DCF Model Builder

Overview

This skill creates institutional-quality DCF models for equity valuation following investment banking standards. Each analysis produces a detailed Excel model (with sensitivity analysis included at the bottom of the DCF sheet).

Tools

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

Critical Constraints - Read These First

These constraints apply throughout all DCF model building. Review before starting:

Environment: Office JS vs Python/openpyxl:

• If running inside Excel (Office Add-in / Office JS environment): Use Office JS directly — do NOT use Python/openpyxl. Write formulas via range.formulas = [["=D19*(1+$B$8)"]]. No separate recalc step needed; Excel calculates natively. Use range.format.* for styling. The same formulas-over-hardcodes rule applies: set .formulas, never .values for derived cells.
• If generating a standalone .xlsx file (no live Excel session): Use Python/openpyxl as described below, then run recalc.py before delivery.
• The rest of this skill uses openpyxl examples — translate to Office JS API calls when in that environment, but all principles (formula strings, cell comments, section checkpoints, sensitivity table loops) apply identically.

⚠️ Office JS merged cell pitfall: When building section headers with merged cells, do NOT call .merge() then set .values on the merged range — Office JS still reports the range's original dimensions and will throw InvalidArgument: The number of rows or columns in the input array doesn't match the size or dimensions of the range. Instead, write the value to the top-left cell alone, then merge and format the full range:

// WRONG — throws InvalidArgument:
const hdr = ws.getRange("A7:H7");
hdr.merge();
hdr.values = [["MARKET DATA & KEY INPUTS"]];  // 1×1 array vs 1×8 range → fails

// CORRECT — value first on single cell, then merge + format the range:
ws.getRange("A7").values = [["MARKET DATA & KEY INPUTS"]];
const hdr = ws.getRange("A7:H7");
hdr.merge();
hdr.format.fill.color = "#1F4E79";
hdr.format.font.bold = true;
hdr.format.font.color = "#FFFFFF";

This applies to every merged section header in the DCF (market data, scenario blocks, cash flow projection, terminal value, valuation summary, sensitivity tables).

Formulas Over Hardcodes (NON-NEGOTIABLE):

• Every projection, margin, discount factor, PV, and sensitivity cell MUST be a live Excel formula — never a value computed in Python and written as a number
• When using openpyxl: ws["D20"] = "=D19*(1+$B$8)" is correct; ws["D20"] = calculated_revenue is WRONG
• The only hardcoded numbers permitted are: (1) raw historical inputs, (2) assumption drivers (growth rates, WACC inputs, terminal g), (3) current market data (share price, debt balance)
• If you catch yourself computing something in Python and writing the result — STOP. The model must flex when the user changes an assumption.

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

• After data retrieval → show the user the raw inputs block (revenue, margins, shares, net debt) and confirm before projecting
• After revenue projections → show the projected top line and growth rates, confirm before building margin build
• After FCF build → show the full FCF schedule, confirm logic before computing WACC
• After WACC → show the calculation and inputs, confirm before discounting
• After terminal value + PV → show the equity bridge (EV → equity value → per share), confirm before sensitivity tables
• Catch errors at each stage — a wrong margin assumption discovered after sensitivity tables are built means rebuilding everything downstream

Sensitivity Tables:

• Use an ODD number of rows and columns (standard: 5×5, sometimes 7×7) — this guarantees a true center cell
• Center cell = base case. Build the axis values so the middle row header and middle column header exactly equal the model's actual assumptions (e.g., if base WACC = 9.0%, the middle row is 9.0%; if terminal g = 3.0%, the middle column is 3.0%). The center cell's output must therefore equal the model's actual implied share price — this is the sanity check that the table is built correctly.
• Highlight the center cell with the medium-blue fill (#BDD7EE) + bold font so it's immediately visible which cell is the base case.
• Populate ALL cells (typically 3 tables × 25 cells = 75) with full DCF recalculation formulas
• Use openpyxl loops (or Office JS loops) to write formulas programmatically
• NO placeholder text, NO linear approximations, NO manual steps required
• Each cell must recalculate full DCF for that assumption combination

