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20 defi & on-chain arbitrage strategies for crypto, from the AlgoBrain wiki. Price gaps that live on-chain: DEX triangles, flash loans, cross-chain and L2 spreads, LST and stablecoin depegs, yield-token mispricing. Each one lists the indicators it uses, the Crypto Data API endpoints that feed it and copy-paste prompts for an AI agent to build and backtest it. All of them are in the API: GET /api/v1/strategies?group=defi-arbitrage.
Trading the fungible-token markets on Bitcoin introduced by two competing standards:
Why it works: Bitcoin Runes (April 2024) and BRC-20 (March 2023) introduced fungible tokens to Bitcoin via two competing standards. Cross-marketplace arbitrage (UniSat, OKX, Magic Eden, Ordinals Wallet, Best in Slot) and cross-standard triangulation (Runes vs BRC-20 vs wrapped-on-Ethereum versions) opened a new fragmented market analogous to early Ethereum DEX arb.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Via API/api/v1/strategies/bitcoin-runes-brc20-arbitrage
AI-agent prompts
Build it with an AI agent
Build the Bitcoin Runes / BRC-20 Arbitrage crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/arbitrage/bitcoin-runes-brc20-arbitrage.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/dex/trending
- GET https://cryptodataapi.com/api/v1/dex/new-pools
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
- GET https://cryptodataapi.com/api/v1/market-data/klines
3. Compute the signals described in the playbook on 5m bars (pinned: interval=5m, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the Bitcoin Runes / BRC-20 Arbitrage strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=15m (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/arbitrage/bitcoin-runes-brc20-arbitrage.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
Cross-chain arbitrage exploits price discrepancies for the same token across different blockchain networks -- buying on the chain where the price is lower and selling (or bridging and selling) on the chain where the price is higher.
Why it works: Price fragmentation across independent blockchain ecosystems creates persistent mispricings; bridge latency and risk premiums prevent instant convergence, leaving profit for those willing to bear bridging risk and maintain multi-chain infrastructure.
Build the Cross-Chain Arbitrage crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/arbitrage/cross-chain-arbitrage.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/dex/trending
- GET https://cryptodataapi.com/api/v1/dex/new-pools
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
- GET https://cryptodataapi.com/api/v1/market-data/klines
3. Compute Volatility on 5m bars (pinned: interval=5m, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the Cross-Chain Arbitrage strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=15m (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/arbitrage/cross-chain-arbitrage.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
Arbitrage exploiting price divergence of the same asset across Ethereum Layer-2 rollups (Arbitrum, Optimism, Base, zkSync Era, Polygon zkEVM, Linea, Scroll, Mantle, Blast).
Why it works: Each L2 (Arbitrum, Optimism, Base, zkSync, Polygon zkEVM, Linea, Scroll) has its own sequencer producing blocks at different cadences (~250ms-2s) with different liquidity. Same asset trades at different prices across L2s for seconds-to-minutes; arbs close the gap via fast bridges (Across, Hop, Stargate) or shared inventory.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Build the Cross-L2 Arbitrage crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/arbitrage/cross-l2-arbitrage.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/hyperliquid/l2-book
- GET https://cryptodataapi.com/api/v1/liquidity/depth
- GET https://cryptodataapi.com/api/v1/dex/trending
- GET https://cryptodataapi.com/api/v1/dex/new-pools
- GET https://cryptodataapi.com/api/v1/sentiment/macro
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Compute the signals described in the playbook on 5m bars (pinned: interval=5m, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the Cross-L2 Arbitrage strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=15m (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/arbitrage/cross-l2-arbitrage.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
The "Curve Wars" trade is a structural arbitrage on the bribe (vote-incentive) market built on top of Curve Finance's vote-escrow governance system. Holders of veCRV (vote-escrowed CRV, locked up to 4 years) direct CRV emissions to specific Curve pools via gauge weight votes.
