." Following the publication of the first edition, Dr. Chan remained active in the quantitative trading space for over a decade, authoring books like Algorithmic Trading (2013) and Machine Trading (2017) to expand on related topics. In the second edition released in 2021, the author updated the technology and case studies, adding new machine learning techniques for parameter optimization, Python and R code examples, and the latest strategy backtest results, keeping the content current with contemporary developments in quantitative trading. Although tools and market environments have evolved, as emphasized in the preface to the second edition, the fundamental principles of quantitative trading taught in the book have stood the test of time, and its core concepts remain applicable more than a decade later.

In summary, Quantitative Trading is a practice-oriented guide that provides readers with a roadmap to build quantitative trading strategies and businesses from scratch. It helps independent traders challenge Wall Street professionals and offers a valuable knowledge framework and practical tools for investors seeking a systematic and objective approach to trading.

2. Core Ideas Distilled

The book embodies the author's key viewpoints and philosophy on quantitative trading. The core ideas are distilled below:

  • The Essence of Quantitative Trading: Data-Driven, Transcending Subjective Judgment. Quantitative trading (or algorithmic trading) refers to a trading method where buy and sell decisions are made entirely by computer algorithms. This is not merely an upgrade of traditional technical analysis but a process that transforms any quantifiable information (prices, fundamental indicators, news sentiment, etc.) into algorithmic inputs, executed by an automated system to eliminate the influence of human emotions and subjective biases on trading decisions. In simple terms, quantitative trading aims to achieve excess returns in a systematic and disciplined manner, using computers to strictly follow tested strategies and adhere to predefined rules regardless of market conditions or personal feelings.

  • The Democratization of Quantitative Trading: An Arena Open to Individuals. Chan emphasizes that quantitative trading is no longer the exclusive domain of large Wall Street institutions. With modern computing resources and public data, individual investors can also make their mark in this field. The author points out that possessing basic mathematical and statistical concepts and some programming/Excel skills is sufficient to develop and test simple statistical arbitrage strategies. This proliferation of technology and knowledge gives independent traders the opportunity to challenge institutional traders in certain niche areas, thus redefining the competitive landscape. The author encourages readers to leverage open-source tools and inexpensive data sources, approaching quantitative trading with a spirit of small-scale experimentation, rather than being intimidated by the high barriers of financial engineering.

  • Rigorous Backtesting and Avoiding Pitfalls. Throughout the book, Chan repeatedly stresses that backtesting (testing on historical data) is the core of quantitative strategy development and a crucial basis for independent traders to build confidence and persuade potential investors (if any). However, he warns readers to be cautious with backtest results and to guard against common biases and pitfalls. For instance, he discusses in detail issues like look-ahead bias, data-snooping bias, and survivorship bias, as well as the risks of insufficient sample size and overfitting, which can create "illusory profits." The author recommends using out-of-sample testing by dividing data into training and testing sets, performing sensitivity analysis on strategy parameters, and considering real-world transaction costs and slippage to ensure that strategy returns are robust and not merely a product of curve-fitting.

  • The Importance of Business Architecture and Automated Execution. Chan treats quantitative trading as a serious business, not a hobby, reminding readers to focus on the organizational and execution architecture of their trading business in addition to the technology. He discusses the differences between being an independent retail trader and joining a professional trading firm, weighing the pros and cons of aspects like account permissions, leverage limits, and regulatory requirements. Regardless of the model, the author emphasizes that building reliable trading infrastructure and an automated trading system is crucial. On one hand, a semi-automated or fully automated system can significantly reduce the intensity of manual operations and the probability of errors, ensuring consistent strategy execution. On the other hand, good infrastructure (including high-speed, stable internet, low-latency order execution APIs, and rigorous monitoring and alert systems) can help independent traders narrow the execution efficiency gap with large institutions. The author notes that automated trading also helps reduce transaction costs (e.g., through algorithmic order optimization and avoiding high-fee periods) and control the deviation between actual and expected performance, as live results often differ from backtested returns, a problem that can be identified early through simulated trading.

