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Dcf Model

Community
fivetaku
dcf-model

Real DCF (Discounted Cash Flow) model creation for equity valuation. Retrieves financial data from SEC filings and analyst reports, builds comprehensive cash flow projections with proper WACC calculations, performs sensitivity analysis, and outputs professional Excel models with executive summaries. Use when users need to value a company using DCF methodology, request intrinsic value analysis, or ask for detailed financial modeling with growth projections and terminal value calculations.

Overview

Publisherfivetaku
Repositoryclaude-office-skills
Skill namedcf-model
Stars
72
Forks
11
Bundled files
2
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by fivetaku on GitHub. Read the source before you install it.

Installation

Install the Dcf Model AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/fivetaku/claude-office-skills/tree/main/claude-in-excel/dcf-model
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/fivetaku/claude-office-skills.git /tmp/claude-office-skills
mkdir -p .claude/skills
cp -r /tmp/claude-office-skills/claude-in-excel/dcf-model .claude/skills/dcf-model
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dcf Model in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Dcf Model on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Dcf Model is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

DCF Model Builder

Overview

Institutional-quality DCF models for equity valuation following investment banking standards. Each analysis produces a detailed Excel model (with sensitivity analysis at bottom of DCF sheet).

Preflight: Dependency Check

Before starting, verify required libraries and tools are installed and install any that are missing.

bash
python3 -c "import openpyxl" 2>/dev/null || python3 -m pip install openpyxl
command -v soffice >/dev/null 2>&1 || command -v libreoffice >/dev/null 2>&1 || ls /Applications/LibreOffice.app/Contents/MacOS/soffice >/dev/null 2>&1 || echo "WARNING: LibreOffice not found. Install: brew install --cask libreoffice (macOS) or apt install libreoffice (Linux). Required for scripts/recalc.py."

Important: Do not skip this step — scripts/recalc.py and scripts/validate_dcf.py need these tools to verify sensitivity tables and TV-as-%-of-EV sanity checks.

Scripts

  • scripts/recalc.py — Force formula recalculation via headless LibreOffice. Run after building: python scripts/recalc.py <model.xlsx>
  • scripts/validate_dcf.py — DCF-specific validation (terminal growth < WACC, WACC in 5-20% range, TV as 40-80% of EV, formula errors). Run after recalc: python scripts/validate_dcf.py <model.xlsx>

Tools

  • Default to using all information provided by the user and MCP servers available for data sourcing.

Critical Constraints - Read These First

Environment: Office JS vs Python/openpyxl

  • Office JS: Use range.formulas = [["=D19*(1+$B$8)"]] — never range.values for derived cells
  • Python/openpyxl: Write ws["D15"] = "=D14*(1+Assumptions!$B$5)", then run recalc.py
  • Office JS merged cell pitfall: Write value to top-left cell alone, then merge + format

Formulas Over Hardcodes (NON-NEGOTIABLE)

  • Every projection/margin/discount factor/PV/sensitivity cell MUST be live Excel formula
  • Only permitted hardcodes: (1) raw historical inputs, (2) assumption drivers, (3) current market data
  • "If you catch yourself computing something in Python and writing the result — STOP"

Verify Step-by-Step With the User (DO NOT build end-to-end)

  1. After data retrieval → confirm raw inputs
  2. After revenue projections → confirm top line + growth rates
  3. After FCF build → confirm FCF schedule logic
  4. After WACC → confirm calculation + inputs
  5. After terminal value + PV → confirm equity bridge
  6. After sensitivity tables → final review

Sensitivity Tables

  • Use ODD number of rows/columns (5×5 or 7×7)
  • Center cell = base case (must equal model's actual implied share price)
  • Highlight center cell with #BDD7EE + bold
  • Populate ALL cells with full DCF recalculation formulas (75 total for 3 tables)
  • NO placeholder text, NO linear approximations

Cell Comments

  • Add AS each hardcoded value is created
  • Format: "Source: [System/Document], [Date], [Reference], [URL]"
  • Never defer to end or write "TODO: add source"

Model Layout Planning

  • Define ALL section row positions BEFORE writing formulas
  • Write ALL headers → section dividers → THEN formulas

DCF Process Workflow

Step 1: Data Retrieval and Validation

  • Priority: MCP Servers → User-Provided Data → Web Search/Fetch
  • Validation: net debt vs net cash, diluted shares, historical margins, growth rates, tax rate

Step 2: Historical Analysis (3-5 years)