Why it works: veCRV/vlCVX holders direct CRV emissions to Curve pools; protocols needing liquidity pay bribes that exceed organic governance value, creating a yield arb between bribe income and lock cost.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Via API/api/v1/strategies/curve-gauge-wars-arbitrage
AI-agent prompts
Build it with an AI agent
Build the Curve Gauge Wars Arbitrage crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/arbitrage/curve-gauge-wars-arbitrage.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/dex/trending
- GET https://cryptodataapi.com/api/v1/dex/new-pools
- GET https://cryptodataapi.com/api/v1/supply/float
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Compute the signals described in the playbook on 1d bars (pinned: interval=1d, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the Curve Gauge Wars Arbitrage strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=1d (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/arbitrage/curve-gauge-wars-arbitrage.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
Atomic on-chain triangular arbitrage executed across Automated Market Maker (AMM) pools — typically Uniswap v2/v3, Curve, Balancer, SushiSwap. A searcher detects a 3+-pool cycle whose implied product exceeds 1, executes the entire trade in one transaction (often via flash loan), and pockets the difference net of gas.
Why it works: AMM constant-product pools (Uniswap, Curve, Balancer) reprice at different speeds across pools. After a large external trade or oracle update, cross-pool implied rates form an exploitable cycle that closes only when an arbitrageur or the next price-update transaction lands.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Via API/api/v1/strategies/dex-pool-triangular-arbitrage
AI-agent prompts
Build it with an AI agent
Build the DEX Pool Triangular Arbitrage crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/arbitrage/dex-pool-triangular-arbitrage.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/dex/trending
- GET https://cryptodataapi.com/api/v1/dex/new-pools
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
- GET https://cryptodataapi.com/api/v1/market-data/klines
3. Compute the signals described in the playbook on 5m bars (pinned: interval=5m, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the DEX Pool Triangular Arbitrage strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=15m (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/arbitrage/dex-pool-triangular-arbitrage.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
A sector basket of decentralised exchange protocol tokens with active Hyperliquid perpetuals. DEX tokens (governance tokens of AMMs, perp DEXs, and aggregators) are directly linked to on-chain trading volume — a structurally trackable metric — making this basket more fundamental than pure narrative plays.
Why it works: DEX tokens are directly tied to trading volume and fee revenue, which creates a structural relationship between on-chain activity cycles and token prices; within-sector dispersion tracks volume-share shifts between DEX protocols (AMM innovations, liquidity-mining changes, new chain launches), enabling cross-sectional harvest as market-share battles play out.
Build the DEX Tokens Basket (Hyperliquid Basket) crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/hyperliquid-baskets/dex-tokens-basket.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/derivatives/funding-rates
- GET https://cryptodataapi.com/api/v1/hyperliquid/funding-rates
- GET https://cryptodataapi.com/api/v1/derivatives/open-interest
- GET https://cryptodataapi.com/api/v1/hyperliquid/open-interest
- GET https://cryptodataapi.com/api/v1/market-health/altcoin-breadth
- GET https://cryptodataapi.com/api/v1/coins/top
3. Compute Open Interest on 4h bars (pinned: interval=4h, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the DEX Tokens Basket (Hyperliquid Basket) strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=4h (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/hyperliquid-baskets/dex-tokens-basket.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
Flash loan arbitrage is a DeFi-native, fully atomic strategy: a searcher borrows uncollateralised capital from a flash-loan provider (Aave at 0.09%, Balancer/Morpho at ~0%, Uniswap flash swaps), uses it to close a price gap across decentralized exchanges within a single blockchain transaction, repays the loan plus fee, and keeps the remainder — all in one block.
Why it works: AMM pools re-price only when someone trades against them, so a swap on one pool leaves correlated pools stale for the rest of the block. A searcher borrows uncollateralised capital via a flash loan, closes the gap across pools atomically, and repays in the same transaction. The counterparty is the liquidity provider / trader whose swap moved one pool but not the others — and, increasingly, the blo
IndicatorsPrice and volume only — see the playbook for the exact rules.
Build the Flash Loan Arbitrage crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/arbitrage/flash-loan-arbitrage.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/dex/trending
- GET https://cryptodataapi.com/api/v1/dex/new-pools
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Compute the signals described in the playbook on 5m bars (pinned: interval=5m, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the Flash Loan Arbitrage strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=15m (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/arbitrage/flash-loan-arbitrage.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
The arbitrageur counterpart to intent based trading. Rather than executing arb on the public mempool and competing for blockspace, solvers in intent systems (CoW Protocol, UniswapX, 1inch Fusion, Bebop) compete to fill user-signed orders.
