How does the skill extract AISC (All-In Sustaining Cost)?

The skill uses a priority-based approach: first searching SEC XBRL filings for standardized fields, then parsing MD&A text for keywords, and finally using a proxy formula (OpCost + SustCapex + G&A - Byproduct) / Oz if direct disclosure is missing.

What is the purpose of the 'Backsolve' logic?

Backsolve logic allows you to set a target ratio (e.g., a historical peak of 1.7) and mathematically determine what specific improvements in AISC, debt reduction, or multiple expansion would be required to reach that level.

Which metals and mining universes are supported?

It supports any metal symbol available via Yahoo Finance (e.g., SI=F for Silver, GC=F for Gold) and can analyze individual stocks or entire ETF holdings like SIL, GDX, or SILJ.

Can this skill generate visual reports?

Yes, it includes scripts to generate a four-panel visual dashboard containing time-series ratios, factor radar charts, fundamental scoring bars, and scenario-based heatmaps.

Backsolve Miner/Metal Ratio Fundamentals

Name: Backsolve Miner/Metal Ratio Fundamentals
Author: fatfingererr

byfatfingererr

데이터 과학 및 ML

Decomposes mining stock-to-metal price ratios into fundamental drivers like AISC, leverage, and valuation multiples using automated financial data extraction.

소개

This skill provides a quantitative framework for analyzing the valuation gap between mining companies and their underlying physical metals. By automatically scraping financial reports from SEC EDGAR and SEDAR+, it extracts key metrics—All-In Sustaining Costs (AISC), net debt, EV/EBITDA multiples, and share dilution—to perform a four-factor decomposition of the 'Miner/Metal Ratio.' It is particularly useful for macro analysts and investors seeking to determine if a mining stock's underperformance is due to fundamental cost pressures, leverage issues, or broader market sentiment, providing actionable 'backsolve' targets for recovery scenarios.

주요 기능

Four-factor ratio decomposition (Multiple, Leverage, Cost, Dilution)
Backsolve logic to identify fundamental requirements for target price ratios
Visual dashboard generation including factor radars and scenario heatmaps
0 GitHub stars
Historical event studies to analyze drivers of market bottoms and peaks
Automated extraction of AISC and operational data from SEC XBRL and PDF filings

사용 사례

Analyzing whether the SIL/Silver ratio is at a fundamentally justified bottom
Simulating mining stock upside potential based on specific metal price targets
Benchmarking cost and leverage improvements needed to reach historical valuation multiples

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add fatfingererr/macro-skills backsolve-miner-vs-metal-ratio-with-fundamentals

For use in Claude.ai and ChatGPT

Download Skill

GitHub

소개