strategy-compare

/strategy-compare RELIANCE ema-crossover rsi donchian /strategy-compare SBIN long-vs-short ema-crossover

Parse $ARGUMENTS as: symbol followed by strategy names • $0 = symbol (e.g., SBIN, RELIANCE, NIFTY) • Remaining args = strategies to compare (e.g., ema-crossover rsi donchian) If only a symbol is given with no strategies, compare: ema-crossover, rsi, donchian, supertrend. If "long-vs-short" is one of the strategies, compare longonly vs shortonly vs both for the first real strategy.

• Read the vectorbt-expert skill rules for reference patterns • Create backtesting/strategy_comparison/ directory if it doesn't exist (on-demand) • Create a .py file in backtesting/strategy_comparison/ named {symbol}_strategy_comparison.py • The script must: • Fetch data once via OpenAlgo • If user provides a DuckDB path, load data directly via duckdb.connect(path, read_only=True). See vectorbt-expert rules/duckdb-data.md. • If openalgo.ta is not importable (standalone DuckDB), use inline exrem() fallback. • Use TA-Lib for ALL indicators (never VectorBT built-in) • Use OpenAlgo ta for specialty indicators (Supertrend, Donchian, etc.) • Clean signals with ta.exrem() (always .fillna(False) before exrem) • Run each strategy on the same data • Indian delivery fees: fees=0.00111, fixed_fees=20 for delivery equity • Collect key metrics from each into a side-by-side DataFrame • Include NIFTY benchmark in the comparison table (via OpenAlgo NSE_INDEX) • Print Strategy vs Benchmark comparison table: Total Return, Sharpe, Sortino, Max DD, Win Rate, Trades, Profit Factor • Explain results in plain language - which strategy performed best and why • Plot overlaid equity curves for all strategies using Plotly (template="plotly_dark") • Save comparison to CSV • Never use icons/emojis in code or logger output