advanced-math-trading/foundations-core
Probability, moments/tails, Bayes, and statistical learning foundations for systematic trading.
Best use case
advanced-math-trading/foundations-core is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Probability, moments/tails, Bayes, and statistical learning foundations for systematic trading.
Teams using advanced-math-trading/foundations-core should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/advanced-math-trading-foundations-core/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How advanced-math-trading/foundations-core Compares
| Feature / Agent | advanced-math-trading/foundations-core | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Probability, moments/tails, Bayes, and statistical learning foundations for systematic trading.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# What this covers - Probability spaces, random variables, moments, tail risk, Bayes updates. - Core statistical learning basics and regularization. # Navigation (load on demand) - docs/knowledge-base/domains/foundations/advanced-mathematics/Algorithmic Foundations for Systematic Trading.md — probability, moments, tail risk, Bayes code. - docs/knowledge-base/domains/foundations/advanced-mathematics/statistical-foundations.md — stats core. - docs/knowledge-base/domains/foundations/advanced-mathematics/probability-and-stochastic-processes.md — probability + processes overview. - docs/knowledge-base/domains/foundations/advanced-mathematics/probability-spaces-and-random-variables.md — formal definitions. - docs/knowledge-base/domains/foundations/advanced-mathematics/statistical-learning.md — learning basics. - docs/knowledge-base/domains/foundations/advanced-mathematics/regularization-methods.md — regularization patterns. # Quick workflows - Tail metrics: lift VaR/ES/Hill estimators from Algorithmic Foundations. - Bayesian updates: use conditional-probability code for regime/parameter updates. - When in doubt, start with Algorithmic Foundations then pull topic-specific MDs above. # Notes - Load only the files needed; avoid bulk-loading the whole directory.
Related Skills
kimmo-agent-friendly-score
Score developer tools and SaaS products for AI agent compatibility. Use when evaluating how well a devtool works with AI coding assistants, or when optimizing a product for the agent era.
hive-mind-advanced
Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory
corearena-classes-rewards
Troubleshooting class selection, tier upgrades, experience, and nugget economy
agent-roles-core
Core agent role definitions and responsibilities used across repositories.
Advanced Testability Ai Ergonomic
Design code for testability and AI/LLM ergonomics with explicit contracts and observable patterns. Use when optimizing code for AI tools, improving testability, or making codebases LLM-friendly.
advanced-statusline
Implement AI-powered statusline with session tracking, plan detection, workspace emojis, and intelligent caching for Claude Code
advanced-rendering
Master high-performance rendering for large datasets with Datashader. Use this skill when working with datasets exceeding 100M+ points, optimizing visualization performance, or implementing efficient rendering strategies with rasterization and colormapping techniques.
advanced-math-trading/portfolio-factors
Factor modeling and portfolio construction (Markowitz, Black-Litterman, constraints, turnover).
advanced-file-management
Advanced file management tools. Includes batch folder creation, batch file moving, file listing, and HTML author extraction.
advanced-example
Advanced example showing all available metadata fields and complex folder structure
advanced-evaluation
Master LLM-as-a-Judge evaluation techniques including direct scoring, pairwise comparison, rubric generation, and bias mitigation. Use when building evaluation systems, comparing model outputs, or establishing quality standards for AI-generated content.
Advanced Deterministic Runtime Container
Build deterministic IoC containers with proper lifecycle management, scoping, and disposal patterns. Use when implementing DI containers, managing service lifetimes, or designing runtime systems.