  • Money Management and Risk Control: Survive First, Then Thrive. Risk management is placed on an equal, if not higher, level of importance as strategy development. Chan delves into how to determine optimal capital allocation and leverage ratios to enhance returns while controlling risk. The book introduces methods like the Kelly Criterion to calculate the optimal bet size given a certain win rate and payoff ratio, complete with mathematical derivations for the reader's reference. The author also elaborates on a range of risk categories, such as model risk (the risk of the strategy model itself failing), software risk (losses due to programming bugs or system failures), and extreme event risk (abnormal losses from natural disasters or black swan events). These risks are often overlooked by novices, but Chan reminds readers that they must have contingency plans. Furthermore, he emphasizes the importance of psychological preparedness: traders need the mental fortitude and discipline to withstand consecutive losses and continue executing the strategy as long as its statistical edge remains, without deviating from the plan due to short-term setbacks. Overall, his philosophy on money and risk management is to first ensure that devastating losses are avoided while pursuing profit maximization. Only by surviving can one hope to profit in the long run.

  • Mean Reversion vs. Momentum Trading: A Trade-off of Different Philosophies. In discussing special topics, Chan provides a comparative analysis of mean-reversion and trend-following (momentum) strategies. He points out that all trading strategies profit on the premise that prices either exhibit mean-reverting characteristics or trend-continuing characteristics; otherwise, if prices follow a random walk, there is no profit to be made. Mean-reversion strategies are based on the idea that prices will eventually return to their long-term equilibrium after deviating, so these strategies often take counter-trend positions, profiting from the correction of excessive volatility. Momentum strategies, conversely, assume that once a trend (up or down) is established, it will persist for some time, so they follow the trend, profiting by riding its continuation. The author particularly emphasizes the different roles of stop-loss orders in these two types of trading. In momentum strategies, if the price moves against the position, it likely signals a trend reversal, and a timely stop-loss can prevent larger losses. In mean-reversion strategies, however, an adverse price movement might just be a normal deviation, and a premature stop-loss could cause one to miss the subsequent profit opportunity as the price reverts to the mean. However, identifying whether the market is currently in a trending or mean-reverting state is not easy—news or fundamental-driven moves are often trending, and one should not "try to stand in front of a freight train" by shorting against the trend. Conversely, non-news-driven fluctuations are more likely to be mean-reverting. He also explores the mechanisms that generate momentum (such as post-earnings announcement drift caused by information diffusion lags, and investor herding behavior) and notes that increased competition shortens the duration of momentum. As information spreads faster and more traders participate, the window for trend continuation often becomes shorter. Consequently, momentum models need constant adjustment to adapt to a faster pace. For mean-reversion strategies, the author introduces statistical methods to estimate the half-life of mean reversion to select holding periods, which is less reliant on subjective judgment than momentum strategies. In summary, Chan advises traders to adopt different risk control and parameter optimization methods based on the strategy's characteristics, fully understanding the performance differences between "mean-reversion" and "momentum" strategies under different market states. The table below summarizes some of the book's comparisons of these two strategy types:

FeatureMean-Reversion StrategyMomentum Strategy
Core LogicPrices revert to a historical mean.Price trends will continue.
Entry SignalBuy when price is low, sell when high (relative to mean).Buy when price is rising, sell when falling.
PositioningCounter-trend (contrarian).Trend-following.
Role of Stop-LossRisky; can exit prematurely before reversion.Crucial; signals a potential trend reversal.
Profit SourceCorrection of over-reactions and volatility.Riding the continuation of a price move.
Market ConditionBest in ranging or non-trending markets.Best in trending markets (driven by news, fundamentals).
Typical ChallengeIdentifying a true, stable mean.Identifying the start and end of a trend.
  • The Niche Advantage of Independent Traders: Fly Under the Radar, Focus on Niche Strategies. The author believes that for independent traders to succeed, they should choose strategy areas that are not on the radar of large institutions or are difficult for them to engage in, thereby leveraging the advantage of being "small and nimble." He proposes that when evaluating a strategy, one should ask: "Is this strategy outside the 'radar' coverage of institutional funds?" That is, try to discover obscure strategies or assets, because if a strategy is too obvious and has high capacity, the major players on Wall Street are likely already involved, leaving little room and alpha for smaller players. Conversely, in some niche markets or with specific strategies (such as very short-term statistical arbitrage or strategies driven by very new alternative data), individual traders may be able to avoid direct competition with giants and earn relatively stable excess returns. Chan encourages independent traders to cultivate a keen sense for subtle market inefficiencies. Even if a strategy seems simple and has a low profit margin, if it can consistently make money and does not compete head-on with large funds, it is a good strategy worth considering. This philosophy of "surviving in the cracks" permeates the book and is reflected in the expectations he sets for the reader: rather than fantasizing about finding a magic formula to disrupt the market, it is better to build a few small but effective trading strategies and accumulate returns over time.

These core ideas form the foundation of the author's quantitative trading philosophy: treat trading rationally using scientific methodologies and tools, simplify complex problems, focus on one's own advantages and market inefficiencies, and adhere to discipline for long-term, stable returns.

3. Detailed Chapter Summaries

The book is divided into 8 chapters by theme, along with several appendices. The following is an overview of the main content and key concepts of each chapter:

  • Chapter 1. The Whats, Whos, and Whys of Quantitative Trading This opening chapter answers three fundamental questions: "What is quantitative trading, who can do it, and why should they?" The author first defines quantitative trading: a trading method that uses computer algorithms to make decisions automatically based on quantitative indicators, distinguishing it from traditional technical analysis and discretionary trading. Next, the author addresses the question of who can become a quantitative trader, emphasizing that independent traders can be perfectly competent with basic math, programming, and statistical intuition, without needing a prestigious degree or a Wall Street background. He lists several major advantages of independent quantitative trading, which constitute its business value: first, Scalability (an effective algorithmic strategy can proportionally increase profits as capital grows); second, Time Efficiency (algorithms can run automatically, reducing the need for manual monitoring, allowing a trader to manage multiple strategies and have more free time); third, since decisions are entirely data-driven, little to no marketing is needed to validate a strategy's effectiveness (unlike manual trading, which requires telling a story to attract capital)—the performance itself is the best "marketing." These factors together form the business motivation for individuals to engage in quantitative trading. The chapter concludes by outlining the development trajectory of quantitative trading and the reader's path forward, encouraging beginners to start with small capital and simple strategies, gradually accumulating experience and capital (a pyramid-style growth), and setting the stage for subsequent chapters.

  • Chapter 2. Fishing for Ideas This chapter focuses on how to capture and evaluate ideas for quantitative trading strategies. The author first answers "where to find good strategy ideas," pointing out that inspiration can come from various sources: academic papers, financial blogs, trading forums, business news, and even everyday experiences. But more importantly, he discusses how to assess whether a strategy is suitable for you. Chan provides a series of self-assessment dimensions to help readers filter strategies that match their personal circumstances:

    • Available Work Time: Some strategies require high-frequency monitoring and position adjustments, suitable for full-time traders. For those who can only trade part-time, they should choose low-frequency or end-of-day execution strategies.
    • Programming Ability: If a reader's programming skills are not strong, they can start with simple strategies in Excel or chart-based trading. Conversely, those proficient in programming can directly implement complex models using MATLAB, Python, etc.
    • Trading Capital Size: The amount of capital affects strategy choice. Small capital is suitable for low-capacity strategies like short-term trading in small-cap stocks or high-frequency arbitrage. Large capital needs to consider strategy scalability and market capacity to avoid impacting the market itself. (Chan provides a table comparing choices at different capital levels, e.g., low-capital traders might lean towards joining a prop trading firm for leverage, while high-capital traders could consider an independent account).
    • Return Objectives: Different strategies have different risk-return profiles and should align with personal financial goals. Some seek stable, modest returns, while others aim for high returns and are willing to bear high volatility; strategies should be matched accordingly. After this self-assessment, the latter half of the chapter provides key points for a "preliminary strategy feasibility screen"—checking critical questions before committing to a full backtest:
    • Benchmark Comparison & Return Robustness: Does the strategy's historical performance significantly outperform a simple benchmark (like an index), and is the source of returns reasonable? Is the equity curve smooth, or is it highly dependent on a few large trades?
    • Maximum Drawdown & Duration: What is the strategy's historical maximum drawdown and its duration? Is the drawdown so deep and long that an investor couldn't tolerate it? This is an intuitive indicator of the strategy's risk level.
    • Impact of Transaction Costs: If actual commissions and slippage are considered, is the strategy's profit wiped out? High-frequency strategies, in particular, are extremely sensitive to costs.
    • Survivorship Bias in Data: Does the historical data used suffer from survivorship bias (only including surviving securities while ignoring those that were delisted)? Incomplete data leads to overly optimistic backtest results. Chan warns that free data (like from Yahoo Finance) often has this bias, while bias-free data is expensive and hard to obtain.
    • Long-Term Validity: Has the strategy's performance changed over the decades? That is, was it only effective in a specific historical period, or has it maintained its edge through changing market conditions? If a strategy has failed recently, be wary that it may have been arbitraged away.
    • Data-Snooping Bias (Data-Dredging Pitfall): Could this strategy be a product of overfitting? Chan stresses suspicion of "coincidental good performance"—if parameters were chosen after the fact to match historical data, the returns might be spurious noise. This must be validated with rigorous out-of-sample testing.
    • Institutional Attention: The aforementioned question of "flying below the institutional radar." If a strategy is already used by many large hedge funds, it will be difficult for an individual to compete. Niche strategies have a higher chance of success. Through this series of questions, the author helps readers conduct a preliminary feasibility assessment of strategy ideas before investing valuable time and effort in full development.
  • Chapter 3. Backtesting This is one of the more technical chapters, systematically explaining how to correctly conduct historical backtesting, including the tools to use, data processing, and avoiding common mistakes.

    • Tools: Chan introduces several common backtesting platforms and tools: Spreadsheets (Excel) for beginners, MATLAB for powerful scientific computing (an appendix provides a quick intro), Python/R (added in the second edition as they have become mainstream), and integrated platforms like TradeStation.
    • Data: He discusses acquiring and processing historical data, emphasizing the importance of adjusted prices (for splits and dividends) and the critical issue of survivorship bias. He notes that "a survivorship-bias-free database is usually not cheap."
    • Performance Metrics: Beyond standard metrics like Sharpe ratio, Chan emphasizes focusing on Maximum Drawdown and its recovery period, as these directly relate to a strategy's real-world tolerability.
    • Backtesting Pitfalls: This is a crucial section covering:
      • Look-Ahead Bias: Using future information in a backtest.
      • Data-Snooping Bias: Reporting only the best results from many tested strategies. Chan recommends strict out-of-sample validation to combat this.
      • Insufficient Sample Size: A small number of trades makes results statistically unreliable.
      • Overfitting: Creating a strategy with too many parameters that is "deceptively optimized" for the past. He suggests cross-validation or rolling-sample backtests to check for robustness.
      • Neglecting Transaction Costs: Ignoring commissions and slippage. Chan advises being conservative and even overestimating costs. The chapter concludes that the purpose of backtesting is not just to find "optimal" historical parameters but to validate the strategy's logic and understand its risks.
  • Chapter 4. Setting up Your Business This chapter shifts from the technical to the practical, discussing how to start and structure quantitative trading as a business.