Why it works: Intent batches contain Coincidence-of-Wants matches, multi-hop routing optimizations, and arb cycles that solvers extract by winning the auction. Surplus = (best_path_output - user_min_output) shared between solver and user.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Build the Intent-Based Arbitrage (Solver-Side) crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/arbitrage/intent-based-arbitrage.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/dex/trending
- GET https://cryptodataapi.com/api/v1/dex/new-pools
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Compute the signals described in the playbook on 5m bars (pinned: interval=5m, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the Intent-Based Arbitrage (Solver-Side) strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=15m (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/arbitrage/intent-based-arbitrage.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
Intent-based trading, as a buildable strategy, means operating on the solver / filler side of an intent protocol — CoW Protocol (batch auctions), UniswapX (Dutch-auction fills), or 1inch Fusion (resolvers).
Why it works: As a solver/filler you win a batch auction by returning more output than the user's limit and more than rival solvers, then capture the residual — CoW ring-matching surplus, cross-venue routing improvement, and your own inventory spread — minus gas and settlement risk; the user on the other side is paying for guaranteed MEV-protected execution and is happy to leave that residual on the table.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Build the Intent-Based Trading crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/algorithmic/intent-based-trading.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/hyperliquid/l2-book
- GET https://cryptodataapi.com/api/v1/liquidity/depth
- GET https://cryptodataapi.com/api/v1/dex/trending
- GET https://cryptodataapi.com/api/v1/dex/new-pools
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Compute the signals described in the playbook on 15m bars (pinned: interval=15m, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the Intent-Based Trading strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=15m (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/algorithmic/intent-based-trading.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
Liquid Staking Token (LST) depeg arbitrage captures the spread between a liquid staking derivative (stETH, rETH, cbETH) and underlying ETH when forced selling temporarily pushes the LST below its 1:1 redemption value.
Why it works: Liquid staking tokens are claims on staked ETH redeemable through a withdrawal queue, not at-will. Forced selling during liquidity crises temporarily breaks the peg below intrinsic value.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Build the LST Depeg Arbitrage (stETH / rETH / cbETH) crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/arbitrage/lst-depeg-arbitrage.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/dex/trending
- GET https://cryptodataapi.com/api/v1/dex/new-pools
- GET https://cryptodataapi.com/api/v1/indicators/technical
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
- GET https://cryptodataapi.com/api/v1/market-data/klines
3. Compute the signals described in the playbook on 1d bars (pinned: interval=1d, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the LST Depeg Arbitrage (stETH / rETH / cbETH) strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=1d (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/arbitrage/lst-depeg-arbitrage.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
A relative-value pair trade: long bridge tokens with multi-verifier (multi-DVN, multi-Guardian, multi-relayer) configurations; short tokens of bridge applications still using thin-verifier (1-of-1 DVN, single-validator, single-multisig) configurations.
Why it works: KelpDAO (Apr 2026) demonstrated that 1-of-1 DVN configurations on LayerZero are fatal: a single Decentralized Verifier Network compromise via RPC poisoning + DDoS forced failover to corrupted nodes, draining ~$290M and contributing to a reported ~$15B TVL drawdown across DeFi (Galaxy Research figure). LayerZero subsequently announced it will no longer sign messages from 1-of-1 DVN apps. Market has
IndicatorsPrice and volume only — see the playbook for the exact rules.
Via API/api/v1/strategies/multi-dvn-bridge-config-arbitrage
AI-agent prompts
Build it with an AI agent
Build the Multi-DVN Bridge Configuration Arbitrage crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/arbitrage/multi-dvn-bridge-config-arbitrage.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
- GET https://cryptodataapi.com/api/v1/market-data/klines
3. Compute the signals described in the playbook on 1d bars (pinned: interval=1d, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the Multi-DVN Bridge Configuration Arbitrage strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=1d (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/arbitrage/multi-dvn-bridge-config-arbitrage.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
Trading the Principal Token (PT) and Yield Token (YT) decomposition of yield-bearing assets on Pendle Finance. Pendle splits any yield-bearing token into two synthetic components: PT (zero-coupon claim on principal at maturity) and YT (claim on all yield from now until maturity).
