{"enrichment":{"faq":[{"a":"volatility uses a mean reversion approach by computing annualized historical volatility and ranking it percentile-wise over a lookback period. When volatility sits in the low percentile range, long signals trigger to position for expansion; when volatility ranks high, short or exit signals fire to bet on contraction. This captures the tendency for extreme volatility to revert toward average levels.","q":"What is volatility mean reversion strategy and how does it work?"},{"a":"volatility ranks current historical volatility against its percentile distribution over the lookback window. Low percentile readings indicate a low volatility regime suitable for long entry, while high percentile readings signal a high volatility regime for short positioning or exits. This percentile-based ranking automatically adapts to market conditions without fixed thresholds.","q":"How does volatility identify low and high volatility regimes?"},{"a":"Yes. volatility generates signals by monitoring volatility expansion and contraction patterns. Long signals emerge when volatility expands from low percentile levels, capturing upside moves as markets become more active. Short or exit signals trigger when volatility contracts from high percentile levels, betting on mean reversion back to calmer conditions.","q":"Can volatility generate trading signals from volatility expansion and contraction?"},{"a":"volatility works with any OHLCV (open, high, low, close, volume) data. It supports both equities and crypto markets, making it flexible across asset classes. The strategy computes annualized historical volatility from price bars, so any market with reliable OHLCV feeds can be backtested or traded live.","q":"What data does volatility require and which markets does it support?"},{"a":"volatility backtests by applying its percentile-ranked historical volatility logic to OHLCV bars over your chosen period. The strategy computes annualized volatility for each bar, ranks it against the lookback window, and generates entry/exit signals based on percentile thresholds. Results show how mean reversion signals would have performed on past data.","q":"How can I backtest volatility-based strategy on historical OHLCV data?"},{"a":"volatility is designed to detect and adapt to volatility regime shifts across crypto and equity markets. By continuously ranking historical volatility percentile-wise, it responds to transitions between calm and turbulent market conditions. This regime-aware approach helps traders adjust positioning when volatility dynamics fundamentally change.","q":"Does volatility capture volatility regime shifts across different markets?"}],"shadow_tags":["mean-reversion","volatility-regimes","percentile-ranking","expansion-contraction","statistical-trading","regime-detection","volatility-cycles","signal-generation","risk-adjusted","ohlcv-compatible"],"summary_rewrite":"This strategy captures volatility mean reversion by computing annualized historical volatility and ranking it percentile-wise over a lookback period. Long signals trigger when volatility sits in the low percentile range, positioning for expansion; short or exit signals fire when volatility ranks high, betting on contraction. Works with any OHLCV data across equities and crypto."},"files":[{"bytes":2117,"path":"agent/src/skills/volatility/SKILL.md","sha256":"28f51210749781848200511189d3311b93ce0e7a01c72ea9e20b187cc9cd1f4d","url":"https://skillfed.io/files/HKUDS/Vibe-Trading/volatility/1eee8c72/SKILL.md"}],"id":"HKUDS/Vibe-Trading/volatility","links":{"html":"https://skillfed.io/HKUDS/Vibe-Trading/volatility","md":"https://skillfed.io/HKUDS/Vibe-Trading/volatility.md","repo":"https://github.com/HKUDS/Vibe-Trading"},"meta":{"agents_supported":[],"first_seen":"2026-07-28","forks":4557,"language":"Python","last_updated":"2026-07-27","license":"MIT","name":"volatility","publisher":"HKUDS","stars":28096},"relations":{"similar":[{"id":"JoelLewis/finance_skills/historical-risk"},{"id":"agiprolabs/claude-trading-skills/regime-detection"},{"id":"agiprolabs/claude-trading-skills/volatility-modeling"},{"id":"nicepkg/ai-workflow/options-strategy-advisor"},{"id":"BaggaT236/AI-Trading-Skills/options-strategy-advisor"},{"id":"tradermonty/claude-trading-skills/options-strategy-advisor"},{"id":"terrylica/cc-skills/opendeviation-eval-metrics"},{"id":"HKUDS/Vibe-Trading/etf-analysis"},{"id":"agiprolabs/claude-trading-skills/correlation-analysis"},{"id":"HKUDS/Vibe-Trading/correlation-analysis"}]},"slug":{"owner":"HKUDS","repo":"Vibe-Trading","skill":"volatility"},"version":"1eee8c72"}