Cross-Rollup Arbitrage Dynamics

Updated 20 October 2025

Cross-rollup arbitrage is the practice of exploiting pricing discrepancies and liquidity fragmentation across distinct Layer-2 rollups.
Empirical analyses reveal misalignments persisting from seconds to minutes, with arbitrage opportunities yielding 0.03–0.25% of trading volume.
Innovations like CRATE and shared sequencers enhance atomic execution, mitigating risks such as non-atomicity and bridging delays.

Cross-rollup arbitrage describes the set of trading activities and mechanism designs intended to exploit, detect, or eliminate profit opportunities that arise from price, liquidity, or structural inconsistencies between distinct rollup-based Layer-2 (L2) blockchains in the decentralized finance (DeFi) ecosystem. This phenomenon is a direct consequence of the fragmentation of liquidity and state introduced by L2 scalability solutions, which, while improving throughput and reducing transaction costs, introduce new sources of inefficiency and inter-market risk. As L2 adoption expands, cross-rollup arbitrage has emerged as a focal topic in areas including market microstructure, mechanism design, multi-agent optimization, and protocol engineering.

1. Nature and Microstructure of Cross-Rollup Arbitrage

Cross-rollup arbitrage emerges when the same or economically equivalent assets are priced differently across rollups, typically due to asynchronicity of state updates, operational latency, variations in liquidity, fee structures, or block production times. These price discrepancies can be transient, reflecting the time required for information, price impact, and liquidity to propagate between rollups, or persistent, arising from architectural fragmentations such as distinct sequencing, consensus, or bridge models.

Arbitrage is categorized as “non-atomic” when transactions on different rollups cannot be executed as a single all-or-nothing operation, thus exposing the arbitrageur to price drift (state change risk). The typical arbitrage cycle involves identifying a price misalignment, executing a buy on the cheaper rollup (or DEX/CEX), transferring or bridging the asset, and executing a sell on the more expensive venue. High-frequency actors may operate simultaneously across multiple rollups, but execution risks and infrastructural asynchronies define the risk–reward frontier.

Empirical analyses on tokens such as WETH–USDC reveal that, between major rollups (e.g., Arbitrum, Base, Optimism, zkSync), thousands of arbitrage opportunities emerge per day, with typical misalignments persisting for 10–20 blocks—much longer than on Ethereum mainnet where arbitrage is atomic and opportunities usually decay within one block (Gogol et al., 4 Jun 2024). On Arbitrum, average misalignment duration is 7–9 seconds due to 0.25s block times, whereas Base sees longer decay (~420s) due to operational and liquidity factors. The Maximal Arbitrage Value (MAV), a precise per-opportunity profit measure, typically ranges from 0.03–0.05% of trading volume on mature rollups, but can reach 0.25% on newer venues with lower liquidity (Gogol et al., 4 Jun 2024, Gogol et al., 24 Mar 2024).

2. Quantification and Detection: Models and Metrics

Arbitrage profitability assessment is founded on rigorous profit–cost models that reflect the realities of fragmented liquidity and non-atomic execution:

$P(s_m, s_n) = \pi(\alpha^{\mathrm{o}}_{s_m}) - \pi(\alpha^{\mathrm{i}}_{s_n}) - \rho(s_m, s_n)$

where $\pi(\alpha^{\mathrm{o}}_{s_m})$ is the output on one rollup, $\pi(\alpha^{\mathrm{i}}_{s_n})$ the input on another (hedge leg), and $\rho(s_m, s_n)$ aggregates network, execution, and bridging fees (Öz et al., 28 Jan 2025). The MAV metric, derived from AMM invariants, yields the optimal trade volume and maximal profit for a given mispricing and available liquidity:

$\text{MAV} = V_{max} \cdot (P_a - P_c) - V_{max} \cdot P_a \cdot \rho(V_{max})$

$V_{max} = \frac{y (P_a - P_c)}{2 P_a}$

$\text{MAV} = \frac{y (P_a - P_c)^2}{4 P_a}$

where $P_a$ and $P_c$ are the prices on the AMM and the CEX (or alternative rollup), $y$ the AMM reserve, and $\rho$ the percentage price impact (Gogol et al., 24 Mar 2024, Gogol et al., 4 Jun 2024).

Analyses must address non-atomicity and opportunity duration. The Loss Versus Rebalancing (LVR) metric is adapted to record only the maximum MAV per period of continuous misalignment, suppressing double-counting due to slow decay (Gogol et al., 4 Jun 2024).

3. Mechanisms, Execution Strategies, and Protocol Design

Execution strategies for cross-rollup arbitrage may be broadly categorized:

Inventory-based Arbitrage (SIA): The arbitrageur pre-positions capital on both rollups, enabling out-of-sequence execution and minimizing latency but incurring inventory risk (Öz et al., 28 Jan 2025).
Bridge-based Arbitrage (SDA): The arbitrageur executes on one rollup, bridges assets to the destination rollup, and completes the trade. This strategy is sensitive to bridge latency (e.g., median 246s vs. 9s for SIA) and bridging costs, and is thus generally less profitable and riskier than SIA (Öz et al., 28 Jan 2025).

The development of cross-rollup atomicity protocols (e.g., $\mathsf{CRATE}$ ) introduces a new paradigm. CRATE enables composite cross-rollup transactions (CRTs) that are either fully executed on all rollups or not at all, preserving serializability. Key mechanisms include an off-chain Executor with an extended EVM (XEVM), General System Contracts (GSCs) for trigger-action synchronization, and a two-phase commit protocol among Layer-1-based Validator smart contracts (VSMs) to ensure all-or-nothing state changes even across heterogeneous L1s (Kaklamanis et al., 7 Feb 2025). CRATE supports both chain and DAG models for action sequencing and has been demonstrated to enable cross-rollup flash loans and atomic arbitrage cycles with only moderate increases in L1 gas usage.

