merger-model

name	merger-model
description	M&A deal modeling: accretion/dilution analysis, LBO models, DCF valuation, comparable company analysis, precedent transactions, and synergy estimation. Full three-statement merger models.
tags	["mergers","acquisitions","lbo","valuation","dcf","financial-modeling","zorai"]

Overview

A merger model estimates the financial impact of an acquisition or merger: purchase price, financing mix, pro forma statements, synergies, accretion/dilution, leverage, and returns. Use it for M&A analysis, not just valuation in isolation.

When to Use

Use this skill when:

• evaluating whether a deal is accretive or dilutive,
• comparing stock vs cash vs mixed consideration,
• building a simple LBO/strategic deal screen,
• estimating synergy sensitivity,
• or drafting the structure for a full M&A model.

Core model sections

A proper merger model usually includes:

1. transaction assumptions
2. purchase price / enterprise value
3. financing sources and uses
4. purchase accounting adjustments
5. pro forma income statement
6. share count bridge
7. accretion/dilution analysis
8. leverage and coverage metrics
9. sensitivity tables

Basic accretion / dilution calculation

def accretion_dilution(acquirer_net_income, target_net_income,
                       acquirer_shares, new_shares_issued,
                       after_tax_synergies=0.0):
    pro_forma_income = acquirer_net_income + target_net_income + after_tax_synergies
    pro_forma_shares = acquirer_shares + new_shares_issued
    base_eps = acquirer_net_income / acquirer_shares
    pro_forma_eps = pro_forma_income / pro_forma_shares
    accretion_pct = (pro_forma_eps / base_eps - 1) * 100
    return {
        'base_eps': round(base_eps, 4),
        'pro_forma_eps': round(pro_forma_eps, 4),
        'accretion_pct': round(accretion_pct, 2),
    }

print(accretion_dilution(
    acquirer_net_income=900,
    target_net_income=220,
    acquirer_shares=300,
    new_shares_issued=50,
    after_tax_synergies=40,
))

Sources and uses pattern

Uses:
- equity purchase price
- debt repayment / assumption
- fees and expenses

Sources:
- cash on balance sheet
- new debt
- stock issuance

Always reconcile sources == uses.

LBO-style screen example

def rough_lbo_irr(entry_ebitda, entry_multiple, debt_pct, ebitda_growth, exit_multiple, years):
    entry_ev = entry_ebitda * entry_multiple
    debt = entry_ev * debt_pct
    equity = entry_ev - debt
    exit_ebitda = entry_ebitda * ((1 + ebitda_growth) ** years)
    remaining_debt = debt * 0.65  # simple placeholder assumption
    exit_ev = exit_ebitda * exit_multiple
    exit_equity = exit_ev - remaining_debt
    irr = (exit_equity / equity) ** (1 / years) - 1
    return round(irr * 100, 2)

Minimum real-world checks

• Is the target EV/EBITDA multiple plausible vs comps?
• Are synergies cost, revenue, or both?
• Are synergies pre-tax or after-tax?
• Is financing realistic at current rates and leverage levels?
• Does the model include fees, integration costs, and stock-based comp effects?
• Are share issuance and treasury method assumptions explicit?

Common failure modes

• counting synergies with no timing ramp
• mixing EBITDA, EBIT, and net income carelessly
• forgetting transaction fees
• using enterprise value where equity value is needed
• assuming all synergies are immediate and fully realizable
• treating accretion as proof of strategic quality