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Killer-Skills

strategy-compare — how to use strategy-compare how to use strategy-compare, strategy-compare alternative, strategy-compare setup guide, what is strategy-compare, strategy-compare vs backtrader, vectorbt backtesting, quantstats tearsheets, trading strategy optimization, monte-carlo simulation in trading, walk-forward optimization

v1.0.0
GitHub

About this Skill

Perfect for Trading Agents needing advanced backtesting and strategy comparison capabilities using VectorBT strategy-compare is a coding skill for backtesting trading strategies using VectorBT, supporting multiple markets and featuring realistic transaction cost modeling.

Features

Supports backtesting of trading strategies using VectorBT
Features realistic transaction cost modeling for accurate results
Includes 12 ready-made strategy templates for easy comparison
Utilizes QuantStats tearsheets for in-depth strategy analysis
Allows for Monte-Carlo simulations and walk-forward optimization
Supports TA-Lib indicators for technical analysis

# Core Topics

marketcalls marketcalls
[92]
[22]
Updated: 3/5/2026

Quality Score

Top 5%
46
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add marketcalls/vectorbt-backtesting-skills/strategy-compare

Agent Capability Analysis

The strategy-compare MCP Server by marketcalls is an open-source Categories.community integration for Claude and other AI agents, enabling seamless task automation and capability expansion. Optimized for how to use strategy-compare, strategy-compare alternative, strategy-compare setup guide.

Ideal Agent Persona

Perfect for Trading Agents needing advanced backtesting and strategy comparison capabilities using VectorBT

Core Value

Empowers agents to backtest and compare multiple trading strategies across Indian, US, and Crypto markets, utilizing technical indicators like ema-crossover, rsi, and donchian, and supporting long-vs-short strategy comparisons with libraries like VectorBT

Capabilities Granted for strategy-compare MCP Server

Backtesting trading strategies for optimal performance
Comparing multiple strategies across different markets and symbols
Optimizing strategy parameters using VectorBT's backtesting capabilities

! Prerequisites & Limits

  • Requires VectorBT library
  • Limited to Indian, US, and Crypto markets
  • Default strategies used if no strategies are provided
SKILL.md
Readonly

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
  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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