Why it works: Pendle Finance splits yield-bearing assets (stETH, sUSDe, eETH) into Principal Tokens (PT) — entitled to underlying at maturity — and Yield Tokens (YT) — entitled to all yield until maturity. PT trades at discount to underlying; the discount equals expected yield. When market priced PT-implied-yield diverges from oracle/strategy expected yield, arb opens.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Build the Pendle PT/YT Arbitrage crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/arbitrage/pendle-pt-yt-arbitrage.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/dex/trending
- GET https://cryptodataapi.com/api/v1/dex/new-pools
- GET https://cryptodataapi.com/api/v1/sentiment/macro
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
- GET https://cryptodataapi.com/api/v1/market-data/klines
3. Compute the signals described in the playbook on 4h bars (pinned: interval=4h, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the Pendle PT/YT Arbitrage strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=4h (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/arbitrage/pendle-pt-yt-arbitrage.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
Polymarket-as-crypto-leading-indicator is a hybrid information-arbitrage strategy that treats polymarket event-resolution odds as a signal source for trading crypto spot and perpetuals — not as a venue for trading prediction markets themselves.
Why it works: Polymarket aggregates calibrated probabilities on event-driven catalysts (Fed decisions, ETF approvals, regulatory outcomes, geopolitical events). On event-resolution markets, these probabilities lead consensus; the signal is tradeable by pre-positioning the affected crypto asset. The reverse direction — using Polymarket BTC/ETH price-threshold odds to forecast spot — does NOT work, because LLM-dr
IndicatorsPrice and volume only — see the playbook for the exact rules.
Via API/api/v1/strategies/polymarket-as-crypto-leading-indicator
AI-agent prompts
Build it with an AI agent
Build the Polymarket as a Crypto Leading Indicator crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/polymarket-as-crypto-leading-indicator.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/on-chain/whales
- GET https://cryptodataapi.com/api/v1/quant/whales
- GET https://cryptodataapi.com/api/v1/news/market-moving
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
- GET https://cryptodataapi.com/api/v1/market-data/klines
3. Compute the signals described in the playbook on 4h bars (pinned: interval=4h, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the Polymarket as a Crypto Leading Indicator strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=4h (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/polymarket-as-crypto-leading-indicator.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
Trading the price discrepancies between binary-outcome prediction markets — primarily Polymarket (crypto-native, on Polygon), Kalshi (CFTC-regulated US), PredictIt (academic/research), and Manifold Markets (play-money).
Why it works: Prediction markets price probabilities of binary outcomes (election winners, economic prints, sports). Multiple venues quote the same event with different liquidity, regulatory access, and participant bases. Cross-venue triangulation, complementary-market arbitrage (YES + NO must = 100%), and reality-vs-market arbitrage all generate persistent edge.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Via API/api/v1/strategies/polymarket-prediction-market-arbitrage
AI-agent prompts
Build it with an AI agent
Build the Polymarket Prediction Market Arbitrage crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/arbitrage/polymarket-prediction-market-arbitrage.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
- GET https://cryptodataapi.com/api/v1/market-data/klines
3. Compute the signals described in the playbook on 4h bars (pinned: interval=4h, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the Polymarket Prediction Market Arbitrage strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=4h (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/arbitrage/polymarket-prediction-market-arbitrage.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
The methodology for sizing and routing arbitrage trades to maximize net profit after AMM slippage, gas, and validator capture — not just maximize gross spread.
Why it works: Competing arb bots size and route trades suboptimally against convex AMM slippage curves; solving the exact sizing/routing optimization captures the share of net profit naive bots leave on the table or burn by over-trading.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Via API/api/v1/strategies/slippage-optimal-pathfinding
AI-agent prompts
Build it with an AI agent
Build the Slippage-Optimal Path-Finding crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/arbitrage/slippage-optimal-pathfinding.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/hyperliquid/trade-flow
- GET https://cryptodataapi.com/api/v1/market-intelligence/taker-buy-sell
- GET https://cryptodataapi.com/api/v1/dex/trending
- GET https://cryptodataapi.com/api/v1/dex/new-pools
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
- GET https://cryptodataapi.com/api/v1/market-data/klines
3. Compute the signals described in the playbook on 5m bars (pinned: interval=5m, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the Slippage-Optimal Path-Finding strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=15m (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/arbitrage/slippage-optimal-pathfinding.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
A tactical companion to stablecoin pair arbitrage and synthetic stablecoin depeg arbitrage. Those pages answer "when does a depeg create a tradable opportunity?" — this page answers "once it does, how do we extract the most profit?". Different question, different toolkit.
