What is 'Scenario Math' in this context?

It is a calculation that determines the exact percentage move required for a mining stock to reach a target historical ratio (like the median or top) assuming the metal price remains unchanged, and vice versa.

Can I use this for other metals like Gold?

While configured for silver, the underlying methodology and scripts can be adapted by changing the miner and metal proxy tickers to gold equivalents like GDX and GC=F.

Does a 'bottom' ratio signal always mean silver prices will rise?

Not necessarily. A low ratio indicates miners are cheap relative to the metal. This could lead to a 'catch-up' rally in stocks, or it could reflect fundamental risks like rising production costs or equity dilution.

What data sources does this skill use?

The skill uses the yfinance library to retrieve historical and real-time data for silver mining ETFs (like SIL or SILJ) and silver price proxies (like SI=F or SLV).

Silver Miner Metal Ratio Analyzer

Name: Silver Miner Metal Ratio Analyzer
Author: fatfingererr

byfatfingererr

Data Science & ML

Analyzes the relative valuation of silver mining stocks against spot silver prices using historical quantiles and scenario modeling.

About

The Silver Miner Metal Ratio Analyzer is a specialized macro-analysis tool designed to measure the valuation gap between silver mining equities (e.g., SIL, SILJ) and the silver metal itself. By calculating the ratio of miner prices to metal prices and mapping them against historical percentiles, the skill identifies periods where mining stocks are statistically overvalued or undervalued. It provides quantitative scenario planning to determine the price movement required for mean reversion and performs backtests on forward returns following historical valuation extremes, helping analysts identify market divergences and potential turning points.

Key Features

Historical quantile ranking to categorize valuations into bottom, low, neutral, high, and top zones.
Comprehensive backtesting of forward 1, 2, and 3-year returns following historical valuation bottoms.
Automated calculation of the Miner-to-Metal ratio using live market data via yfinance.
Divergence signal detection to identify when miner performance lags or leads metal price action.
0 GitHub stars
Quantitative scenario modeling to calculate price targets for miners or metal based on historical ratios.

Use Cases

Identifying oversold opportunities in silver mining ETFs when the ratio hits historical 20% quantiles.
Validating macro investment themes by cross-referencing metal price trends with equity valuation extremes.
Calculating the 'catch-up' potential for mining stocks if silver prices remain stable at current highs.

About

Key Features

Historical quantile ranking to categorize valuations into bottom, low, neutral, high, and top zones.
Comprehensive backtesting of forward 1, 2, and 3-year returns following historical valuation bottoms.
Automated calculation of the Miner-to-Metal ratio using live market data via yfinance.
Divergence signal detection to identify when miner performance lags or leads metal price action.
0 GitHub stars
Quantitative scenario modeling to calculate price targets for miners or metal based on historical ratios.

Use Cases

Identifying oversold opportunities in silver mining ETFs when the ratio hits historical 20% quantiles.
Validating macro investment themes by cross-referencing metal price trends with equity valuation extremes.
Calculating the 'catch-up' potential for mining stocks if silver prices remain stable at current highs.