volatility-modeling
CommunityModel and forecast market volatility.
AuthorJoelLewis
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps users understand, model, and forecast market volatility, which is crucial for risk management, options pricing, and trading strategy development.
Core Features & Use Cases
- Volatility Modeling: Implement EWMA and GARCH(1,1) models to capture volatility clustering and mean reversion.
- Implied Volatility: Extract and interpret implied volatility from option prices.
- Volatility Surface Analysis: Understand volatility smiles, skews, and term structures.
- Use Case: A portfolio manager needs to assess the risk of a new options strategy. They can use this Skill to analyze the current implied volatility surface and forecast future volatility using GARCH models to determine potential downside risk.
Quick Start
Use the volatility-modeling skill to forecast the next 30 days of volatility using the GARCH(1,1) model with the provided historical return data.
Dependency Matrix
Required Modules
numpyscipy
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: volatility-modeling Download link: https://github.com/JoelLewis/finance_skills/archive/main.zip#volatility-modeling Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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