Add a self-contained AAPL daily strategy backtester with risk controls and documentation

[Copilot]

This change adds a complete, backtestable implementation of the requested AAPL daily strategy: EMA(20/50) crossover with RSI, trend, volume, and ATR filters, plus explicit position sizing and exit rules. It turns the strategy specification into runnable code and repository-level documentation rather than a prose-only design.

• Strategy engine

  • Adds src/aapl_strategy.py with:
    • OHLCV CSV loading and validation
    • indicator calculations for EMA, SMA, RSI, and ATR
    • next-open entry/exit execution
    • 2% equity-at-risk position sizing using the 12% hard stop
    • exit handling for hard stop, trailing stop, profit target, and bearish EMA cross
    • summary metrics including profit factor, drawdown, win rate, Sharpe, CAGR, and final equity

• Execution model

  • Encodes the strategy as daily close signal evaluation with fills at the next session open
  • Applies explicit slippage assumptions in both directions
  • Keeps the implementation cash-constrained so position size cannot exceed available capital

• Test coverage

  • Adds tests/test_aapl_strategy.py covering:
    • SMA / EMA / RSI / ATR computations
    • position sizing math
    • CSV validation for invalid market data
    • a deterministic trade path that exercises live strategy behavior

• Documentation

  • Replaces the placeholder README with a usable strategy spec:
    • entry and exit rules
    • risk model
    • data requirements and assumptions
    • expected backtest shape and limitations
    • CLI usage for running the backtester

• Repo hygiene

  • Adds .gitignore entries for Python bytecode and __pycache__

Example usage:

python src/aapl_strategy.py /absolute/path/to/aapl_daily.csv

Core sizing logic now implemented in code:

stop_price = entry_price * (1 - config.hard_stop_pct)
risk_budget = equity * config.risk_per_trade
shares = floor(risk_budget / (entry_price - stop_price))