backtest

Create a complete VectorBT backtest script for the user. Parse $ARGUMENTS as: strategy symbol exchange interval If no arguments, ask the user which strategy they want. /backtest ema-crossover RELIANCE NSE D /backtest rsi SBIN /backtest supertrend NIFTY NFO 5m - $0 = strategy name (e.g., ema-crossover, rsi, donchian, supertrend, macd, sda2, momentum) - $1 = symbol (e.g., SBIN, RELIANCE, NIFTY). Default: SBIN - $2 = exchange (e.g., NSE, NFO). Default: NSE - $3 = interval (e.g., D, 1h, 5m). Default: D - Read the vectorbt-expert skill rules for reference patterns - Create backtesting/{strategy_name}/ directory if it doesn't exist (on-demand) - Create a .py file in backtesting/{strategy_name}/ named {symbol}_{strategy}_backtest.py - Use the matching template from rules/assets/{strategy}/backtest.py as the starting point - The script must: - Load .env from the project root using find_dotenv() (walks up from script dir automatically) - Fetch data via client.history() from OpenAlgo - If user provides a DuckDB path, load data directly via duckdb.connect(path, read_only=True) instead of OpenAlgo API. Auto-detect format: Historify ( market_data table, epoch timestamps) vs custom ( ohlcv table, date+time). See vectorbt-expert rules/duckdb-data.md . - If openalgo.ta is not importable (standalone DuckDB), use inline exrem() fallback.