run-backtest

Name: run-backtest
Availability: InStock
Author: jaggia

Resolve partial inputs and execute backtests with configuration defaults.

1|Updated Apr 11, 2026

Search Tags:#reporting #finance #data-analytics #trading #backtest #monte-carlo

Ready to run

npx skills add https://github.com/Jaggia/backTestingTraderBot --skill run-backtest

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: run-backtest
Source: https://github.com/Jaggia/backTestingTraderBot/tree/main/.claude/skills/run-backtest
Command: npx skills add https://github.com/Jaggia/backTestingTraderBot --skill run-backtest

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill orchestrates end-to-end backtests by taking partial user inputs and filling in the rest from a live configuration, then running a complete backtest and delivering a structured interpretation.

Core Features & Use Cases

Argument resolution: merges user-supplied dates, mode, and data source with config defaults.
MC analysis ready: optionally runs Monte Carlo simulations and produces a report.
Results navigation: locates the generated backtest results and config snapshot for review.
Use Case: A user asks for a backtest for 2025-01-01 to 2026-04-02 with equities, and the skill resolves missing parameters, executes the run, and returns a ready-to-interpret analysis.

Quick Start

Ask Claude to run a backtest for 2025-01-01 to 2026-04-02 in equities mode and review the resulting analysis.

Frequently Asked Questions about run-backtest

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

FAQPage Schema

How do I run a backtest with partial parameters and Monte Carlo simulations?▼

To run a backtest, provide partial inputs like date ranges and trade mode, and the system merges them with defaults from config/strategy_params.yaml. It then executes the run and optionally applies Monte Carlo simulations for robust analysis.

What is Monte Carlo simulation in trading backtests?▼

Monte Carlo simulation in backtesting models probability distributions of trade outcomes to assess strategy robustness. This skill applies Monte Carlo settings to generate statistical insights and saves a Claude-friendly analysis report to the results path.

How to backtest equities or options strategies automatically?▼

Backtesting equities or options requires specifying a trade mode and date range. The skill validates inputs, selects the appropriate runner based on parameter counts, and executes the backtest across the configured data source.

Do I need a configuration file to execute a backtest?▼

Yes, a configuration file is required. The skill reads config/strategy_params.yaml to resolve missing parameters such as data source, date range, and Monte Carlo settings, ensuring the backtest executes with validated defaults.

Can I review configuration snapshots after a backtest run?▼

Yes, you can review configuration snapshots after a backtest run. The skill locates generated backtest results and saves a config snapshot alongside a structured analysis report for interpretation and review.

What are the limitations of automated backtest argument resolution?▼

Automated backtest argument resolution depends entirely on the existing config/strategy_params.yaml file. If required defaults are missing or invalid in the configuration, the validation step will fail before the runner executes.