quant
CommunityPrediction markets & binary contracts.
Data & Analytics#monte carlo#prediction markets#agent-based modeling#binary contracts#importance sampling#particle filter#copulas
Authoreliza420ai-beep
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides a comprehensive quantitative framework for understanding and simulating prediction markets and binary contracts, moving beyond simple price-as-probability assumptions.
Core Features & Use Cases
- Probabilistic Modeling: Simulates binary contracts using Monte Carlo, importance sampling for rare events, and particle filters for real-time updates.
- Correlation & Risk: Analyzes correlated outcomes using copulas and models market dynamics with agent-based simulations.
- Use Case: Model the probability of a specific political outcome by simulating correlated state-level predictions using a t-copula, and then update these probabilities in real-time as new polling data becomes available using a particle filter.
Quick Start
Use the quant skill to simulate a binary contract for AAPL with a strike of $200.
Dependency Matrix
Required Modules
numpyscipypytest
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: quant Download link: https://github.com/eliza420ai-beep/vince/archive/main.zip#quant Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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