change-point-detection
Use when segmenting time-series into regimes, detecting structural breaks, or constructing context sets for few-shot learning. Covers GP-CPD algorithms, Matérn kernels, likelihood ratio tests, regime identification, market state transitions, volatility regime changes, and trend reversals in financial markets.
npx skills add majiayu000/claude-skill-registry --skill change-point-detection-donaldshen27-xtrend-vanilla-2 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Change-Point Detection for Financial Regimes ## Purpose Comprehensive guide for detecting regime changes in financial time-series using Gaussian Process change-point detection (GP-CPD), essential for segmenting markets into stationary periods and improving trading strategies. ## When to Use Activate this skill when: - Segmenting time-series into distinct regimes - Detecting structural breaks or market transitions - Constructing context sets for few-shot learning - Identifying momentum crashes or reversals - Analyzing volatility regime changes - Building regime-aware trading models ## Core Concepts ### 1. What is a Regime Change? A **regime change** (or change-point) is a point in time where the statistical properties of a time-series shift significantly. **Examples in Finance:** - **2020 COVID-19**: Transition from bull market to extreme volatility - **2008 Financial Crisis**: Shift to high correlation and volatility - **2022 Russia-Ukraine**: Commodity market disruption - **Rate Hiking Cycles**: Change in interest rate sensitivity **Why Detect Them?** - Momentum strategies suffer during regime transitions ("momentum crashes") - Different regimes require different trading approac
- Purpose
- When to Use
- Core Concepts
- 1. What is a Regime Change?
- 2. Gaussian Process Basics
- 3. Change-Point Kernel
- 4. GP-CPD Algorithm
- 5. Segmentation Algorithm
- 6. Using CPD for Context Sets
- Hyperparameter Selection
- Lookback Window
- Severity Threshold
- Segment Length Constraints
- Practical Usage
What does the change-point-detection skill do?
Use when segmenting time-series into regimes, detecting structural breaks, or constructing context sets for few-shot learning. Covers GP-CPD algorithms, Matérn kernels, likelihood ratio tests, regime identification, market state transitions, volatility regime changes, and trend reversals in financial markets.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill change-point-detection-donaldshen27-xtrend-vanilla-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.