Cell Comments:

• Add cell comments AS each hardcoded value is created
• Format: "Source: [System/Document], [Date], [Reference], [URL if applicable]"
• Every blue input must have a comment before moving to next section
• Do not defer to end or write "TODO: add source"

Model Layout Planning:

• Define ALL section row positions BEFORE writing any formulas
• Write ALL headers and labels first
• Write ALL section dividers and blank rows second
• THEN write formulas using the locked row positions
• Test formulas immediately after creation

Formula Recalculation:

• Run python recalc.py model.xlsx 30 before delivery
• Fix ALL errors until status is "success"
• Zero formula errors required (#REF!, #DIV/0!, #VALUE!, etc.)

Scenario Blocks:

• Create separate blocks for Bear/Base/Bull cases
• Show assumptions horizontally across projection years within each block
• Use IF formulas: =IF($B$6=1,[Bear cell],IF($B$6=2,[Base cell],[Bull cell]))
• Verify formulas reference correct scenario block cells

DCF Process Workflow

Step 1: Data Retrieval and Validation

Fetch data from MCP servers, user provided data, and the web.

Data Sources Priority:

1. MCP Servers (if configured) - Structured financial data from providers like Daloopa
2. User-Provided Data - Historical financials from their research
3. Web Search/Fetch - Current prices, beta, debt and cash when needed

Validation Checklist:

• Verify net debt vs net cash (critical for valuation)
• Confirm diluted shares outstanding (check for recent buybacks/issuances)
• Validate historical margins are consistent with business model
• Cross-check revenue growth rates with industry benchmarks
• Verify tax rate is reasonable (typically 21-28%)

Step 2: Historical Analysis (3-5 years)

Analyze and document:

• Revenue growth trends: Calculate CAGR, identify drivers
• Margin progression: Track gross margin, EBIT margin, FCF margin
• Capital intensity: D&A and CapEx as % of revenue
• Working capital efficiency: NWC changes as % of revenue growth
• Return metrics: ROIC, ROE trends

Create summary tables showing:

Historical Metrics (LTM):
Revenue: $X million
Revenue growth: X% CAGR
Gross margin: X%
EBIT margin: X%
D&A % of revenue: X%
CapEx % of revenue: X%
FCF margin: X%

Step 3: Build Revenue Projections

Methodology:

1. Start with latest actual revenue (LTM or most recent fiscal year)
2. Apply growth rates for each projection year
3. Show both dollar amounts AND calculated growth %

Growth Rate Framework:

• Year 1-2: Higher growth reflecting near-term visibility
• Year 3-4: Gradual moderation toward industry average
• Year 5+: Approaching terminal growth rate

Formula structure:

• Revenue(Year N) = Revenue(Year N-1) × (1 + Growth Rate)
• Growth %(Year N) = Revenue(Year N) / Revenue(Year N-1) - 1

Three-scenario approach:

Bear Case: Conservative growth (e.g., 8-12%)
Base Case: Most likely scenario (e.g., 12-16%)
Bull Case: Optimistic growth (e.g., 16-20%)

Step 4: Operating Expense Modeling

Fixed/Variable Cost Analysis:

Operating expenses should model realistic operating leverage:

• Sales & Marketing: Typically 15-40% of revenue depending on business model
• Research & Development: Typically 10-30% for technology companies
• General & Administrative: Typically 8-15% of revenue, shows leverage as company scales

Key principles:

• ALL percentages based on REVENUE, not gross profit
• Model operating leverage: % should decline as revenue scales
• Maintain separate line items for S&M, R&D, G&A
• Calculate EBIT = Gross Profit - Total OpEx

Margin expansion framework:

Current State → Target State (Year 5)
Gross Margin: X% → Y% (justify based on scale, efficiency)
EBIT Margin: X% → Y% (result of revenue growth + opex leverage)

Step 5: Free Cash Flow Calculation

Build FCF in proper sequence:

EBIT
(-) Taxes (EBIT × Tax Rate)
= NOPAT (Net Operating Profit After Tax)
(+) D&A (non-cash expense, % of revenue)
(-) CapEx (% of revenue, typically 4-8%)
(-) Δ NWC (change in working capital)
= Unlevered Free Cash Flow

Working Capital Modeling:

• Calculate as % of revenue change (delta revenue)
• Typical range: -2% to +2% of revenue change
• Negative number = source of cash (working capital release)
• Positive number = use of cash (working capital build)

Maintenance vs Growth CapEx:

• Maintenance CapEx: Sustains current operations (~2-3% revenue)
• Growth CapEx: Supports expansion (additional 2-5% revenue)
• Total CapEx should align with company's growth strategy

Step 6: Cost of Capital (WACC) Research

CAPM Methodology for Cost of Equity:

Cost of Equity = Risk-Free Rate + Beta × Equity Risk Premium

Where:
- Risk-Free Rate = Current 10-Year Treasury Yield
- Beta = 5-year monthly stock beta vs market index
- Equity Risk Premium = 5.0-6.0% (market standard)

Cost of Debt Calculation:

After-Tax Cost of Debt = Pre-Tax Cost of Debt × (1 - Tax Rate)

Determine Pre-Tax Cost of Debt from:
- Credit rating (if available)
- Current yield on company bonds
- Interest expense / Total Debt from financials

Capital Structure Weights:

Market Value Equity = Current Stock Price × Shares Outstanding
Net Debt = Total Debt - Cash & Equivalents
Enterprise Value = Market Cap + Net Debt

Equity Weight = Market Cap / Enterprise Value
Debt Weight = Net Debt / Enterprise Value

WACC = (Cost of Equity × Equity Weight) + (After-Tax Cost of Debt × Debt Weight)

Special Cases:

• Net Cash Position: If Cash > Debt, Net Debt is NEGATIVE
  • Debt Weight may be negative
  • WACC calculation adjusts accordingly
• No Debt: WACC = Cost of Equity

Typical WACC Ranges:

• Large Cap, Stable: 7-9%
• Growth Companies: 9-12%
• High Growth/Risk: 12-15%

Step 7: Discount Rate Application (5-10 Year Forecast)

Mid-Year Convention:

• Cash flows assumed to occur mid-year
• Discount Period: 0.5, 1.5, 2.5, 3.5, 4.5, etc.
• Discount Factor = 1 / (1 + WACC)^Period

Present Value Calculation:

For each projection year:
PV of FCF = Unlevered FCF × Discount Factor

Example (Year 1):
FCF = $1,000
WACC = 10%
Period = 0.5
Discount Factor = 1 / (1.10)^0.5 = 0.9535
PV = $1,000 × 0.9535 = $954

Projection Period Selection:

• 5 years: Standard for most analyses
• 7-10 years: High growth companies with longer runway
• 3 years: Mature, stable businesses

Step 8: Terminal Value Calculation

Perpetuity Growth Method (Preferred):

Terminal FCF = Final Year FCF × (1 + Terminal Growth Rate)
Terminal Value = Terminal FCF / (WACC - Terminal Growth Rate)

Critical Constraint: Terminal Growth < WACC (otherwise infinite value)

Terminal Growth Rate Selection:

• Conservative: 2.0-2.5% (GDP growth rate)
• Moderate: 2.5-3.5%
• Aggressive: 3.5-5.0% (only for market leaders)

Do not exceed: Risk-free rate or long-term GDP growth

Exit Multiple Method (Alternative):

Terminal Value = Final Year EBITDA × Exit Multiple

Where Exit Multiple comes from:
- Industry comparable trading multiples
- Precedent transaction multiples
- Typical range: 8-15x EBITDA

Present Value of Terminal Value:

PV of Terminal Value = Terminal Value / (1 + WACC)^Final Period

Where Final Period accounts for timing:
5-year model with mid-year convention: Period = 4.5

Terminal Value Sanity Check:

• Should represent 50-70% of Enterprise Value
• If >75%, model may be over-reliant on terminal assumptions
• If <40%, check if terminal assumptions are too conservative

Step 9: Enterprise to Equity Value Bridge

Valuation Summary Structure:

(+) Sum of PV of Projected FCFs = $X million
(+) PV of Terminal Value = $Y million
= Enterprise Value = $Z million

(-) Net Debt [or + Net Cash if negative] = $A million
= Equity Value = $B million

÷ Diluted Shares Outstanding = C million shares
= Implied Price per Share = $XX.XX

Current Stock Price = $YY.YY
Implied Return = (Implied Price / Current Price) - 1 = XX%

Critical Adjustments:

• Net Debt = Total Debt - Cash & Equivalents
  • If positive: Subtract from EV (reduces equity value)
  • If negative (Net Cash): Add to EV (increases equity value)
• Use Diluted Shares: Includes options, RSUs, convertible securities
• Other adjustments (if applicable):
  • Minority interests
  • Pension liabilities
  • Operating lease obligations

Valuation Output Format:

Valuation Component,Amount ($M)
PV Explicit FCFs,X.X
PV Terminal Value,Y.Y
Enterprise Value,Z.Z
(-) Net Debt,A.A
Equity Value,B.B
,,
Shares Outstanding (M),C.C
Implied Price per Share,$XX.XX
Current Share Price,$YY.YY
Implied Upside/(Downside),+XX%

Step 10: Sensitivity Analysis

Build three sensitivity tables at the bottom of the DCF sheet showing how valuation changes with different assumptions:

1. WACC vs Terminal Growth - Shows enterprise value sensitivity to discount rate and perpetuity growth
2. Revenue Growth vs EBIT Margin - Shows impact of top-line growth and operating leverage
3. Beta vs Risk-Free Rate - Shows sensitivity to cost of equity components

Implementation: These are simple 2D grids (NOT Excel's "Data Table" feature) with formulas in each cell. Each cell must contain a full DCF recalculation for that specific assumption combination. See Critical Constraints section for detailed requirements on populating all 75 cells programmatically using openpyxl.

<correct_patterns>

This section contains all the CORRECT patterns to follow when building DCF models.

Scenario Block Selection Pattern - Follow This Approach

Assumptions are organized in separate blocks for each scenario:

CRITICAL STRUCTURE - Three rows per section header:

BEAR CASE ASSUMPTIONS (section header, merge cells across)
Assumption,FY1,FY2,FY3,FY4,FY5
Revenue Growth (%),12%,10%,9%,8%,7%
EBIT Margin (%),45%,44%,43%,42%,41%

BASE CASE ASSUMPTIONS (section header, merge cells across)
Assumption,FY1,FY2,FY3,FY4,FY5
Revenue Growth (%),16%,14%,12%,10%,9%
EBIT Margin (%),48%,49%,50%,51%,52%

BULL CASE ASSUMPTIONS (section header, merge cells across)
Assumption,FY1,FY2,FY3,FY4,FY5
Revenue Growth (%),20%,18%,15%,13%,11%
EBIT Margin (%),50%,51%,52%,53%,54%

Each scenario block MUST have a column header row showing the projection years (FY2025E, FY2026E, etc.) immediately below the section title. Without this, users cannot tell which assumption value corresponds to which year.

How to reference assumptions - Create a consolidation column:

1. Case selector cell (e.g., B6) contains 1=Bear, 2=Base, or 3=Bull
2. Create a consolidation column with INDEX or OFFSET formulas to pull from the correct scenario block
3. Projection formulas reference the consolidation column (clean cell references)
4. Each scenario block contains full set of DCF assumptions across projection years

Recommended consolidation column pattern (using INDEX): =INDEX(B10:D10, 1, $B$6)

NOT this - scattered IF statements throughout: =IF($B$6=1,[Bear block cell],IF($B$6=2,[Base block cell],[Bull block cell]))

The consolidation column approach centralizes logic and makes the model easier to audit.

