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quantitative-statistics

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Test stationarity, model volatility, and validate signals.

Data & Analytics#quantitative finance#bootstrap#garch#cointegration#regression diagnostics#time series testing
Authorloanntc
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill helps you rigorously validate quantitative trading assumptions by running core statistical tests, volatility models, and diagnostics so your backtest conclusions are more defensible.

Core Features & Use Cases

  • Time-series integrity checks: Run ADF stationarity testing, Engleā€“Granger cointegration testing, and Granger causality for predictive relationships.
  • Volatility modeling: Fit GARCH(1,1) and common variants (e.g., EGARCH, GJR-GARCH, FIGARCH) to capture volatility clustering and persistence.
  • Regression diagnostics & inference: Test for heteroskedasticity/autocorrelation, apply bootstrap confidence intervals, and correct for multiple testing (e.g., FDR).

Quick Start

Ask the AI to analyze your price/return series by running ADF, cointegration, GARCH fitting, residual diagnostics, and bootstrap-based significance testing for your strategy metrics.

Dependency Matrix

Required Modules

None required

Components

Standard package

šŸ’» Claude Code Installation

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Please help me install this Skill:
Name: quantitative-statistics
Download link: https://github.com/loanntc/Paave/archive/main.zip#quantitative-statistics

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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