Perform quantitative analysis of returns, correlations, risk factors, and portfolio optimization. Statistical modeling with institutional-grade rigor.
Execute structured quantitative analysis workflows with statistical validation.
data_validator_cli.py for statistical validity (outliers, gaps, splits)risk_metrics_cli.py for VaR/CVaR/Sharpe/Sortino/Drawdown (minimum 90 days)momentum_cli.py for confluence analysisvolatility_cli.py for regime analysiscorrelation_cli.py for diversification and covariance matricesfactors_cli.py for Fama-French 3-factor, Carhart 4-factor modelsbacktester_cli.pyoptimizer_cli.py for mean-variance, risk parity, max Sharpe, Black-Litterman# Risk metrics
uv run python src/analysis/risk_metrics_cli.py TICKER --days 252 --benchmark SPY
# Momentum confluence
uv run python src/utils/momentum_cli.py TICKER --days 90
# Volatility regime
uv run python src/utils/volatility_cli.py TICKER --days 90
# Correlation matrix
uv run python src/analysis/correlation_cli.py TICKER1 TICKER2 --days 90
# Factor analysis
uv run python src/analysis/factors_cli.py TICKER --days 252 --benchmark SPY
# Backtesting
uv run python src/strategies/backtester_cli.py TICKER --days 252 --strategy rsi
# Portfolio optimization
uv run python src/strategies/optimizer_cli.py TICKERS --days 252 --method max_sharpe