Build end-to-end DCF valuation models with scenario analysis and Excel outputs.
npx skills add https://github.com/ginlix-ai/LangAlpha --skill dcf-model
Please help me install this Agent Skill. Skill: dcf-model Source: https://github.com/ginlix-ai/LangAlpha/tree/main/skills/dcf-model Command: npx skills add https://github.com/ginlix-ai/LangAlpha --skill dcf-model
Automates the construction of robust DCF valuation models, standardizing inputs, calculations, and outputs to support consistent equity analyses.
Create a new DCF workbook for your target and input your historicals to generate projected FCF and valuation results.
High-intent search queries and answers about installing and using this skill.
DCF valuation models with scenario analysis are built by standardizing centralized assumptions for Bear/Base/Bull cases, projecting 5-year revenues, margins, and FCF, and populating Excel formulas via OpenPyXL to generate an auditable workbook with WACC estimation, terminal value, and sensitivity analysis.
Automating WACC estimation and terminal value calculations involves creating a scalable workbook with centralized assumptions and data validation. The process populates 5-year projections using OpenPyXL formulas and runs a recalc script to validate outputs, ensuring consistent equity analysis for investment bankers and portfolio managers.
Yes, sensitivity analysis across Bear, Base, and Bull scenarios is generated for 5-year financial projections by consolidating centralized assumptions into a scalable workbook. The model auto-generates sensitivity outputs aligned to corporate finance standards, validating projected FCF and valuation results through a recalc script.
Automated DCF modeling requires historical financial data inputs to project free cash flow accurately. You input historicals for revenue, margins, tax, D&A, CapEx, and NWC into the generated workbook to calculate 5-year projected FCF and terminal value for investment decisions.
OpenPyXL formula population creates auditable financial modeling workbooks by programmatically writing calculation formulas directly into Excel cells for 5-year projections. This ensures proper forecasting structure and alignment with investment banking practices, followed by a recalc script to validate the populated valuation outputs.
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