  • Revenue growth trends (CAGR), margin progression, capital intensity, WC efficiency, return metrics

Step 3: Build Revenue Projections

  • Revenue(Year N) = Revenue(Year N-1) × (1 + Growth Rate)
  • Three-scenario approach: Bear/Base/Bull
  • Growth rates: Year 1-2 higher → Year 3-4 moderate → Year 5+ approaching terminal

Step 4: Operating Expense Modeling

  • S&M, R&D, G&A — ALL percentages based on REVENUE, not gross profit
  • Model operating leverage: % should decline as revenue scales

Step 5: Free Cash Flow Calculation

  • EBIT → (-)Taxes → NOPAT → (+)D&A → (-)CapEx → (-)ΔNWC → Unlevered FCF

Step 6: Cost of Capital (WACC) Research

  • CAPM: Cost of Equity = Risk-Free Rate + Beta × ERP
  • After-Tax Cost of Debt = Pre-Tax × (1 - Tax Rate)
  • WACC = (Ke × We) + (Kd × Wd)

Step 7: Discount Rate Application

  • Mid-year convention: periods 0.5, 1.5, 2.5...
  • Discount Factor = 1 / (1 + WACC)^Period

Step 8: Terminal Value Calculation

  • Perpetuity Growth: TV = Terminal FCF / (WACC - g)
  • Exit Multiple: TV = Final Year EBITDA × Exit Multiple
  • Sanity check: TV should be 50-70% of EV

Step 9: Enterprise to Equity Value Bridge

  • Sum PV FCFs + PV Terminal Value = EV
  • EV - Net Debt = Equity Value
  • Equity Value / Diluted Shares = Implied Price per Share

Step 10: Sensitivity Analysis

Three tables: (1) WACC vs Terminal Growth, (2) Revenue Growth vs EBIT Margin, (3) Beta vs Risk-Free Rate

<correct_patterns> section

  • Scenario Block Selection: INDEX/consolidation column approach (not scattered IF statements)
  • Revenue Projection: Reference consolidation column
  • FCF Formula: Use consolidation columns with INDEX
  • Cell Comment Format: exact source with date/URL
  • Assumption Table Structure: 3 elements per block (header + column headers + data rows)
  • Row Planning Process: headers first → dividers → formulas
  • Sensitivity Table: 5×5 grid, symmetric axes, center = base case, formula in every cell

<common_mistakes> section

  • WRONG: Linear approximations in sensitivity tables
  • WRONG: Placeholder text instead of formulas
  • WRONG: Missing cell comments
  • WRONG: Formula row references off (write formulas before headers)
  • WRONG: Single row per assumption across scenarios
  • WRONG: No borders
  • WRONG: Wrong font colors
  • WRONG: OpEx based on Gross Profit instead of Revenue
  • TOP 5 ERRORS: row references, comments, sensitivity, scenario references, borders

Excel Model Structure

Sheet Architecture: 2 sheets — DCF + WACC

Formatting Standards

  • Font Colors: Blue=#0000FF (inputs), Black (formulas), Green=#008000 (cross-sheet)
  • Fill Colors: Dark blue #1F4E79 (headers), Light blue #D9E1F2 (sub-headers), Light grey #F2F2F2 (inputs), White (formulas), Medium blue #BDD7EE (outputs)
  • Borders: Thick 1.5pt (major sections), Medium 1pt (sub-sections), Thin 0.5pt (data tables)
  • Number Formats: Years as text, % as 0.0%, Currency $#,##0, Negatives in parentheses

DCF Sheet Detailed Structure (Sections 1-5 + Sensitivity)

[Detailed row-by-row layout with formula patterns]

(-) Δ NWC,(XX),(XX),(XX),(XX),[=(E29-D29)$E$23],[=(F29-E29)$E$23],[=(G29-F29)*$E$23] % of ΔRev,XX%,XX%,XX%,XX%,[=$E$23],[=$E$23],[=$E$23] ,,,,,, Unlevered FCF,XXX,XXX,XXX,XXX,[=E57+E58-E60-E62],[=F57+F58-F60-F62],[=G57+G58-G60-G62] FCF Margin,XX%,XX%,XX%,XX%,[=E64/E29],[=F64/F29],[=G64/G29] Key Formula Pattern (FCF):

