backtest

Generate a complete VectorBT backtest script for a specified strategy and symbol.

186|44|Updated Feb 25, 2026
One-click install
npx skills add https://github.com/marketcalls/vectorbt-backtesting-skills --skill backtest-marketcalls
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: backtest
Source: https://github.com/marketcalls/vectorbt-backtesting-skills/tree/main/.claude/skills/backtest
Command: npx skills add https://github.com/marketcalls/vectorbt-backtesting-skills --skill backtest-marketcalls

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Backtesting trading strategies quickly on historical data by generating complete, executable VectorBT scripts that validate ideas before live deployment.

Core Features & Use Cases

  • Generate a complete VectorBT backtest script for a given strategy and symbol.
  • Use a templated starting point, load environment configuration, and fetch data via OpenAlgo.
  • Produce performance statistics, plots, and a trade log for review.

Quick Start

Provide a strategy, symbol, exchange, and interval to generate a ready-to-run backtest script.

Frequently Asked Questions about backtest

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I backtest a trading strategy using VectorBT?▼

To backtest a trading strategy using VectorBT, you provide a strategy, symbol, exchange, and interval to generate a ready-to-run Python script. The script fetches historical data via OpenAlgo and runs portfolio backtests using vbt.Portfolio.from_signals.

Can I use TA-Lib indicators in my VectorBT backtest script?▼

Yes, the generated VectorBT backtest script supports using TA-Lib indicators and OpenAlgo ta for technical analysis. The script integrates these indicators to generate the signals required for running portfolio backtests.

What do I need to set up before running an OpenAlgo VectorBT backtest?▼

Before running an OpenAlgo VectorBT backtest, you need to load your environment variables for API configuration and optionally set up a DuckDB path. You also need to specify your target symbol, exchange, and time interval.

How does the VectorBT backtest output performance statistics and trade logs?▼

The VectorBT backtest outputs performance statistics by printing them to the console and generates a QuantStats tearsheet if available. It also plots results with Plotly and exports the executed trades to a CSV file for review.

Is there a way to automatically generate a Python script for a VectorBT backtest?▼

Yes, you can automatically generate a complete Python script for a VectorBT backtest by specifying your chosen strategy and parameters. This process optionally creates a dedicated backtest directory to keep your testing scripts organized.