dcf-model

Name: dcf-model
Availability: InStock
Author: brittaniebuffiecsu

Create and analyze DCF valuation models with sensitivity analysis.

1|Updated Feb 17, 2026

Search Tags:#financial modeling #valuation #DCF #investment banking #equity analysis

Ready to run

npx skills add https://github.com/brittaniebuffiecsu/zerogravityclaw --skill dcf-model-brittaniebuffiecsu

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dcf-model
Source: https://github.com/brittaniebuffiecsu/zerogravityclaw/tree/main/src/hermes-core/optional-skills/finance/dcf-model
Command: npx skills add https://github.com/brittaniebuffiecsu/zerogravityclaw --skill dcf-model-brittaniebuffiecsu

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openpyxl, python-decouple, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the process of building and analyzing DCF (Discounted Cash Flow) valuation models, providing a streamlined approach to equity analysis and investment banking standards.

Core Features & Use Cases

DCF Model Creation: Build institutional-quality DCF models following investment banking standards.
Data Validation: Validates and retrieves financial data from various sources.
Scenario Analysis: Supports Bear, Base, and Bull case scenarios with sensitivity analysis.
Use Case: Utilize this Skill to create a DCF model for a company, incorporating historical financials, revenue projections, and WACC calculations, to determine its intrinsic value.

Quick Start

Run the dcf-model skill with the required parameters, such as company identifier and growth assumptions.

Frequently Asked Questions about dcf-model

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

FAQPage Schema

How do I build a DCF valuation model for equity analysis?▼

To build a DCF valuation model, you automate revenue projections, WACC calculations, and intrinsic value determination by passing a company identifier and growth assumptions into the workflow. This streamlines equity analysis by handling data retrieval, validation, and sensitivity analysis.

What is the best way to run sensitivity analysis for multiple DCF scenarios?▼

The best way to run sensitivity analysis for DCF scenarios is to use automated scenario modeling that evaluates Bear, Base, and Bull cases. This approach processes historical financials and growth assumptions to test valuation resilience across different market conditions.

Do I need openpyxl and python-decouple to automate investment banking financial models?▼

Yes, you need openpyxl and python-decouple to automate investment banking financial models. Openpyxl handles Excel operations for model outputs, while python-decouple manages configuration for data retrieval and validation workflows.

Can I calculate the cost of capital and revenue projections automatically for equity research?▼

You can calculate the cost of capital and revenue projections automatically for equity research by utilizing an automated DCF workflow. It processes historical financials to generate institutional-quality revenue forecasts and WACC calculations.

How does data validation work when creating DCF models from various financial data sources?▼

Data validation for DCF models works by automatically retrieving and verifying financial data from various sources before processing. This ensures historical financials and growth assumptions meet investment banking standards before revenue projection and valuation calculations occur.