advanced-math-trading/portfolio-factors
Factor modeling and portfolio construction (Markowitz, Black-Litterman, constraints, turnover).
Best use case
advanced-math-trading/portfolio-factors is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Factor modeling and portfolio construction (Markowitz, Black-Litterman, constraints, turnover).
Teams using advanced-math-trading/portfolio-factors 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-portfolio-factors/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How advanced-math-trading/portfolio-factors Compares
| Feature / Agent | advanced-math-trading/portfolio-factors | 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?
Factor modeling and portfolio construction (Markowitz, Black-Litterman, constraints, turnover).
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 - Factor models, mean-variance, BL, turnover/constraints, links to advanced optimization examples. # Navigation (load on demand) - docs/knowledge-base/domains/foundations/advanced-mathematics/factor-models.md - docs/knowledge-base/domains/foundations/advanced-mathematics/mean-variance-optimization-markowitz.md - docs/knowledge-base/domains/foundations/advanced-mathematics/black-litterman-model.md - Relevant sections in docs/knowledge-base/domains/foundations/advanced-mathematics/advanced-optimization.md (MOO, MIP). # Quick workflows - Build factor portfolio → factor-models + Markowitz. - BL prior/posterior setup → Black-Litterman MD. - Add cardinality/turnover → reuse MOO/MIP from advanced-optimization. # Notes - Keep loads targeted to the needed construction.
Related Skills
hive-mind-advanced
Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory
analyzing-innovation-portfolio
Analyze the CustomGPT.ai Labs Innovation workbook and cost tracking data to surface portfolio-level insights, trends, and recommendations for where to focus Innovation efforts.
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/foundations-core
Probability, moments/tails, Bayes, and statistical learning foundations for systematic trading.
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.
advanced-analytics
Advanced analytics including machine learning, predictive modeling, and big data techniques
git-advanced-workflows
Master advanced Git workflows including rebasing, cherry-picking, bisect, worktrees, and reflog to maintain clean history and recover from any situation. Use when managing complex Git histories, collaborating on feature branches, or troubleshooting repository issues.