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Comparisons

Proactive Market Making (PMM) vs Automated Market Making (AMM)

A technical analysis comparing oracle-guided liquidity provisioning (PMM) with algorithmic, on-chain price discovery (AMM). We evaluate core mechanisms, capital efficiency, price stability, and ideal use cases for CTOs and protocol architects.
Chainscore © 2026
introduction
THE ANALYSIS

Introduction: The Core Architectural Divide in DEX Liquidity

Understanding the fundamental choice between proactive price-setting and passive liquidity pools is critical for protocol design.

Automated Market Making (AMM) excels at permissionless, continuous liquidity for long-tail assets by relying on liquidity provider (LP) deposits and a deterministic pricing curve (e.g., Uniswap V3's concentrated liquidity, Curve's stablecoin invariant). This model democratizes market creation, as evidenced by the $50B+ in Total Value Locked (TVL) across leading AMMs. However, capital efficiency is constrained by the spread between the curve price and the global market price, leading to impermanent loss for LPs during volatility.

Proactive Market Making (PMM) takes a different approach by algorithmically adjusting a centralized price curve in real-time to mirror external market data (e.g., from Chainlink oracles). Pioneered by DEXs like dYdX and Perpetual Protocol, this strategy results in superior capital efficiency and tighter spreads for major trading pairs. The trade-off is a reliance on oracles and active management, making it less suitable for assets without reliable external price feeds.

The key trade-off: If your priority is maximizing capital efficiency and minimizing slippage for established, oracle-feedable assets (e.g., ETH, major stablecoins), choose a PMM design. If you prioritize permissionless listing, censorship resistance, and deep liquidity for any ERC-20 token, an AMM architecture is the proven, decentralized choice.

tldr-summary
Proactive Market Making (PMM) vs Automated Market Making (AMM)

TL;DR: Key Differentiators at a Glance

A data-driven comparison of the two dominant liquidity models. Choose based on your protocol's need for capital efficiency versus permissionless composability.

01

PMM: Superior Capital Efficiency

Targeted Liquidity: Uses an oracle price anchor to concentrate liquidity around the fair price, reducing idle capital. This matters for perpetual DEXs (e.g., dYdX v3) and stablecoin swaps (Curve) where slippage must be minimized. Can achieve 10-100x higher capital efficiency than a standard AMM for the same depth.

02

PMM: Predictable, Low Slippage

Oracle-Guided Pricing: Price discovery is external (e.g., Chainlink, Pyth), leading to stable, low-slippage trades near the oracle price. This matters for institutional trading and high-frequency strategies where execution price certainty is critical. Trade execution is more akin to a CLOB but on-chain.

03

PMM: Centralized Risk & Complexity

Oracle Dependency: System integrity relies entirely on the security and liveness of the price oracle. A failure or manipulation (e.g., flash loan attack on oracle) can drain the pool. This matters for protocol architects who must audit and trust external data providers, adding a systemic risk layer.

04

AMM: Permissionless & Composable

Universal Pool Creation: Anyone can create a market for any asset pair without permission. This matters for long-tail assets and experimental DeFi primitives (e.g., Uniswap v3, Balancer). It's the foundation for money legos—liquidity is automatically usable by aggregators (1inch), lenders (Aave), and other dApps.

05

AMM: Pure On-Chain Price Discovery

Bonding Curve Pricing: Price is determined solely by the pool's reserve ratio, making it censorship-resistant and self-contained. This matters for truly decentralized exchanges and novel assets with no oracle feed. However, it leads to higher slippage and vulnerability to front-running on volatile assets.

06

AMM: Capital Inefficiency & Impermanent Loss

Slippage & Dilution: Liquidity is spread across all prices (or wide ranges in v3), requiring more capital for deep liquidity. Impermanent Loss is a fundamental risk for LPs when assets diverge. This matters for LPs and protocols where maximizing yield on deposited capital is a primary concern, often requiring complex hedging strategies.

LIQUIDITY PROVISION ARCHITECTURE

Head-to-Head Feature Comparison: PMM vs AMM

Direct comparison of liquidity mechanisms, capital efficiency, and typical use cases.

Metric / FeatureProactive Market Maker (PMM)Automated Market Maker (AMM)

Core Pricing Mechanism

Oracle-based reference price + depth curve

Constant function (e.g., x*y=k)

Capital Efficiency (for stable pairs)

~1000x higher than AMM

1x (Baseline)

Typical Price Impact (for $1M swap)

0.01% - 0.05%

0.3% - 2.0%

Impermanent Loss Risk

Significantly lower

Inherent and high

Primary Use Case

Spot DEXs (e.g., DODO), Perpetuals

Generalized DeFi (e.g., Uniswap, Curve)

Oracle Dependency

Required (Chainlink, Pyth)

Not required

Liquidity Concentration

Active around reference price

Passive across entire range

pros-cons-a
PMM vs AMM: Key Differentiators

Pros and Cons of Proactive Market Making (PMM)

A data-driven comparison of DEX liquidity mechanisms. PMM, pioneered by DODO and used by Perpetual Protocol, uses oracles and capital efficiency models, while AMMs like Uniswap V3 and Curve rely on constant function formulas.