    • Business Structure: Chan weighs the pros and cons of two paths: trading as an independent retail trader (full autonomy but limited leverage and higher costs) versus joining/forming a proprietary trading firm (higher leverage, lower costs, but profit sharing and less autonomy).
    • Broker Selection: He lists key criteria for choosing a brokerage: commission rates, available leverage (e.g., portfolio margin), market access, API quality, and reputation. Interactive Brokers is mentioned as a suitable choice for quants.
    • Infrastructure: He covers the physical setup for an independent trader: hardware (powerful computers), network connectivity (high-speed internet), data feeds, and backup/disaster recovery plans (UPS, backup internet). He also introduces the concept of co-location for latency-sensitive strategies, though he notes it's unnecessary for most independent traders. The core message is to treat quantitative trading as a serious entrepreneurial venture, planning the business architecture and infrastructure carefully.
  • Chapter 5. Execution Systems This chapter delves into the process of trade execution and building an automated system.

    • Automation Levels: Chan recommends beginners start with a semi-automated system (e.g., a program generates signals, trader executes manually) before moving to a fully automated system that connects to a broker's API to handle everything from signal generation to order placement.
    • System Design: He emphasizes building robust and fault-tolerant systems that can handle exceptions like network outages or rejected orders.
    • Minimizing Transaction Costs: An automated system can intelligently reduce costs through algorithmic order splitting or choosing between market and limit orders.
    • Paper Trading: The author strongly recommends testing the system in a live market simulation (paper trading) before risking real money. This helps identify bugs and logistical issues.
    • Performance Slippage: Chan acknowledges that live performance often falls short of backtested results due to factors like slippage, latency, and market impact. He advises traders to monitor these discrepancies and continuously refine the execution model. The key takeaway is that efficient and reliable execution is the "last mile" problem in converting a good strategy into actual profits.
  • Chapter 6. Money and Risk Management This chapter focuses on managing capital and controlling risk, which is crucial for survival and long-term profitability.

    • Optimal Capital Allocation: Chan introduces the Kelly Criterion as a theoretical guide for determining the optimal position size to maximize long-term wealth growth. However, he warns that using the full Kelly stake can be too volatile and suggests using a "half-Kelly" or "fractional Kelly" approach in practice.
    • Types of Risk: The chapter covers a comprehensive view of risk:
      • Portfolio-Level Risk: Setting risk budgets for strategies and monitoring correlations between them.
      • Leverage Risk: Using leverage cautiously and monitoring margin requirements.
      • Model Risk: The risk that the strategy's underlying assumptions are wrong or become invalid.
      • Technological and Operational Risk: Risks from software bugs, hardware failures, or power outages. He recommends having contingency plans.
      • Psychological Risk: The risk of a trader emotionally interfering with a systematic strategy. The guiding philosophy is "risk-first." Success depends not just on capturing gains but on controlling downside and surviving long enough to profit.
  • Chapter 7. Special Topics in Quantitative Trading This chapter covers a collection of advanced topics and specific strategy types.

    • Mean Reversion vs. Momentum: A detailed comparison of the two dominant strategy philosophies, emphasizing the importance of identifying the market "regime" (trending or ranging).
    • Regime Switching and Conditional Parameters: Discusses building models that adapt to changing market conditions. Example 7.1 shows using machine learning to detect market turning points and adjust strategy parameters accordingly.
    • Stationarity and Cointegration: Explains the statistical concept of cointegration for pairs trading. The GLD vs. GDX pairs trade (Example 3.6/7.2) is a classic case study used to demonstrate the entire process from testing for cointegration to backtesting the strategy. A counterexample using KO vs. PEP (Example 7.3) shows that high correlation does not guarantee cointegration.
    • Factor Models: Introduces multifactor models (like Fama-French) for explaining returns and managing risk. He shows how Principal Component Analysis (PCA) can be used to extract underlying factors (Example 7.4).
    • Exit Strategies: Discusses the importance of a well-defined exit plan, covering methods like profit targets, stop-losses, time-based exits, and trailing stops.
    • Seasonal Trading Strategies: Explores calendar effects, using the "January Effect" in small-cap stocks as a concrete, backtested example (Example 7.6).
    • High-Frequency Trading (HFT): Briefly introduces HFT concepts and strategies (market making, latency arbitrage), acknowledging that while true HFT is out of reach for most individuals, the principles can be informative.
    • High Leverage vs. High Beta: A discussion on whether it's better to leverage a low-risk portfolio or invest in a high-risk (high-beta) one without leverage, concluding that a high-Sharpe, low-volatility strategy with modest leverage is generally superior.
  • Chapter 8. Conclusion The final chapter summarizes the book's key messages and provides guidance for the reader's next steps. Chan reiterates that independent traders can succeed by following a disciplined, scientific path. He encourages readers to:

    • Continue Learning and Practicing: Read more, follow blogs, and experiment with small amounts of capital.
    • Network and Collaborate: Find partners or mentors to build a team.
    • Consider Career Paths: Use self-developed strategies as a portfolio to seek jobs in the industry.
    • Stay Current: Keep up with new technologies and market changes, such as the use of machine learning. The chapter ends on a realistic yet encouraging note, emphasizing patience and persistence as the keys to long-term success.
  • Appendices:

    • Appendix A: A brief tutorial on MATLAB for readers unfamiliar with the software.
    • Appendix B (Implicit): A mathematical derivation of the Kelly Criterion for normally distributed returns.

4. Specific Methodology

The book outlines a systematic methodology for developing and launching a quantitative trading business. This process can be summarized in the following logical steps:

  1. Strategy Ideation & Selection: Start by sourcing ideas from multiple channels (research, observation) and then perform a preliminary feasibility screen based on logic, personal fit (time, skills, capital), and institutional competition.
  2. Data Collection & Preparation: Obtain the necessary historical data, prioritizing quality (bias-free if possible). Clean, adjust (for splits/dividends), and format the data for the strategy.
  3. Backtest Modeling & Validation: Build a rigorous backtesting engine that avoids look-ahead bias and incorporates realistic costs. Validate the strategy's performance using in-sample optimization and out-of-sample testing to ensure robustness and avoid overfitting.
  4. Strategy Optimization & Confirmation: Refine the strategy based on backtest results, but avoid excessive curve-fitting. The goal is a simple, robust model. Confirm the final model and consider building a portfolio of uncorrelated strategies.
  5. Business Structure & Account Preparation: Decide on the legal and operational structure (retail vs. prop firm). Set up the necessary brokerage accounts, secure funding, and ensure all API connections are working.
  6. Execution System Development: Build or configure an automated or semi-automated trading system to translate signals into live orders. Test this system thoroughly in a simulated environment first.
  7. Live Trading & Monitoring: Deploy the strategy with real capital. Continuously monitor its performance against expectations and historical backtests. Maintain strict discipline and adhere to risk management rules.
  8. Strategy Iteration & New Development: Use live feedback to make informed adjustments to the existing strategy. Simultaneously, continue the research and development cycle to build new, uncorrelated strategies to grow the business.

Two principles underpin this methodology:

  • Combining Quantitative and Qualitative Analysis: While data-driven, Chan advises using common sense and economic intuition to vet ideas and manage risks.
  • Prioritizing Simplicity: Following Einstein's maxim, "Make things as simple as possible, but not simpler," he advocates for simple, understandable, and maintainable strategies over complex "black boxes."