Why it works: Stablecoin depegs create temporary price dislocations from $1.00. Multiple distinct profit-capture methods extract value at different risk/reward profiles: spot mean-reversion buy, redemption-channel arb (near risk-free), pair-trade on cross-stable spreads, leveraged borrow-and-redeem, AMM-band capture, post-event short of overshoot, options skew capture. The trade is matching the right capture me
Via API/api/v1/strategies/stablecoin-depeg-profit-capture
AI-agent prompts
Build it with an AI agent
Build the Stablecoin Depeg Profit Capture Playbook crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/arbitrage/stablecoin-depeg-profit-capture.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/derivatives/funding-rates
- GET https://cryptodataapi.com/api/v1/hyperliquid/funding-rates
- GET https://cryptodataapi.com/api/v1/market-intelligence/options
- GET https://cryptodataapi.com/api/v1/volatility/implied
- GET https://cryptodataapi.com/api/v1/sentiment/stablecoins
- GET https://cryptodataapi.com/api/v1/dex/trending
3. Compute Funding Rate, Open Interest on 4h bars (pinned: interval=4h, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the Stablecoin Depeg Profit Capture Playbook strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=4h (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/arbitrage/stablecoin-depeg-profit-capture.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
A mechanism-aware extension of stablecoin pair arbitrage focused on synthetic, algorithmic, and over-collateralized stablecoins (sUSDe, GHO, crvUSD, FRAX hybrid, sDAI, sFRAX, white-label deployments).
Why it works: Synthetic and algorithmic stablecoins (sUSDe, GHO, crvUSD, FRAX, USDe, sDAI) maintain peg via mechanism-specific paths — delta-neutral perp baskets, over-collateralization with soft-liquidation, hybrid backing — that have distinct break modes from fiat-backed stables. Contagion events trigger cross-mechanism repricing. Each break-mode is mechanically predictable; the trade is to long the cheap sta
Via API/api/v1/strategies/synthetic-stablecoin-depeg-arbitrage
AI-agent prompts
Build it with an AI agent
Build the Synthetic Stablecoin Depeg Arbitrage crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/arbitrage/synthetic-stablecoin-depeg-arbitrage.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/derivatives/funding-rates
- GET https://cryptodataapi.com/api/v1/hyperliquid/funding-rates
- GET https://cryptodataapi.com/api/v1/hyperliquid/l2-book
- GET https://cryptodataapi.com/api/v1/liquidity/depth
- GET https://cryptodataapi.com/api/v1/sentiment/stablecoins
- GET https://cryptodataapi.com/api/v1/dex/trending
3. Compute Funding Rate, Open Interest on 4h bars (pinned: interval=4h, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the Synthetic Stablecoin Depeg Arbitrage strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=4h (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/arbitrage/synthetic-stablecoin-depeg-arbitrage.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
Trading the arbitrage and MEV opportunities created by Uniswap V4 hooks — arbitrary smart contracts that execute before/after pool swaps and can modify pool behavior in unprecedented ways.
Why it works: Uniswap V4 (mainnet launch 30 January 2025) introduces 'hooks' — arbitrary smart contracts that execute before/after pool swaps. This enables custom AMM logic (dynamic fees, MEV-internalization, on-chain limit orders, custom curves, gated pools). Hook-specific behaviors create new arb surfaces invisible to V2/V3-aware bots. Edge concentrated in the first 6-18 months of any hook's deployment.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Via API/api/v1/strategies/uniswap-v4-hooks-arbitrage
AI-agent prompts
Build it with an AI agent
Build the Uniswap V4 Hooks Arbitrage crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/arbitrage/uniswap-v4-hooks-arbitrage.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/dex/trending
- GET https://cryptodataapi.com/api/v1/dex/new-pools
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Compute the signals described in the playbook on 5m bars (pinned: interval=5m, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the Uniswap V4 Hooks Arbitrage strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=15m (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/arbitrage/uniswap-v4-hooks-arbitrage.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
Trading the bribe markets for Velodrome (Optimism's dominant DEX) and Aerodrome (Base's dominant DEX) — both implementations of Andre Cronje's ve(3,3) tokenomics.