04

AMM: Unmatched Composability & Network Effects

Ecosystem standard: The AMM is the default liquidity primitive, integrated into thousands of DeFi protocols (e.g., lending, options, yield aggregators). Tools like The Graph for analytics and Gelato for automation are built for AMMs. This matters for developers who need seamless integration with the broader DeFi stack and existing user bases.

4,000+
Integrations (Uniswap)
pros-cons-b
KEY TRADEOFFS

Proactive Market Making (PMM) vs Automated Market Making (AMM)

A data-driven comparison of capital efficiency and market structure for protocol architects and CTOs.

01

PMM: Superior Capital Efficiency

Targeted Liquidity: Uses price oracles (e.g., Chainlink, Pyth) to concentrate liquidity around a reference price, reducing required capital by 10-100x for the same slippage profile compared to constant-product AMMs. This matters for new token launches and stablecoin pairs where price stability is paramount.

10-100x
Capital Efficiency
02

PMM: Reduced Impermanent Loss

Oracle-Guided Pricing: By pegging to an external price feed, liquidity providers (LPs) experience significantly lower divergence loss when the asset price moves predictably. This matters for attracting large, institutional LPs to provide deep liquidity for blue-chip assets.

~0.02%
IL for Stable Pairs
04

AMM: Battle-Tested Security & Composability

Proven Audits & Integration: Protocols like Uniswap V3 and Curve have secured $10B+ in TVL and are integrated into thousands of dApps (e.g., lending, derivatives). This matters for protocols where security and existing developer tooling (SDKs, subgraphs) are non-negotiable.

$10B+
Collective TVL
CHOOSE YOUR PRIORITY

Decision Framework: When to Choose PMM vs AMM

PMM for Capital Efficiency

Verdict: Superior for Concentrated Liquidity & Stable Assets. PMM protocols like DODO and Curve Finance (StableSwap) use price oracles to concentrate liquidity around a target price, drastically reducing slippage for high-volume trades. This is ideal for stablecoin pairs (USDC/USDT) or pegged assets (wBTC/BTC). TVL is deployed more effectively, offering deeper liquidity with less capital locked.

AMM for Capital Efficiency

Verdict: Simpler but Requires Over-Collateralization. Traditional AMMs like Uniswap V2 spread liquidity across an infinite price range, leading to significant idle capital. While Uniswap V3 introduced concentrated liquidity positions, it shifts the management burden to LPs. For volatile, long-tail assets without reliable oracles, the AMM model's simplicity can be a necessary trade-off against efficiency.

verdict
THE ANALYSIS

Final Verdict and Strategic Recommendation

Choosing between PMM and AMM is a strategic decision based on your protocol's specific liquidity needs and target market.

Proactive Market Making (PMM) excels at providing deep, stable liquidity for predictable, high-volume assets because it uses oracles to concentrate capital around a fair price. For example, DODO's vDODO pools and Curve's stableswap invariant achieve near-zero slippage for stablecoin pairs, with Curve's pools often handling billions in TVL. This model is highly capital-efficient, minimizing impermanent loss for LPs and offering a superior user experience for large trades in well-defined markets.

Automated Market Making (AMM) takes a different approach by relying on a constant function formula (e.g., x*y=k) and passive, permissionless liquidity provision. This results in a trade-off of broader asset support and censorship resistance at the cost of capital efficiency. Protocols like Uniswap V3 introduced concentrated liquidity to mitigate this, but the core model remains best for long-tail assets and bootstrapping new markets where price discovery is needed, as seen with the explosive growth of memecoins on decentralized exchanges.

The key trade-off: If your priority is capital efficiency and low slippage for established, correlated assets (e.g., stablecoins, wrapped assets, liquid staking tokens), choose a PMM design like those from DODO or Curve. If you prioritize permissionless listing, maximal decentralization, and support for speculative or nascent assets, a generalized AMM like Uniswap or PancakeSwap is the proven foundation. For protocols with predictable order flow, PMM offers a tailored solution; for open-ended ecosystems, the flexibility of an AMM is indispensable.

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PMM vs AMM: Oracle-Driven vs Algorithmic Liquidity | DEX Comparison | ChainScore Comparisons