{"enrichment":{"faq":[{"a":"Mean-reversion uses statistical tests including the Augmented Dickey-Fuller (ADF) test for stationarity, Hurst exponent calculation to measure mean-reversion strength, and variance ratio tests to confirm price series predictably return to their long-run average. These tests identify assets suitable for mean-reversion trading strategies.","q":"How does mean-reversion detect mean reverting assets?"},{"a":"Mean-reversion generates buy/sell signals by measuring z-score deviations from the mean. When a price deviates significantly (high z-score), mean-reversion signals a potential reversal trade. The skill calculates z-score thresholds to define entry and exit points, helping traders capitalize on temporary price dislocations.","q":"What are z-score mean reversion signals and how do I use them?"},{"a":"Mean-reversion estimates mean-reversion speed and half-life\u2014the time for a price to revert halfway to its mean. This metric informs position sizing and holding periods. Faster half-lives suit shorter-term trades; slower ones require longer holding periods and larger position adjustments.","q":"How does mean-reversion estimate half-life for position sizing?"},{"a":"Yes. Mean-reversion identifies cointegrated pairs whose spreads exhibit mean-reverting behavior, enabling pairs trading strategies. The skill tests spread stationarity and models the relationship, allowing traders to profit from temporary divergences between correlated assets.","q":"Can mean-reversion find cointegrated pairs for spread trading?"},{"a":"Mean-reversion models mean-reverting dynamics using the Ornstein-Uhlenbeck process, a continuous-time framework capturing mean-reversion speed and volatility. This approach enables more sophisticated parameter estimation and risk modeling compared to discrete-time methods.","q":"What is the Ornstein-Uhlenbeck process in mean-reversion modeling?"},{"a":"Mean-reversion excels in ranging markets where prices oscillate around a stable mean. The skill identifies these conditions via statistical tests, then generates signals when prices deviate from the range. This approach works well for stablecoin depegs, funding rate arbitrage, and other mean-reverting dynamics in crypto and traditional markets.","q":"How can mean-reversion be used for ranging market strategy?"}],"shadow_tags":["statistical-testing","spread-trading","signal-generation","reversion-metrics","pairs-analysis","regime-filtering","stationarity-check","time-series-modeling","risk-adjusted-sizing"],"summary_rewrite":"Mean-reversion identifies when prices, spreads, or other financial metrics deviate from their long-run average and predictably return. This skill provides statistical tests (ADF, Hurst exponent, variance ratio) to confirm mean reversion, half-life estimation to time entries and exits, z-score frameworks for signal generation, and Ornstein-Uhlenbeck process modeling for continuous-time analysis."},"files":[{"bytes":9955,"path":"skills/mean-reversion/SKILL.md","sha256":"158f03d64b3aa331ca151d37094f8b503c7eaa5d0182823916aadaaed89a4ab6","url":"https://skillfed.io/files/agiprolabs/claude-trading-skills/mean-reversion/d9c697ce/SKILL.md"}],"id":"agiprolabs/claude-trading-skills/mean-reversion","links":{"html":"https://skillfed.io/agiprolabs/claude-trading-skills/mean-reversion","md":"https://skillfed.io/agiprolabs/claude-trading-skills/mean-reversion.md","repo":"https://github.com/agiprolabs/claude-trading-skills"},"meta":{"agents_supported":[],"first_seen":"2026-07-28","forks":52,"language":"Python","last_updated":"2026-06-24","license":"MIT","name":"mean-reversion","publisher":"agiprolabs","stars":248},"relations":{"similar":[{"id":"agiprolabs/claude-trading-skills/cointegration-analysis"},{"id":"nicepkg/ai-workflow/pair-trade-screener"},{"id":"BaggaT236/AI-Trading-Skills/pair-trade-screener"},{"id":"tradermonty/claude-trading-skills/pair-trade-screener"},{"id":"HKUDS/Vibe-Trading/correlation-analysis"},{"id":"agiprolabs/claude-trading-skills/regime-detection"},{"id":"JoelLewis/finance_skills/volatility-modeling"},{"id":"LeonChaoX/qinyan-academic-skills/pymc"},{"id":"drshailesh88/integrated_content_OS/pymc"},{"id":"synthetic-sciences/openscience/pymc"}]},"slug":{"owner":"agiprolabs","repo":"claude-trading-skills","skill":"mean-reversion"},"version":"d9c697ce"}