backtest

Name: backtest
Availability: InStock
Author: upbit-official

Execute historical backtests of JSON trading strategies using Upbit candle data.

7|Updated Jun 30, 2026

Search Tags:#strategy #simulation #finance #trading #backtest #upbit

Ready to run

npx skills add https://github.com/upbit-official/upbit-strategy-toolkit --skill backtest-upbit-official

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: backtest
Source: https://github.com/upbit-official/upbit-strategy-toolkit/tree/main/.cursor/skills/backtest
Command: npx skills add https://github.com/upbit-official/upbit-strategy-toolkit --skill backtest-upbit-official

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires uv, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This skill removes the guesswork from trading strategy development by providing a standardized, objective environment to validate hypotheses against historical Upbit market data without the risk of live trading.

Core Features & Use Cases

Deterministic Backtesting: Runs strategy JSON files against historical candle data to produce factual performance metrics like CAGR, MDD, and Sharpe ratios.
Hypothesis Falsification: Automatically compares backtest results against user-defined criteria to provide an objective assessment of whether a strategy hypothesis holds up.
Benchmark Comparison: Provides a direct, factual comparison against simple market buy-and-hold performance to contextualize strategy effectiveness.

Quick Start

Run the backtest skill for the strategy file named golden-cross-v1 to validate its performance and hypothesis.

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 historical market data?▼

Backtesting a trading strategy requires defining it in a JSON file and running it against historical candle data. The simulation produces factual performance metrics like CAGR, MDD, and Sharpe ratios.

What is hypothesis falsification in trading strategy simulation?▼

Hypothesis falsification in trading simulation automatically compares backtest results against user-defined criteria. This provides an objective assessment of whether a strategy hypothesis holds up under historical market conditions.

Do I need uv installed to run strategy simulations with Upbit data?▼

Yes, you need uv installed to run strategy simulations. The skill requires uv for environment management and network access to the Upbit candle API to retrieve historical market data.

Can I compare my trading strategy results against a market benchmark?▼

You can compare your trading strategy results against a market benchmark. The skill provides a direct factual comparison against simple buy-and-hold performance to contextualize strategy effectiveness.

What limitations exist when validating trading strategies with historical data?▼

A key limitation of validating trading strategies with historical data is the requirement for continuous network access to the Upbit candle API. Simulations are also strictly bound to the deterministic data available in that historical feed.