Correct Revenue Projection Pattern

Create a consolidation column with INDEX formulas, then reference it in projections:

Step 1 - Consolidation column for FY1 growth: =INDEX([Bear FY1 growth]:[Bull FY1 growth], 1, $B$6)

Step 2 - Revenue projection references the consolidation column: Revenue Year 1: =D29*(1+$E$10)

Where:

• D29 = Prior year revenue
• $E$10 = Consolidation column cell for FY1 growth (contains INDEX formula)
• $B$6 = Case selector (1=Bear, 2=Base, 3=Bull)

This approach is cleaner than embedding IF statements in every projection formula and makes it much easier to audit which scenario assumptions are being used.

Correct FCF Formula Pattern

Use consolidation columns with INDEX formulas, then reference them in FCF calculations:

Consolidation column approach:

Item,Formula,Reference
D&A,=E29*$E$21,$E$21 = consolidation column for D&A %
CapEx,=E29*$E$22,$E$22 = consolidation column for CapEx %
Δ NWC,=(E29-D29)*$E$23,$E$23 = consolidation column for NWC %
Unlevered FCF,=E57+E58-E60-E62,E57=NOPAT E58=D&A E60=CapEx E62=Δ NWC

Each consolidation column cell contains an INDEX formula that pulls from the appropriate scenario block based on case selector. This keeps projection formulas clean and auditable.

Before writing formulas, confirm scenario block row locations and set up consolidation columns.

Correct Cell Comment Format

Every hardcoded value needs this format:

"Source: [System/Document], [Date], [Reference], [URL if applicable]"

Examples:

Item,Source Comment
Stock price,Source: Market data script 2025-10-12 Close price
Shares outstanding,Source: 10-K FY2024 Page 45 Note 12
Historical revenue,Source: 10-K FY2024 Page 32 Consolidated Statements
Beta,Source: Market data script 2025-10-12 5-year monthly beta
Consensus estimates,Source: Management guidance Q3 2024 earnings call

Correct Assumption Table Structure

CRITICAL: Each scenario block requires THREE structural elements:

1. Section header row (merged cells): e.g., "BEAR CASE ASSUMPTIONS"
2. Column header row showing years - THIS IS REQUIRED, DO NOT SKIP
3. Data rows with assumption values

Structure:

BEAR CASE ASSUMPTIONS (section header - merge across columns A:G)
Assumption,FY1,FY2,FY3,FY4,FY5
Revenue Growth (%),X%,X%,X%,X%,X%
EBIT Margin (%),X%,X%,X%,X%,X%
Terminal Growth,X%,,,,
WACC,X%,,,,

BASE CASE ASSUMPTIONS (section header - merge across columns A:G)
Assumption,FY1,FY2,FY3,FY4,FY5
Revenue Growth (%),X%,X%,X%,X%,X%
EBIT Margin (%),X%,X%,X%,X%,X%
Terminal Growth,X%,,,,
WACC,X%,,,,

BULL CASE ASSUMPTIONS (section header - merge across columns A:G)
Assumption,FY1,FY2,FY3,FY4,FY5
Revenue Growth (%),X%,X%,X%,X%,X%
EBIT Margin (%),X%,X%,X%,X%,X%
Terminal Growth,X%,,,,
WACC,X%,,,,

WITHOUT the column header row showing projection years (FY2025E, FY2026E, etc.), users cannot tell which assumption value corresponds to which year. This row is MANDATORY.

Then create a consolidation column (typically the next column to the right) that uses INDEX formulas to pull from the selected scenario block based on the case selector. This consolidation column is what your projection formulas reference.

Correct Row Planning Process

1. Write ALL headers and labels FIRST:

Row,Content
1,[Company Name] DCF Model
2,Ticker | Date | Year End
4,Case Selector
7,KEY ASSUMPTIONS
26,Assumption headers
27-31,Growth assumptions
...,...

