change-point-detector
Skill7 starsChanged 4 months agoLicence not identifiedView on GitHub
Bayesian Online Change-Point Detection (BOCPD) on a ticker's daily log returns. Detects points in time where the return-generating distribution changed (regime shift in mean, vol, or both), reports the confidence at each detected boundary, and emits per-segment statistics (annualized return, annualized vol) so the reader can see what changed. Uses Adams and MacKay (2007) BOCPD with a Normal-Gamma prior on (mu, tau) and a Student-t predictive so hyperparameters update in closed form. Requires Stocks Basic. Runs on the free tier.
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In this repository62 other files it gives its agents.
- .claude/CLAUDE.mdCLAUDE.md
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- morning-briefSkill
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- portfolio-macro-scenarioSkill
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- pre-earnings-full-stackSkill
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- regime-auditSkill
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- risk-reportSkill
- rough-vol-forecastSkill
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- t+1-settlement-prepSkill
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- universe-builderSkill
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- vs-benchmark-auditSkill
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The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
0
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The licence could not be identified — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
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