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Strategy Compare

By marketcalls· marketcalls/vectorbt-backtesting-skills· 0

Compare multiple trading strategies side-by-side with performance stats.

Installation

  1. Make sure Claude is on your device and in your terminal.

    Skills load from ~/.claude/skills/ when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then run claude in any terminal to verify.

    One-time setup
    npm i -g @anthropic-ai/claude-code

    Already have it? Skip ahead.

  2. Paste into Claude Code or into your terminal.
    Install
    Sign up to copy
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    This copies the whole skill folder into ~/.claude/skills/strategy-compare-marketcalls/ — the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.

    Faster alternative (instruction-only skills)

    Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.

    Quick install (SKILL.md only)
    Sign up to copy
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  3. Restart Claude Code.

    Quit and reopen Claude Code (or any other agent that loads from ~/.claude/skills/). New skills are picked up on startup.

  4. Just ask Claude.

    Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.

Prefer to read the source first? Open on GitHub.

When Claude uses it

Compare multiple strategies or directions (long vs short vs both) on the same symbol. Generates side-by-side stats table.

What this skill does

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 OpenAlgo ta for ALL indicators by default (never VectorBT built-in). Only switch to TA-Lib if the user explicitly says "talib"/"TA-Lib"
    • Always use OpenAlgo ta for specialty indicators (Supertrend, Donchian, etc.) - no TA-Lib equivalent exists
    • 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
  5. 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

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