vegas-backtest-runbook

Run Vegas strategy backtests and query results from back_test_log.

25|12|Updated Jun 4, 2024
One-click install
npx skills add https://github.com/fairwic/rust_quant --skill vegas-backtest-runbook
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: vegas-backtest-runbook
Source: https://github.com/fairwic/rust_quant/tree/main/.claude/skills/vegas-backtest-runbook
Command: npx skills add https://github.com/fairwic/rust_quant --skill vegas-backtest-runbook

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a structured process for iterating on the Vegas trading strategy's parameters, enabling users to efficiently test, analyze, and optimize trading configurations.

Core Features & Use Cases

  • Backtest Execution: Run backtests for the Vegas strategy with specified configurations.
  • Result Analysis: Query and analyze backtest results from the back_test_log table.
  • Parameter Tuning: Update strategy and risk configurations stored in the database.
  • Iteration Logging: Maintain a historical log of strategy iterations and their outcomes.
  • Use Case: A quantitative trader wants to find the optimal min_trend_move_pct for the Vegas strategy on ETH-USDT-SWAP 4H. They use this Skill to run multiple backtests with varying min_trend_move_pct values, analyze the sharpe_ratio and max_drawdown from the back_test_log, and finally update the strategy_config with the best-performing parameters.

Quick Start

Execute the Vegas backtest by running the cargo command with the specified environment variables.

Frequently Asked Questions about vegas-backtest-runbook

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

FAQPage Schema
How do I backtest a Vegas trading strategy and analyze the results?

To backtest a Vegas trading strategy, execute the backtest command and query the `back_test_log` table to analyze performance metrics like `sharpe_ratio` and `max_drawdown` for strategy optimization.

What is the best way to iterate quantitative trading parameters for risk management?

Iterating quantitative trading parameters involves running multiple backtests with varying values, analyzing outcomes via SQL queries, and updating the `strategy_config` and risk configurations in the database with the optimal parameters.

How do I update strategy and risk configurations after a Vegas strategy backtest?

You update strategy and risk configurations by applying SQL commands to modify the database entries, ensuring the best-performing parameters from the `back_test_log` are saved for future trading execution.

What are common JSON configuration pitfalls when running a trading strategy backtest?

Common JSON configuration pitfalls during a backtest include syntax errors or incorrect parameter mapping, which can be avoided by strictly adhering to the compatibility guidelines for historical data.

How can I query historical backtest results to evaluate strategy performance?

You query historical backtest results by executing essential SQL queries against the `back_test_log` table to extract and evaluate specific performance metrics for your trading strategy.