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Hypotheses

Daily Cross-Sectional Low-Volatility Anomaly: Long Bottom-2 Lowest-Vol + Short Top-2 Highest-Vol Across 6 Major Binance Perps

A dollar-neutral, cross-sectional anomaly strategy on a fixed universe of 6 major Binance USD-M perpetuals (BTC, ETH, SOL, BNB, AVAX, LINK — all confirmed clean data) that captures the most-documented cross-sectional…

Hypothesis

A dollar-neutral, cross-sectional anomaly strategy on a fixed universe of 6 major Binance USD-M perpetuals (BTC, ETH, SOL, BNB, AVAX, LINK — all confirmed clean data) that captures the most-documented cross-sectional risk anomaly in finance: the LOW-VOLATILITY ANOMALY. Every 24 hours, the strategy ranks the 6 assets by their trailing 30-day realized volatility, goes LONG the 2 LOWEST-vol assets and SHORT the 2 HIGHEST-vol assets, equal-weighted within each leg, dollar-neutral. Hold 24 hours, then re-rank. The……Show moreShow less

A dollar-neutral, cross-sectional anomaly strategy on a fixed universe of 6 major Binance USD-M perpetuals (BTC, ETH, SOL, BNB, AVAX, LINK — all confirmed clean data) that captures the most-documented cross-sectional risk anomaly in finance: the LOW-VOLATILITY ANOMALY. Every 24 hours, the strategy ranks the 6 assets by their trailing 30-day realized volatility, goes LONG the 2 LOWEST-vol assets and SHORT the 2 HIGHEST-vol assets, equal-weighted within each leg, dollar-neutral. Hold 24 hours, then re-rank. The middle 2 assets are excluded. This is the third in a cross-sectional series (after CrossSectionalMeanReversion3Major using HL funding and DailyCrossSectional7DReturnReversal using Binance returns) — same major-basket universe, COMPLETELY DIFFERENT signal axis. Volatility ranking is structurally orthogonal to return ranking and funding ranking, so this strategy will take positions UNCORRELATED with the prior two cross-sectional strategies, providing genuine portfolio diversification rather than mechanism overlap. The Low-Vol Anomaly is documented in: Black (1972), Frazzini-Pedersen (2014) 'Betting Against Beta', Baker-Bradley-Wurgler (2011) 'Benchmarks as Limits to Arbitrage', and crypto-specific Liu-Tsyvinski-Wu (2022) 'Common Risk Factors in Cryptocurrency'. The mechanism: high-vol crypto assets attract speculative 'lottery-ticket' flow that systematically underperforms their realized volatility (retail FOMO + periodic liquidation cascades); low-vol assets attract institutional / long-horizon capital that provides structural bid support and steady risk-adjusted returns. Directly responds to the analyst's repeated recommendation: 'prioritize cross-sectional mechanisms for the current regime'. Fills FIVE under-represented buckets: long-short direction (14.0% → toward 45%), multi-instrument scope (7.2% → grow), cross-sectional class (the confirmed-winning mechanism), portfolio diversifier vs directional strategies, and BINANCE-USD-M-only (clean data). Position sizing: 12% of equity per leg × 2 + 12% × 2 = 48% gross exposure, dollar-neutral. Risk per trade: ~1% from daily vol-dispersion volatility.

Backtest and paper results are hypothetical. Trading involves risk of loss.