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9 cex & cross-venue arbitrage strategies for crypto, from the AlgoBrain wiki. Capture price gaps between centralised venues and instruments — cross-exchange, triangular, spot/perp/futures and latency arbitrage. 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=cex-arbitrage.
Calendar spread arbitrage trades the price relationship between two different expiries of the same crypto futures — near quarterly vs far quarterly, or the perpetual vs a dated quarterly — on venues like Deribit, CME, Binance, and OKX.
Why it works: Crypto dated-futures term structure is set by leverage demand and funding expectations, not storage cost. When the near-vs-far (or perp-vs-quarterly) annualised basis dislocates from fair carry, the arb sells the rich expiry and buys the cheap one and is paid by leveraged directional traders who bid one point of the curve without hedging the other — collecting the convergence with far less directi
Via API/api/v1/strategies/calendar-spread-arbitrage
AI-agent prompts
Build it with an AI agent
Build the Calendar Spread Arbitrage (Crypto) 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/calendar-spread-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/derivatives/open-interest
- GET https://cryptodataapi.com/api/v1/hyperliquid/open-interest
- GET https://cryptodataapi.com/api/v1/sentiment/macro
- GET https://cryptodataapi.com/api/v1/hyperliquid/candles
3. Compute Funding Rate, Open Interest, Basis, Time to Expiration (DTE) 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 Calendar Spread Arbitrage (Crypto) 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/calendar-spread-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.
CDS-Bond Basis Arbitrage trades the spread between a company's cash bond spread (yield over the matching Treasury or asset swap spread) and its CDS spread for the same maturity. In theory these should be equal because both instruments compensate for the same default risk.
Why it works: CDS and cash bond markets price the same credit risk but are intermediated by different dealers, funded differently, and held by different investors; the basis compensates the arbitrageur for funding, balance sheet, and liquidity risk -- not for credit risk.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Via API/api/v1/strategies/cds-bond-basis-arbitrage
AI-agent prompts
Build it with an AI agent
Build the CDS-Bond Basis 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/cds-bond-basis-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/sentiment/macro
- 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 CDS-Bond Basis 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/cds-bond-basis-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.
Put-call parity is a mechanical no-arbitrage constraint. Any dislocation is not a forecast — it is a financing gap created by a participant paying for immediacy (a directional buyer, a forced-liquidation seller, a market maker managing inventory imbalance).
Why it works: Put-call parity is a mechanical no-arbitrage identity; the counterparty is whoever created the dislocation — a large directional buyer lifting one option, a forced liquidation dumping a leg, or a market maker skewing inventory — and they are paying for immediacy while the arb desk locks the gap.
Via API/api/v1/strategies/conversion-reversal-arbitrage
AI-agent prompts
Build it with an AI agent
Build the Conversion & Reversal 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/conversion-reversal-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/derivatives/open-interest
- GET https://cryptodataapi.com/api/v1/hyperliquid/open-interest
- GET https://cryptodataapi.com/api/v1/market-intelligence/options
- GET https://cryptodataapi.com/api/v1/volatility/implied
3. Compute Funding Rate, Delta, Gamma, Vega, Theta 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 Conversion & Reversal 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/conversion-reversal-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-exchange arbitrage captures the price gap for the same crypto asset trading simultaneously on two different venues — CEX↔CEX (e.g. Binance vs Coinbase), or CEX↔DEX (e.g. Binance vs a Uniswap pool).
Why it works: Fragmented crypto liquidity across 100+ CEXs and thousands of DEX pools means the same token prints different prices for tens of milliseconds to minutes. The arbitrageur with pre-positioned inventory on both venues closes the gap and is paid the spread by whoever lifted/hit the stale quote — usually a slower taker or a retail market order on the thinner venue.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Via API/api/v1/strategies/cross-exchange-arbitrage
AI-agent prompts
Build it with an AI agent
Build the Cross-Exchange 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-exchange-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/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
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-Exchange 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-exchange-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.
Triangular arbitrage across the three native wrappers of crypto majors: spot (immediate delivery), perpetual swap (funding-rate-clearing), and dated futures (basis-decay-clearing).
Why it works: Three crypto wrappers (spot, perpetual, dated future) of the same underlying clear on different mechanisms (instant, funding-rate, basis-decay). Mismatched implied yields create a closed triangle when one leg drifts.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Via API/api/v1/strategies/crypto-spot-perp-futures-triangle
AI-agent prompts
Build it with an AI agent
Build the Crypto Spot-Perp-Futures 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/crypto-spot-perp-futures-triangle.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/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 Crypto Spot-Perp-Futures Triangular 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/crypto-spot-perp-futures-triangle.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.
Grayscale Bitcoin Trust (gbtc) discount/premium arbitrage exploited the persistent dislocation between GBTC's share price and its underlying Bitcoin net asset value (NAV).
Why it works: Closed-end trust structure forced creation/redemption asymmetry: shares could be created in-kind by accredited investors but not redeemed, so price could deviate from NAV until ETF conversion.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Build the GBTC Discount/Premium 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/gbtc-discount-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 GBTC Discount/Premium 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/gbtc-discount-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.
Latency arbitrage in crypto exploits the microsecond-to-millisecond window during which a price change on the lead venue has not yet propagated to a lagging venue's order book.
Why it works: When BTC re-prices on the fastest venue (Binance/Bybit/OKX or a lead perp), correlated venues' quotes are momentarily stale. The colocated operator who observes the lead move and hits the stale quote on the lagging venue before its matching engine updates is paid by whoever left that resting order — typically a slower market maker or a retail limit order on the lagging book.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Build the Latency Arbitrage (Crypto) 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/latency-arbitrage.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/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 Latency Arbitrage (Crypto) 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/latency-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.
Generalization of triangular arbitrage to cycles of length 4, 5, 6+.
Why it works: Liquidity fragmentation across DEXs, chains, fee tiers, and stablecoin variants creates 4+ leg cycles whose product exceeds 1 even when no 3-leg cycle is profitable. Detection scales as O(V³) for triangles, O(V⁴⁺) for higher cycles — analytical edge dominates.
IndicatorsPrice and volume only — see the playbook for the exact rules.
Build the Multi-Leg Arbitrage (4+ Legs) 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-leg-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
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 Multi-Leg Arbitrage (4+ Legs) 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/multi-leg-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.
Triangular arbitrage exploits pricing inconsistencies among three related currency pairs on a single exchange. In an efficient market, the cross-rate between any three currencies should be mathematically consistent -- for example, if you know EUR/USD and USD/JPY, the implied EUR/JPY rate is determined.
Why it works: Three currency/asset pairs on a single venue must satisfy a no-arbitrage cross-rate identity; when one quote is momentarily stale relative to the other two, a near-risk-free three-leg cycle returns to the starting asset with a small surplus. The edge is overwhelmingly a speed (latency) race to consume the stale quote before competitors.
Build the 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/triangular-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/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 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/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 cex & cross-venue arbitrage crypto trading strategies?
Capture price gaps between centralised venues and instruments — cross-exchange, triangular, spot/perp/futures and latency arbitrage.
How many cex & cross-venue arbitrage strategies are there?
Which indicators do cex & cross-venue arbitrage strategies use?
Most often Funding Rate, Open Interest, Basis, Time to Expiration (DTE).
Can an AI agent build these strategies from an API?
Yes. GET /api/v1/strategies?group=cex-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.