NOPAT = EBIT - Taxes: =E45 (+) D&A: =E29*$E$21 (consolidation column for D&A %) (-) CapEx: =E29*$E$22 (consolidation column for CapEx %) (-) Δ NWC: =(E29-D29)*$E$23 (consolidation column for NWC %) Unlevered FCF: =E57+E58-E60-E62 (NOPAT + D&A - CapEx - ΔNWC) Section 6: Discount Factors & Present Value

Section 6: Discount Rate & Present Value

Discount Period,,,,,0.5,1.5,2.5,3.5,4.5 Discount Factor,,,,,=[=1/(1+$E$25)^E67],[=1/(1+$E$25)^F67],[=1/(1+$E$25)^G67],[=1/(1+$E$25)^H67],[=1/(1+$E$25)^I67] PV of FCF,,,,,=[=E64E68],[=F64F68],[=G64G68],[=H64H68],[=I64*I68] Formula Structure:

Discount Period: 0.5, 1.5, 2.5, 3.5, 4.5 (mid-year convention) WACC reference: $E$25 = consolidation column pulling from scenario block via INDEX Discount Factor: =1/(1+$E$25)^[Period] PV of FCF: =[Unlevered FCF]*[Discount Factor] Sum of PV FCFs: =SUM(E69:I69) Section 7: Terminal Value

Section 7: Terminal Value Calculation

Terminal Value Section: Final Year FCF (Year 5),[=I64] Terminal Growth Rate,[=$E$24] (consolidation column) Terminal FCF,[=I64*(1+$E$24)]

Perpetuity Growth Method: Terminal Value,[=E74/($E$25-$E$24)] TV as % of EV,[=E75/E82] (sanity check: should be 50-70%)

Exit Multiple Method: Final Year EBITDA,[=I41] (Year 5 EBIT + D&A, or direct EBITDA) Exit Multiple,[from assumptions] Terminal Value (Exit),[=E78*E79]

PV of Terminal Value: Discount Factor (final period),[=1/(1+$E$25)^4.5] PV Terminal Value (Perpetuity),[=E75E81] PV Terminal Value (Exit),[=E80E81] Terminal Value Sanity Check:

TV as % of EV should be 50-70% If >75%: over-reliant on terminal assumptions If <40%: terminal assumptions may be too conservative Section 8: Valuation Summary

Section 8: Enterprise to Equity Value Bridge

VALUATION SUMMARY: (+) Sum of PV of Projected FCFs,[=SUM(E69:I69)] (+) PV of Terminal Value (Perpetuity),[=E82] (=) Enterprise Value (Perpetuity),[=E85+E86]

(+) PV of Terminal Value (Exit Multiple),[=E83] (=) Enterprise Value (Exit Multiple),[=E85+E89]

(-) Net Debt,[=$B$[net_debt_row]] (from Market Data section, blue input) (=) Equity Value (Perpetuity),[=E87-E91] (=) Equity Value (Exit Multiple),[=E90-E91]

(÷) Diluted Shares Outstanding (M),[=$B$[shares_row]] (from Market Data section) (=) Implied Price per Share (Perpetuity),[=E92/E94] (=) Implied Price per Share (Exit Multiple),[=E93/E94]

Current Stock Price,[=$B$[price_row]] (blue input) Implied Upside/(Downside) (Perpetuity),[=E95/E97-1] Implied Upside/(Downside) (Exit Multiple),[=E96/E97-1] Output Formatting:

Key output rows (EV, Equity Value, Implied Price): Medium blue fill #BDD7EE, bold Net Debt/Shares/Current Price: Blue font (hardcoded inputs) All calculated values: Black font Sensitivity Tables (Bottom of DCF Sheet)

Sensitivity Analysis — Three Tables

TABLE 1: WACC vs Terminal Growth Rate → Implied Share Price (Perpetuity)

  • Row headers: WACC values [base-2Δ, base-Δ, base, base+Δ, base+2Δ] (e.g., 8.0%, 8.5%, 9.0%, 9.5%, 10.0%)
  • Column headers: Terminal growth [base-2Δ, base-Δ, base, base+Δ, base+2Δ] (e.g., 2.0%, 2.5%, 3.0%, 3.5%, 4.0%)
  • Each cell formula recalculates: Sum PV FCFs (using row WACC) + PV TV (using col growth & row WACC) - Net Debt / Shares
  • Center cell = base case implied price, highlighted #BDD7EE + bold

TABLE 2: Revenue Growth vs EBIT Margin → Implied Share Price

  • Row headers: Revenue growth rates (Year 1)
  • Column headers: EBIT margins
  • Each cell recalculates full DCF with substituted assumptions

