portfolio-final-selection

Select the optimal portfolio version using predefined evaluation metrics and update metadata.

33|2|Updated May 13, 2026
One-click install
npx skills add https://github.com/adennng/stock_strategy_lab --skill portfolio-final-selection
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: portfolio-final-selection
Source: https://github.com/adennng/stock_strategy_lab/tree/main/src/strategy_lab/skills/portfolio_agent/portfolio-final-selection
Command: npx skills add https://github.com/adennng/stock_strategy_lab --skill portfolio-final-selection

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automatically selects the final version of a portfolio from a set of evaluated ones, ensuring consistency in the selection process and reducing manual errors.

Core Features & Use Cases

  • Automatic Selection: Identifies and selects the final version of a portfolio based on pre-defined evaluation metrics.
  • Documentation & Metadata: Generates and updates documentation and metadata related to the final portfolio selection.
  • Use Case: Imagine you have multiple evaluated portfolio versions after an extensive evaluation period. Use this Skill to automatically determine which one to proceed with, based on predefined criteria like Sharpe ratio, maximum drawdown, and risk-adjusted returns.

Quick Start

Execute the 'portfolio final-select' command with the path to the portfolio run state and the version ID to be marked as final, e.g., 'python -m strategy_lab.cli portfolio final-select artifacts\portfolio_runs\portfolio_xxx\portfolio_run_state.json v003_soft_budget_cap'.

Frequently Asked Questions about portfolio-final-selection

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automatically select the best portfolio version from multiple evaluated runs?

You can automate portfolio selection by executing a command with the path to your portfolio run state JSON file and the target version ID. This identifies the optimal portfolio version based on predefined evaluation metrics and updates the metadata accordingly.

What evaluation metrics are used for quantitative finance portfolio selection?

Quantitative portfolio selection uses predefined evaluation metrics like Sharpe ratio, maximum drawdown, and risk-adjusted returns. These criteria ensure consistency in selecting the final portfolio version from multiple evaluated options during financial analytics workflows.

How do I update portfolio metadata after finalizing a selected version?

Portfolio metadata is updated automatically when you execute the final selection command with the run state path and version ID. The process generates and updates documentation to reflect the selected final portfolio version, ensuring accurate records.

Can I use automated portfolio selection for quantitative finance workflows with multiple evaluated versions?

Automated portfolio selection suits quantitative finance workflows requiring consistency across multiple evaluated versions. It processes portfolio run state files to determine the final version based on predefined performance metrics, reducing manual evaluation errors.

What is the process for marking a specific portfolio version as final?

Marking a portfolio version as final requires executing a command line instruction with the portfolio run state JSON path and the target version ID. This applies predefined evaluation criteria to validate the selection and updates the portfolio metadata accordingly.