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This study conducts a comprehensive audit of public Binance BTCUSDT perpetual-futures data, revealing significant gaps in data availability that hinder effective trading decisions. The authors found that a five-minute requirement for critical trading data was unmet for over 304 days, leading to a revision in the data streams used for auditing. Ultimately, while the auditing process improved detection of rule violations, it did not demonstrate superiority over random search methods in terms of profitability or agent performance.
Despite rigorous auditing, the adaptive agent failed to outperform random search, highlighting the challenges in achieving profitability in cryptocurrency trading.
Public cryptocurrency archives may appear usable when files exist, although factor research requires observations available and executable at each decision time. We audit public Binance BTCUSDT USD-M perpetual-futures data using event, publication, and availability times and separate proposal from deterministic auditing, evaluation, and holdout access. An initial gapless five-minute requirement for trade, mark, index, and open interest failed: the longest unrepaired intersection was 304.5729166666667 days. A disclosed revision made trade, mark, index, and realized funding the core streams and made open interest optional because its publication time was unverified. The revised mask retained 727 complete UTC days and supported a 436/145/146-day train, validation, and historical-holdout split. On 80 frozen known-rule templates, the auditor detected 40/40 violations and rejected 0/40 legal templates. Across ten null-signal paths, full auditing reduced mean false passes from 0.2910 to 0.0625. Under matched valid-candidate budgets, the audited adaptive agent tied random search and did not establish superiority. In the one-time historical holdout, all evaluated runs had positive IC but negative net Sharpe under primary costs. We therefore report a scoped negative result rather than a profitability or agent-superiority claim.