AutoQuant: Auditable Framework for Crypto Futures Strategy Tuning
Research Paper#Cryptocurrency Trading, Algorithmic Trading, Backtesting🔬 Research|Analyzed: Jan 3, 2026 20:00•
Published: Dec 27, 2025 05:46
•1 min read
•ArXivAnalysis
This paper addresses the fragility of backtests in cryptocurrency perpetual futures trading, highlighting the impact of microstructure frictions (delay, funding, fees, slippage) on reported performance. It introduces AutoQuant, a framework designed for auditable strategy configuration selection, emphasizing realistic execution costs and rigorous validation through double-screening and rolling windows. The focus is on providing a robust validation and governance infrastructure rather than claiming persistent alpha.
Key Takeaways
- •Backtests in crypto futures are often overly optimistic due to ignoring execution costs.
- •AutoQuant provides a framework for more realistic and auditable strategy evaluation.
- •Double-screening and rolling window validation are crucial for robust results.
- •The framework focuses on validation and governance, not alpha generation claims.
Reference / Citation
View Original"AutoQuant encodes strict T+1 execution semantics and no-look-ahead funding alignment, runs Bayesian optimization under realistic costs, and applies a two-stage double-screening protocol."