Background and Opportunity

The Evolution from Central Limit Order Books to AMMs: The blockchain trilemma, a challenge of balancing decentralization, security, and scalability, made the implementation of traditional Central Limit Order Books (CLOBs) on-chain impractical. This led to the emergence of Automated Market Makers (AMMs) as a decentralized trading solution. Over time, AMMs have progressed through multiple generations, each attempting to refine the inefficiencies of its predecessors through various innovations. However, these models are not without their drawbacks:

Rebalancing Induced Losses:

• Loss Versus Rebalancing (LVR): Liquidity Providers (LPs) experience losses amounting to 5-7% of their liquidity due to selling assets at suboptimal prices, summing up to over $500 million lost annually across various CFMMs.

• Loss Versus Holding: Commonly known as Impermanent Loss, this occurs when the price of deposited assets changes compared to when they were deposited, presenting a significant opportunity cost for LPs.

High Operational Costs:

• Liquidity Management: LPs face ongoing costs for adjusting capital within specific price ranges, often necessitating automated tools which introduces additional expenses.

• Slippage: Large trades can shift prices unfavorably due to the artificial volatility, increasing costs for subsequent traders.

• Trade Execution: Miners or validators might reorder transactions for profit, known as Maximal Extractable Value (MEV), forcing users to pay higher gas fees to secure timely execution.

• MEV Impact: MEV activities often manipulate trade execution prices, leading to suboptimal transaction outcomes. Users face additional capital losses between 2-5% due to these manipulations, cumulatively costing over $1.5 billion annually.

• On-chain Navigation: Moving through multiple liquidity pools incurs substantial gas fees, with each additional hop increasing the cost burden.

Low Earning Potential:

• Idle Liquidity: Up to 70% of liquidity can remain unused in concentrated models, reducing potential fee earnings from active trading.

• Fee Dynamics: Strategies like Just in Time (JIT) liquidity and Request For Quote (RFQ) systems can bypass on-chain liquidity, potentially reducing LP earnings by up to 40% in scenarios of high RFQ adoption.

Centralization Risks:

• Block Building Dominance: High-frequency trading (HFT) entities centralize block creation, impacting blockchain efficiency and fairness through mechanisms like Proposer-Builder Separation (PBS) auctions.

• Liquidity Concentration: Recent trends show a single market maker handling the majority of off-chain trades, potentially skewing market dynamics and hindering smaller liquidity providers.

• Governance and Economic Implications: The governance in AMMs can lean towards plutocracy, where voting power correlates with wealth, possibly leading to decisions that favor large stakeholders over the broader community.

Misaligned Incentives:

• Just-In-Time (JIT) liquidity providers and RFQ-based solvers: exploit the system by engaging primarily in low-risk, lucrative trades, quickly moving in and out to capture non-toxic order flows without long-term liquidity commitment. Conversely, dedicated long-term LPs face higher risks with toxic flows, as off-chain RFQ trades siphon away the safer transactions, decreasing the AMM's trade volume and diluting potential fee earnings for those who maintain consistent liquidity.

The Opportunity for Innovation:

Current AMMs present significant challenges, particularly for retail LPs, who are exposed to higher risks and lower rewards due to a design that favors whales and institutional participants. This imbalance underscores the urgent need for innovative solutions that offer fairer opportunities, optimize capital efficiency, and reduce risk. Dextr addresses this with a radical new design for automated market making, creating a more balanced ecosystem that levels the playing field for all participants.