Generate volatility regime signals from historical returns for mean-reversion trades.
npx skills add https://github.com/HKUDS/Vibe-Trading --skill volatility
Please help me install this Agent Skill. Skill: volatility Source: https://github.com/HKUDS/Vibe-Trading/tree/main/agent/src/skills/volatility Command: npx skills add https://github.com/HKUDS/Vibe-Trading --skill volatility
This skill keeps traders from missing volatility regime swings by automatically spotting low or high volatility periods for mean-reversion strategies, eliminating manual percentile calculations and guesswork.
Ask the trading agent to generate volatility signals for BTC-USDT using hv_window 20, lookback 120, and annualize 365.
High-intent search queries and answers about installing and using this skill.
To calculate volatility percentiles for mean-reversion trades, you annualize rolling historical volatility over a lookback window and rank it to identify low and high volatility regimes. Percentile ranking exposes regime swings to trigger long, short, or neutral trading signals.
A volatility regime signal identifies market calm or turbulence using historical volatility percentiles. In crypto trading, low percentile readings trigger long entries, high readings trigger exits or shorts, and middle ranges stay neutral to reduce whipsaws.
Yes, you can generate mean-reversion signals for equities by feeding daily OHLCV data into a volatility percentile calculator. The process annualizes historical returns and applies threshold logic to decide long, short, or neutral exposures based on volatility regimes.
Use historical volatility percentiles when you need to identify relative volatility regimes for mean-reversion timing. Percentile ranking clarifies whether current volatility is historically high or low, whereas standard deviation alone lacks regime context for entries and exits.
Set up crypto volatility signals by defining an hv_window for rolling historical volatility calculation, a lookback period for percentile ranking, and an annualize factor like 365 for crypto. These parameters process OHLCV data to expose low and high volatility periods.
0xZKnwCalculate annualized historical volatility and percentile rankings from OHLCV data.
JacobHsuGenerate mean-reversion trading signals from percentile-ranked historical volatility.
NigarumOvumCalculate annualized historical volatility, rank percentiles, and generate trading signals.
loanntcGenerates long/short/neutral signals from rolling historical volatility percentiles.