Why it works: Velodrome (Optimism, 2022+) and Aerodrome (Base, 2023+) implement Andre Cronje's ve(3,3) tokenomics: lock VELO/AERO for veVELO/veAERO; vote weekly to direct emissions to specific liquidity pools; receive bribes from protocols competing for that emission. Bribe yield often exceeds 30-100% APR for veToken holders; arbs construct optimal vote allocations.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Via API/api/v1/strategies/velodrome-aerodrome-bribe-arbitrage
AI-agent prompts
Build it with an AI agent
Build the Velodrome / Aerodrome Bribe Arbitrage crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/arbitrage/velodrome-aerodrome-bribe-arbitrage.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/dex/trending
- GET https://cryptodataapi.com/api/v1/dex/new-pools
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
- GET https://cryptodataapi.com/api/v1/market-data/klines
3. Compute the signals described in the playbook on 1d bars (pinned: interval=1d, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the Velodrome / Aerodrome Bribe Arbitrage strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=1d (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/arbitrage/velodrome-aerodrome-bribe-arbitrage.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
Trading the price dislocations between the same underlying asset wrapped in different tokens. Bitcoin alone has had at least 8 separate wrapped variants on Ethereum (WBTC, renBTC, tBTC, sBTC, hBTC, imBTC, pBTC, BTCB) — each with its own custody model and peg risk.
Why it works: The same underlying asset (BTC, ETH, USDC) trades as multiple wrapped variants (WBTC, renBTC, tBTC, sBTC; ETH/wstETH/cbETH/rETH; USDC/USDC.e/axlUSDC) — each with its own custody model, peg mechanism, and liquidity venue. Wrappers depeg from underlying when redemption rails become impaired or when one wrapper's custodian faces solvency questions.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Via API/api/v1/strategies/wrapped-asset-triangular-arbitrage
AI-agent prompts
Build it with an AI agent
Build the Wrapped Asset Triangular Arbitrage crypto trading strategy using the CryptoDataAPI (X-API-Key header, base https://cryptodataapi.com).
1. Read the playbook first: GET https://cryptodataapi.com/api/v1/algobrain/page?path=wiki/strategies/arbitrage/wrapped-asset-triangular-arbitrage.md
2. Pull the inputs:
- GET https://cryptodataapi.com/api/v1/dex/trending
- GET https://cryptodataapi.com/api/v1/dex/new-pools
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
- GET https://cryptodataapi.com/api/v1/market-data/klines
3. Compute the signals described in the playbook on 5m bars (pinned: interval=5m, lookback=500 bars, universe=BTC,ETH,SOL unless the playbook says otherwise).
4. Emit entry/exit rules, position size (risk 1% of equity per trade) and a stop, as JSON: {"symbol","side","entry","stop","target","size_pct","reason"}.
5. State which regime the rules are valid in (GET /api/v1/regimes/current) and stand aside outside it. Research only — do not place orders.
Backtest it
Backtest the Wrapped Asset Triangular Arbitrage strategy on CryptoDataAPI history before trusting it.
- Bars: GET https://cryptodataapi.com/api/v1/backtesting/klines?symbol=BTC&interval=15m (Pro)
- Funding: GET https://cryptodataapi.com/api/v1/backtesting/funding?symbol=BTC (Pro)
- Rules: from the playbook at /api/v1/algobrain/page?path=wiki/strategies/arbitrage/wrapped-asset-triangular-arbitrage.md
Pinned: fees 4.5 bps taker per side, 2 bps slippage, funding applied every 8h, signals on bar close only (no lookahead), 70/30 in-sample/out-of-sample split. Report CAGR, Sharpe, max drawdown, trade count and out-of-sample vs in-sample decay.
Any key works, Free included — mint one in a single call. The list endpoint returns summaries; the per-slug endpoint adds the prompts, edge mechanism and data inputs. Full playbooks come from /api/v1/algobrain/page?path=… using each entry's wiki_path. Or use the MCP server.
What are defi & on-chain arbitrage crypto trading strategies?
Price gaps that live on-chain: DEX triangles, flash loans, cross-chain and L2 spreads, LST and stablecoin depegs, yield-token mispricing.
How many defi & on-chain arbitrage strategies are there?
Which indicators do defi & on-chain arbitrage strategies use?
Most often Open Interest, Funding Rate, Volatility.
Can an AI agent build these strategies from an API?
Yes. GET /api/v1/strategies?group=defi-arbitrage lists them; GET /api/v1/strategies/{slug} returns the build and backtest prompts, and each prompt names the exact Crypto Data API endpoints to call. Any API key works, Free included.