4. Risks, Competition, and Market Structure

Cross-rollup arbitrage is characterized by considerable execution and infrastructure risk:

Non-Atomicity Risk: In the absence of atomic protocols, separate execution of arbitrage legs exposes traders to price drift, reversion, or block reordering—especially as L2 rollups have distinct sequencing and finality guarantees (Gogol et al., 4 Jun 2024).
Centralization: Empirical studies reveal pronounced concentration, with a handful of addresses executing the majority of volume. For example, one address was responsible for nearly 40% of daily cross-chain arbitrage volume after March 2024 (Öz et al., 28 Jan 2025). This vertical integration is driven by the capital-intensive nature of inventory-based strategies, preferential access to sequencing channels, and high costs associated with failed or censored transactions.
Sequencer and Liveness Risk: Disparities in sequencer design, ordering policies, and private vs. public mempools (notably, rollups lack public mempools) create asymmetries in information access and transaction settlement, exacerbating censorship and liveness issues (Torres et al., 30 Apr 2024, Öz et al., 28 Jan 2025).
Finality and Bridging Delays: Optimistic rollups’ fraud-proof periods can delay asset transfer and trade finality for days, whereas zero-knowledge rollups provide rapid finality but potentially at greater implementation complexity and verification cost (Gorzny et al., 24 Apr 2024).

5. Comparison with Classical Models and Theoretical Insights

The analogy between cross-rollup arbitrage and multi-asset market impact/cross-impact in classical finance is established through the lens of the “no-dynamic-arbitrage” and market impact framework (Schneider et al., 2016). For arbitrage-freeness, cross-impact functions (how trading on rollup $j$ affects prices on rollup $i$ ) must be odd and linear, with symmetric coefficients: $f^{ij}(v) = \eta^{ij} v$ , $f^{ij}(v) = -f^{ij}(-v)$ , $\eta^{ij} = \eta^{ji}$ . If rollup interconnections violate these principles, arbitrage may exist, although empirical evidence suggests that transaction costs render such asymmetries largely unexploitable.

Additionally, from the multi-asset derivative literature, it is possible for each rollup or asset to be individually arbitrage-free within its own price interval, yet for joint pricing across subsystems to admit arbitrage due to inconsistent dependence (copulas) between assets/rollups (Papapantoleon et al., 2020). This offers a rigorous probabilistic basis for decomposing and detecting cross-rollup price inconsistencies.

6. Technological and Infrastructural Innovation

Protocol-level innovations seek to minimize the risk and cost of cross-rollup arbitrage and to potentially close structural inefficiencies:

Atomic Transaction Protocols (e.g., CRATE): Guaranteeing serializable, all-or-nothing transaction execution across rollups (Kaklamanis et al., 7 Feb 2025).
Shared Sequencer Networks: Propositioned to enhance composability and MEV extraction. However, atomicity alone does not always guarantee increased arbitrage profitability and may sometimes lead to lower overall revenues depending on liquidity and competition structures (Silva et al., 15 Oct 2024).
Bridging and Synchronization: Direct and fast bridges can lower the latency and cost penalty of cross-rollup arbitrage cycles (Öz et al., 28 Jan 2025).
Mitigation of Cross-layer Information Leakage: Private/encrypted mempools and tighter L1-L2 coordination can prevent front-running or sandwich attacks that exploit visibility into pending cross-rollup trades (Torres et al., 30 Apr 2024).

7. Practical Implications and Future Research Directions

Successful cross-rollup arbitrage requires:

Automated, latency-optimized monitoring and execution across heterogeneous L2s;
Sophisticated fee and revert risk modeling, given the higher incidence of failed transactions in non-atomic environments (Gogol et al., 4 Jun 2024, Öz et al., 28 Jan 2025);
Strategic inventory management to balance capital effectiveness and risk;
Careful choice of bridging routes and, where available, use of atomic protocols to mitigate execution risk.

Open research challenges include the robust decentralization of sequencing infrastructure, reducing cross-domain censorship vectors, and the design of market structures in which composability does not amplify centralization or exacerbate MEV extraction at the expense of liveness and market integrity (Öz et al., 28 Jan 2025, Torres et al., 30 Apr 2024, Silva et al., 15 Oct 2024). The interplay between technology, economics, and mechanism design—especially regarding the synchronization and composability of state across rollups—continues to define the evolution and efficacy of cross-rollup arbitrage.

Table: Selected Cross-Rollup Arbitrage Metrics

Rollup	MAV (% of Volume)	Typical Opportunity Duration (s)
Arbitrum	0.03–0.05%	7–9
Base	0.03–0.05%	up to 420
Optimism	0.03–0.05%	~19
zkSync Era	~0.25%	varies (higher volatility)

In summary, cross-rollup arbitrage leverages temporal, structural, and liquidity-induced discrepancies across L2 ecosystems. Its realization is determined by microstructure-driven opportunities, the limits of current atomicity and bridging technologies, and the dynamics of competition and infrastructure. Ongoing protocol innovations—atomic execution, shared sequencers, robust cross-domain bridges—define the present and future research agenda. Theoretical foundations from financial and probabilistic modeling frame both the detection and constraint of arbitrage, ensuring that cross-rollup markets evolve toward efficiency while navigating new risks unique to decentralized, multi-chain finance.