5. Practical Application Cases

The book is rich with practical examples to illustrate its concepts. Key cases include:

Case StudyChapter(s)Key Concept IllustratedDetails
GLD vs. GDX Pairs Trade3, 5, 7Cointegration, Mean Reversion, BacktestingA detailed walkthrough of testing for cointegration, optimizing parameters on a training set, validating on a test set, and calculating the mean-reversion half-life.
KO vs. PEP Cointegration Test7Cointegration vs. CorrelationDemonstrates that two highly correlated stocks in the same industry are not necessarily cointegrated, warning against making assumptions without statistical proof.
Post-Earnings Drift (PEAD)7Momentum StrategyCites research on the PEAD phenomenon as a classic example of a momentum strategy driven by the slow diffusion of fundamental information.
January Effect7Seasonal StrategyProvides a backtest (with MATLAB code) of a strategy that buys small-cap stocks in January, showing how a market anomaly can be turned into a rule-based strategy.
Machine Learning for Regimes7Regime Switching, Advanced MethodsIntroduces the idea of using ML models to predict shifts in market behavior (e.g., from trending to ranging) to adapt strategy parameters dynamically.
Kelly Criterion Application6Money Management, Position SizingProvides a clear, formula-based method for determining optimal bet size to maximize long-term growth while managing risk, with practical advice to use a fractional approach.
Tool & Data UsageVariousPractical SkillsIncludes code snippets for tasks like scraping historical data from Yahoo Finance with MATLAB, demonstrating how to acquire and process data for analysis.

These concrete examples serve as templates, enabling readers to move from theory to practice and apply the book's methods to their own ideas.

6. Author's Background Information

Understanding the author, Dr. Ernest P. Chan, is key to appreciating the book's value.

  • Education and Wall Street Experience: Dr. Chan holds a Ph.D. in theoretical physics from Cornell University. His strong quantitative background led him to a career on Wall Street, where he worked as a quantitative analyst and developer at institutions like IBM Research, Morgan Stanley, Credit Suisse, and the hedge fund Millennium Partners. This experience gave him hands-on expertise in statistical arbitrage, high-frequency trading, and data mining.

  • Entrepreneurship and Consulting: After leaving Wall Street, Chan founded his own quantitative investment management firm, QTS Capital Management, LLC, where he traded systematic strategies for private clients. He later founded PredictNow.ai, a financial machine learning software and consulting company. His entrepreneurial and consulting work has kept him at the cutting edge of practical quantitative finance.

  • Author and Educator: Dr. Chan is a prolific author known for his practical and accessible writing style. His other popular books include Algorithmic Trading: Winning Strategies and Their Rationale (2013) and Machine Trading: Deploying Computer Algorithms to Conquer the Markets (2017), and most recently, Generative AI for Trading and Asset Management (2023). His willingness to share code, data, and hard-won lessons has earned him a stellar reputation in the quant community.

  • Community Influence: Since 2006, Dr. Chan has maintained a popular blog (epchan.blogspot.com), sharing insights and strategy ideas. He is also an active educator, teaching courses for institutions like QuantInsti and Nanyang Technological University in Singapore.

In summary, Dr. Chan is a respected practitioner-scholar who has successfully bridged the gap between institutional quantitative finance and the independent trading community. His work has been instrumental in demystifying the field and empowering individuals. As one reader, Corey Hoffstein, put it, "Ernie's book is the ideal guide for those aspiring to make the journey from 0 to 1 in quantitative trading." The authority of the book stems not only from its content but from the author's deep and credible experience in both theory and practice.


References:

  • Chan, Ernest P. Quantitative Trading: How to Build Your Own Algorithmic Trading Business. Wiley, 1st Ed. 2009 & 2nd Ed. 2021. (Table of Contents and excerpts).
  • Chan, Ernest P. – Preface to the Second Edition and cover copy (2021); Praise for the book.
  • SoBrief Book Summary – Quantitative Trading Key Takeaways.
  • QuantInsti Faculty Bio – Dr. Ernest P. Chan (education, career, books).
  • Akademika Book Detail – Product info and author bio.
  • Investarr PDF Excerpts – Example 3.6 (GLD-GDX pair trade); Example 7.1 (Regime switching ML); Example 7.3 (KO-PEP cointegration test); Example 7.6 (January effect code); Momentum vs Mean-reversion discussion; Data and Yahoo Finance references.