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commodity-analysis

Generate directional commodity signals for oil, gold, and copper from multi-factor inputs.

6.1k|1.2k|Updated Jun 9, 2022
Search Tags:#signals#backtesting#quantitative#copper#gold#commodity-analysis#oil
One-click install
npx skills add https://github.com/charliedream1/ai_quant_trade --skill commodity-analysis-charliedream1
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: commodity-analysis
Source: https://github.com/charliedream1/ai_quant_trade/tree/main/a_%E5%85%A8%E7%BD%91%E4%BC%98%E7%A7%80%E8%B5%84%E6%BA%90/10_%E5%A4%A7%E6%A8%A1%E5%9E%8B/07_skill%E5%8C%85/vibe_trading_skills/commodity-analysis
Command: npx skills add https://github.com/charliedream1/ai_quant_trade --skill commodity-analysis-charliedream1

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyzes commodity dynamics to generate directional trading signals for backtesting and strategy development.

Core Features & Use Cases

  • Analyze supply-demand balance, inventory cycles, term structure, and seasonality for crude oil, gold, and copper.
  • Generate structured signals suitable for backtesting and risk management.
  • Use case: a quant researcher builds a commodity strategy and uses the signals to decide long/short positions.

Quick Start

Generate a daily directional signal set for crude oil, gold, and copper using supply-demand, inventory cycles, term structure, and seasonality.

Frequently Asked Questions about commodity-analysis

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

FAQPage Schema
How do I generate directional trading signals for crude oil, gold, and copper?▼

Generate directional commodity signals by analyzing supply-demand balance, inventory cycles, term structure, and seasonality. This framework outputs a structured signal report indicating long or short positions for crude oil, gold, and copper.

What factors drive quantitative commodity backtesting signals?▼

Quantitative commodity signals are driven by multi-factor inputs including supply-demand dynamics, inventory cycles, term structure, and seasonality. These factors are computed into indicators to produce structured directional outputs.

Can I export commodity analysis reports to CSV or JSON?▼

Yes, the modular analysis framework outputs a structured signal report suitable for CSV and JSON export. This allows you to seamlessly integrate the generated commodity directional signals into external backtesting systems.

Does this commodity analysis tool require external data source configurations?▼

The framework supports configurable data sources to ingest commodity data for analysis. You must connect your supply-demand, inventory, and term structure data to compute the directional trading indicators.

How are term structure and seasonality used in commodity strategy research?▼

Term structure and seasonality are evaluated as multi-factor inputs within the modular framework. They are computed alongside supply-demand balances to produce structured directional signals for live strategy research and backtesting.

What commodities are supported for quantitative backtesting signal generation?▼

The framework supports quantitative backtesting signal generation for crude oil, gold, and copper. It analyzes inventory cycles and supply-demand dynamics specific to these three commodities to output directional trading indicators.

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