Funding carry factor construction

Abstract Traditional portfolio construction relies on equity-centric risk factors — market beta, size, value, momentum — calibrated over decades of equity returns. Crypto markets present fundamentally different risk dynamics: perpetual funding rates act as a continuous cost-of-carry signal, cross-exchange spreads reveal latent liquidity fragmentation, and extreme funding rate dispersion signals regime-dependent tail risk. This paper proposes a three-factor crypto-native framework — funding carry, spread compression, and dispersion momentum — and evaluates its explanatory power using 831,910 funding rate observations and cross-exchange pricing data from Binance, Hyperliquid, and AsterDEX. We find that funding carry factors exhibit strong persistence for a subset of assets (XMR, NEAR, ZRO at 2–5% annualized), but that extreme negative funding on long-tail assets (PROVE, SUPER, ALT at −25% to −44% annualized) is dominated by survivorship and listing effects rather than systematic risk premia. This is a pilot study — sample coverage spans a single market cycle and lacks out-of-sample validation. The framework is proposed as a starting point, not a production-ready allocation model. Hypotheses - H1 (Moderate confidence): Persistent positive funding rates on select mid-cap perpetuals (XMR, NEAR, ZRO) reflect a structural short-demand premium that can be harvested as a carry factor. Confidence: moderate — persistence is observed but the underlying driver (hedging demand vs. speculative sentiment) is unidentified. - H2 (Low confidence): Cross-exchange spreads between DEX venues (Hyperliquid, AsterDEX) and Binance predict short-term price convergence and can serve as a liquidity-risk factor. Confidence: low — spread data is point-in-time and lacks time-series depth for statistical validation. - H3 (Exploratory): The dispersion of funding rates across assets (measured as cross-sectional standard deviation) functions as a systemic stress indicator that predicts portfolio drawdown risk. Confidence: exploratory — related work (May 2024 dispersion ratio analysis) showed promise, but this formulation lacks out-of-sample testing. Data Provenance All data is sourced from real-time production systems operated by Vex Capital: | Dataset | Source | Records | Collection Method | |---------|--------|---------|-------------------| | Funding rates | PerpsTrader funding.db | 831,910 observations | API polling, 8-hour intervals, multi-exchange | | Cross-exchange spreads | PerpsTrader trading.db | 10 top spreads (point-in-time) | Real-time order book comparison | | Asset coverage | 20+ perpetual futures | 3,617 samples per asset | Continuous since system deployment | Important caveats: - Funding rate data covers a single market cycle (not decade-long equity-style data) - Cross-exchange spreads are point-in-time snapshots, not full time-series - The sample is biased toward assets with active perpetual listings on Hyperliquid and Binance - No execution cost, slippage, or fill-rate data is included in spread estimates Analysis Factor 1: Funding Carry The funding carry factor captures the expected return from holding positions that earn persistent funding payments. Unlike equity dividends, crypto funding rates are paid continuously (typically every 8 hours) and reflect real-time supply-demand for leverage. Top persistent positive funding (shorts pay longs): | Asset | Avg Annualized | Range | Samples | Reliability | |-------|---------------|-------|---------|-------------| | XMR | +5.27% | −7.71% to +35.85% | 3,617 | RELIABLE | | PURR | +4.75% | −606.09% to +171.80% | 3,617 | RELIABLE (high vol) | | NIL | +2.56% | −11.00% to +30.98% | 3,617 | RELIABLE | | LIT | +2.42% | −18.48% to +40.10% | 3,617 | RELIABLE | | MANTA | +2.37% | +1.37% to +27.86% | 3,617 | RELIABLE | | ZRO | +2.30% | +1.37% to +17.47% | 3,617 | RELIABLE | | NEAR | +2.07% | −4.68% to +21.34% | 3,617 | RELIABLE | The carry quality metric (mean return / volatility) is highest for XMR and NEAR — these assets exhibit positive funding with relatively contained downside volatility. PURR, despite higher average carry, has extreme range (−606% to +172%) making it unsuitable for risk-managed carry strategies. Extreme negative funding (longs pay shorts — "crowded long" signal): | Asset | Avg Annualized | Min Annualized | Samples | Reliability | |-------|---------------|---------------|---------|-------------| | PROVE | −43.80% | −910.95% | 3,617 | UNRELIABLE (listing effect) | | SUPER | −26.73% | −1,096.42% | 3,617 | UNRELIABLE (listing effect) | | ALT | −25.18% | −484.99% | 3,617 | UNRELIABLE (listing effect) | These extreme negative rates are dominated by early-listing dynamics — newly listed perpetuals attract one-directional speculative flow, creating funding rates that are structurally non-stationary. Using them as risk factors without controlling for listing age introduces severe survivorship bias. Factor 2: Cross-Exchange Spread Compression Cross-exchange price differentials re