Analyze yfinance options chains to compute put-call ratios, max-pain, and implied volatility metrics.
npx skills add https://github.com/phanijapps/zbot --skill yf-options
Please help me install this Agent Skill. Skill: yf-options Source: https://github.com/phanijapps/zbot/tree/main/gateway/templates/skills/yf-options Command: npx skills add https://github.com/phanijapps/zbot --skill yf-options
Automates the analysis of options chains to quantify volatility structure, liquidity signals, and sentiment, saving time and reducing guesswork for options traders and researchers.
Run yf-options on a target symbol to generate implied-volatility curves, OI-based signals, and a summary report.
High-intent search queries and answers about installing and using this skill.
Analyzing options chains from yfinance measures implied volatility structure by computing put-call ratios, ATM IV by expiry, and term-structure slopes. This quantifies open-interest positioning and directional sentiment across multiple symbols.
Max-pain estimation works by analyzing open-interest distribution across strike prices for a given expiry. It calculates the strike where option writers face the least financial loss, providing a focal point for expiry-by-expiry diagnostics and price magnetism.
Yes, you can calculate put-call volume ratios using yfinance options data by applying numeric cleaning to the downloaded chains. This computes derived metrics that assess liquidity signals and directional sentiment.
Assessing implied-volatility skew using moneyness buckets involves grouping options by strike distance from the underlying price. This expiry-based comparison reveals volatility regime shifts and skew slopes across multiple symbols.
Yes, you need Python with yfinance installed to generate options volatility curves and OI-based signals. The environment processes raw options chains, performs numeric cleaning, and computes derived metrics with optional visual outputs.
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