TABLE 3: Beta vs Risk-Free Rate → Implied Share Price

  • Row headers: Beta values
  • Column headers: Risk-free rate values
  • Each cell recalculates WACC → full DCF Implementation (programmatic loop):

Pseudocode for all 3 tables × 5×5 = 75 cells

wacc_range = [base_wacc - 0.01, base_wacc - 0.005, base_wacc, base_wacc + 0.005, base_wacc + 0.01] tg_range = [base_tg - 0.01, base_tg - 0.005, base_tg, base_tg + 0.005, base_tg + 0.01]

for r, wacc in enumerate(wacc_range): for c, tg in enumerate(tg_range): # Formula references row header ($A$row) for WACC, column header (col$header_row) for TG formula = "=(<sum_pv_fcfs_using_$A${row}as_wacc> + <tv_using{col}${header}as_growth_and$A${row}_as_wacc> - <net_debt>) / " ws.cell(row=start_row+r, column=start_col+c).value = formula WACC Sheet Structure

WACC Sheet Layout

Section 1: Cost of Equity (CAPM) Risk-Free Rate (10Y Treasury),[blue input, with source comment] Equity Risk Premium,[blue input, typically 5.0-6.0%] Beta (5-year monthly),[blue input, with source comment] Cost of Equity,[formula: =Risk_Free + Beta × ERP]

Section 2: Cost of Debt Pre-Tax Cost of Debt,[blue input or =Interest Expense / Total Debt] Tax Rate,[blue input] After-Tax Cost of Debt,[formula: =Pre_Tax × (1 - Tax_Rate)]

Section 3: Capital Structure Current Share Price,[blue input] Diluted Shares Outstanding,[blue input] Market Cap,[formula: =Price × Shares] Total Debt,[blue input] Cash & Equivalents,[blue input] Net Debt,[formula: =Total Debt - Cash] Enterprise Value,[formula: =Market Cap + Net Debt]

Equity Weight,[formula: =Market Cap / EV] Debt Weight,[formula: =Net Debt / EV]

Section 4: WACC Calculation WACC,[formula: =(Cost_of_Equity × Equity_Weight) + (After_Tax_Cost_of_Debt × Debt_Weight)] Formatting:

All inputs: Blue font #0000FF with cell comments All formulas: Black font Cross-sheet references from DCF sheet: Green font #008000 Section headers: Dark blue fill #1F4E79, white text WACC output: Medium blue fill #BDD7EE, bold Special Cases:

Net Cash Position (Cash > Debt): Net Debt is negative, Debt Weight may be negative, WACC adjusts accordingly No Debt: WACC = Cost of Equity Quality Rubric (Full)

Quality Rubric

Every DCF model must maximize for:

  1. Realistic revenue and margin assumptions based on historical performance
    • Growth rates justified by industry trends and company-specific drivers
    • Margin progression consistent with scale economics
  2. Appropriate cost of capital calculation with proper CAPM methodology
    • Risk-free rate = current 10Y Treasury
    • Beta from reliable source (5-year monthly)
    • ERP within standard range (5.0-6.0%)
  3. Comprehensive sensitivity analysis showing valuation ranges
    • Three 5×5 tables, all 75 cells with live formulas
    • Center cell = base case, highlighted
  4. Clear terminal value calculation with supporting rationale
    • Both perpetuity and exit multiple methods
    • TV as % of EV sanity check
  5. Professional model structure enabling scenario analysis
    • Bear/Base/Bull with consolidation columns
    • Clean cell references, no scattered IF statements
  6. Transparent documentation of all key assumptions
    • Cell comments on every hardcoded input
    • Source citations with dates and URLs

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Dcf Model AI skill do?

Real DCF (Discounted Cash Flow) model creation for equity valuation. Retrieves financial data from SEC filings and analyst reports, builds comprehensive cash flow projections with proper WACC calculations, performs sensitivity analysis, and outputs professional Excel models with executive summaries. Use when users need to value a company using DCF methodology, request intrinsic value analysis, or ask for detailed financial modeling with growth projections and terminal value calculations.

Why use Dcf Model on TypingMind?

Because you install it once and use it with any model. Dcf Model is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Dcf Model in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/fivetaku/claude-office-skills/tree/main/claude-in-excel/dcf-model. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Dcf Model?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Dcf Model?

As many as you like. As long as a model supports skills, you can use Dcf Model with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Dcf Model AI skill free?

It is published on GitHub by fivetaku. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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