comps-analysis

Generate comparable company analysis reports in Excel using openpyxl.

Updated May 9, 2026

Search Tags:#Excel #financial analysis #valuation #investment banking #comparable company analysis

Ready to run

npx skills add https://github.com/robertbr123/Linket-Agent --skill comps-analysis-robertbr123

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: comps-analysis
Source: https://github.com/robertbr123/Linket-Agent/tree/main/optional-skills/finance/comps-analysis
Command: npx skills add https://github.com/robertbr123/Linket-Agent --skill comps-analysis-robertbr123

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openpyxl, pandas, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the creation of institutional-grade comparable company analyses in Excel, significantly reducing the manual work involved in financial analysis.

Core Features & Use Cases

Comparable Company Analysis: Build comprehensive analysis reports with operating metrics, valuation multiples, and statistical benchmarking.
Excel Integration: Output structured Excel/spreadsheet files for detailed investment decisions.
Use Case: Ideal for investment professionals seeking to conduct public-company valuation, IPO pricing, or sector benchmarking quickly and efficiently.

Quick Start

Use the 'comps-analysis' skill to generate a comparable company analysis for the companies [Company1, Company2, Company3] using the most recent financial data.

Frequently Asked Questions about comps-analysis

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

FAQPage Schema

How do I automate comparable company analysis in Excel?▼

You can automate comparable company analysis in Excel by using Python with openpyxl and pandas to pull institutional financial data and generate structured reports containing operating metrics, valuation multiples, and statistical benchmarking.

What financial data sources work with comparable company analysis automation?▼

Comparable company analysis automation works with S&P Kensho MCP, FactSet MCP, Daloopa MCP, Bloomberg, and SEC EDGAR, extracting financial data from these institutional sources to populate Excel valuation models.

Can I use Python and pandas to build valuation multiples for investment banking?▼

Yes, you can use Python and pandas to build valuation multiples for investment banking by processing financial data and leveraging openpyxl to format the output into structured Excel spreadsheets for detailed analysis.

Do I need openpyxl to generate Excel financial analysis reports?▼

Yes, you need openpyxl along with pandas to generate Excel financial analysis reports, as these Python libraries handle the spreadsheet processing and formatting required for structuring operating metrics and statistical benchmarking.

What is the best way to benchmark public companies for IPO pricing?▼

The best way to benchmark public companies for IPO pricing is automating comparable company analysis, which calculates operating metrics and valuation multiples across peer groups and outputs statistical benchmarking directly into Excel.

Does comparable company analysis handle statistical benchmarking for sector analysis?▼

Yes, comparable company analysis handles statistical benchmarking for sector analysis by calculating operating metrics and valuation multiples across peer companies and formatting the benchmarking results into structured Excel reports.