2. Write ALL section dividers and blank rows

3. THEN write formulas using the locked row positions

4. Test formulas immediately after creation

Think of it like construction:

• Good: Pour foundation, then build walls (stable structure)
• Bad: Build walls, then pour foundation (walls collapse)

Excel version:

• Good: Add headers, then write formulas (formulas stable)
• Bad: Write formulas, then add headers (formulas break)

Correct Sensitivity Table Implementation

IMPORTANT: These are NOT Excel's "Data Table" feature. These are simple grids where you write regular formulas using openpyxl. Yes, this means ~75 formulas total (3 tables × 25 cells each), but this is straightforward and required.

Programmatic Population with Formulas:

Each sensitivity table must be fully populated with formulas that recalculate the implied share price for each combination of assumptions. Do not use Excel's Data Table feature (it requires manual intervention and cannot be automated via openpyxl).

Implementation approach - CONCRETE EXAMPLE:

Table Structure — 5×5 grid (ODD dimensions, base case centered):

If the model's base WACC = 9.0% and base terminal growth = 3.0%, build the axes symmetrically around those values:

WACC vs Terminal Growth,  2.0%,  2.5%,  3.0%,  3.5%,  4.0%
              8.0%,       [fml], [fml], [fml], [fml], [fml]
              8.5%,       [fml], [fml], [fml], [fml], [fml]
              9.0%,       [fml], [fml], [★  ], [fml], [fml]   ← middle row = base WACC
              9.5%,       [fml], [fml], [fml], [fml], [fml]
             10.0%,       [fml], [fml], [fml], [fml], [fml]
                                   ↑
                          middle col = base terminal g

★ = the center cell. Its formula output MUST equal the model's actual implied share price (from the valuation summary). Apply the medium-blue fill (#BDD7EE) and bold font to this cell so the base case is visually anchored.

Rule for axis values: axis_values = [base - 2*step, base - step, base, base + step, base + 2*step] — symmetric around the base, odd count guarantees a center.

Formula Pattern - Cell B88 (WACC=8.0%, Terminal Growth=2.0%):

The formula in B88 should recalculate the implied price using:

• WACC from row header: $A88 (8.0%)
• Terminal Growth from column header: B$87 (2.0%)

Recommended approach: Reference the main DCF calculation but substitute these values.

Example formula structure: =([SUM of PV FCFs using $A88 as discount rate] + [Terminal Value using B$87 as growth rate and $A88 as WACC] - [Net Debt]) / [Shares]

CRITICAL - Write a formula for EVERY cell in the 5x5 grid (25 cells per table, 75 cells total). Use openpyxl to write these formulas programmatically in a loop. Do NOT skip this step or leave placeholder text.

Python implementation pattern:

# Pseudocode for populating sensitivity table
for row_idx, wacc_value in enumerate(wacc_range):
    for col_idx, term_growth_value in enumerate(term_growth_range):
        # Build formula that uses wacc_value and term_growth_value
        formula = f"=<DCF recalc using {wacc_value} and {term_growth_value}>"
        ws.cell(row=start_row+row_idx, column=start_col+col_idx).value = formula

The sensitivity tables must work immediately when the model is opened, with no manual steps required from the user.

</correct_patterns>

<common_mistakes>

This section contains all the WRONG patterns to avoid when building DCF models.

WRONG: Simplified Sensitivity Table Approximations or Placeholder Text

Don't use linear approximations:

// WRONG - Linear approximation
B97: =B88*(1+(0.096-0.116))    // Assumes linear relationship

// WRONG - Division shortcut
B105: =B88/(1+(E48-0.07))      // Doesn't recalculate full DCF

Don't leave placeholder text:

// WRONG - Placeholder note
"Note: Use Excel Data Table feature (Data → What-If Analysis → Data Table) to populate sensitivity tables."

// WRONG - Empty cells
[leaving cells blank because "this is complex"]

Don't confuse terminology:

• ❌ "Sensitivity tables need Excel's Data Table feature" (NO - that's a specific Excel tool we can't use)
• ✅ "Sensitivity tables are simple grids with formulas in each cell" (YES - this is what we build)