strategy-compare— agent skill

Create a strategy comparison script.

Arguments

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.

Instructions

1. Read the vectorbt-expert skill rules for reference patterns
2. Create backtesting/strategy_comparison/ directory if it doesn't exist (on-demand)
3. Create a .py file in backtesting/strategy_comparison/ named {symbol}_strategy_comparison.py
4. 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

1. Never use icons/emojis in code or logger output

Example Usage

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