Implement trading fee model in portfolio rebalancing and update relat…

[lbsm2017]

…ed documentation

[Copilot]

Pull request overview

This PR implements a trading fee model for portfolio rebalancing and enhances individual hedge analysis with performance metrics (CAGR, Sharpe). The changes enable realistic transaction cost modeling in the quantitative finance backtesting framework.

Key changes:

• Adds configurable trading fees (basis points per turnover) applied during rebalancing
• Computes base (unhedged) performance metrics for comparison with hedged portfolios
• Enriches HTML reports with CAGR and Sharpe ratios alongside existing risk metrics

Reviewed changes

Copilot reviewed 8 out of 9 changed files in this pull request and generated no comments.

Show a summary per file

File	Description
config.yaml	Adds trading_fee_bps: 10 parameter under rebalancing section
src/backtester/rebalancing.py	Implements fee calculation logic in simulate_rebalanced_portfolio() with first-day exemption
src/backtester/engine.py	Computes base_metrics for unhedged baseline, enriches optimization results with CAGR/Sharpe per weight, passes fees to simulations
src/reporting/report.py	Adds trading fee and rebalancing frequency to summary, expands individual hedge table with 4 new performance columns (base/hedged CAGR and Sharpe)
tests/test_rebalancing.py	Adds TestTradingFees class with 5 comprehensive tests covering fee mechanics, edge cases, and frequency effects
tests/test_engine.py	Adds TestBaseMetrics class verifying base_metrics presence, structure, and handling of insufficient data
docs/trading_fees.md	Documents implementation approach, fee formula, design decisions, and testing strategy
data/risk_free_rate.parquet	Binary data file update (likely routine data refresh)
data/prices_metadata.csv	Updates end date from 2025-12-08 to 2025-12-09 (routine data refresh)