"""Anduril valuation, public evidence cutoff 2026-10-14. USD billions. This is an expectations model, not management guidance or audited financials. No external dependencies. Run: python model.py [output_directory] Gross equity = consolidated enterprise value + assumed net cash; subtract the FAIR VALUE of non-controlling interests and other senior claims separately. """ from __future__ import annotations from datetime import date from pathlib import Path import csv import json import math import sys AS_OF = date(2026, 10, 14) TAX = 0.24 REVENUE_2025 = 2.2 # Company-reported; see source S1 in the article. REVENUE_2026 = 4.3 # Reported investor projection, NOT actual revenue; S4. EBIT_2026 = -1.2 # Reported projected operating loss; not audited; S3. STUB = (date(2026, 12, 31) - AS_OF).days / 365 A2 = [0.6, 0.85, 0.9, 0.85, 0.5, 0, 0, 0, 0, 0] # Author timing of the announced $3.7bn private investment, not a company schedule. CASES = { 'Downside': dict( growth=[.30,.25,.22,.18,.15,.12,.10,.08,.06,.05], margins=[-.20,-.12,-.06,0,.05,.09,.12,.14,.15,.15], nwc=[.20]*10, capex=[.06,.06,.06,.055,.05,.045,.04,.04,.04,.04], da=[.02]*10, roic=.10, fade=[.045,.04,.035,.03,.03]), 'Base': dict( growth=[.60,.45,.35,.30,.27,.24,.21,.18,.15,.12], margins=[-.20,-.10,-.03,.03,.09,.14,.18,.20,.21,.22], nwc=[.18,.18,.18,.18,.17,.16,.15,.14,.14,.14], capex=[.06,.06,.06,.055,.05,.045,.04,.04,.035,.035], da=[.02,.02,.02,.02,.025,.025,.025,.025,.025,.025], roic=.15, fade=[.09,.07,.05,.04,.03]), 'Upside': dict( growth=[.75,.60,.50,.40,.30,.25,.20,.18,.15,.12], margins=[-.15,-.05,.02,.08,.14,.20,.24,.26,.27,.28], nwc=[.16,.16,.15,.14,.13,.12,.11,.10,.10,.10], capex=[.06,.06,.06,.055,.05,.045,.04,.035,.03,.03], da=[.02,.02,.02,.02,.025,.025,.025,.025,.025,.025], roic=.20, fade=[.09,.07,.05,.04,.03]), } def value(case: str = 'Base', discount: float = .12, terminal_growth: float = .03, net_cash: float = 3., minority_value: float = 0., scale: float = 1., available_cash: float = 3.) -> dict: """Value consolidated operating cash flows; bridge equity with explicit claims. scale increases each 2027-36 growth factor by scale**0.1; 2036 sales therefore scale exactly. The reverse DCF retains margins and reinvestment assumptions. 2037-41 growth and reinvestment fade into a sustainable ROIC-based perpetuity. The zero minority default is an UNADJUSTED bridge, not an assertion of no NCI. """ if case not in CASES: raise ValueError('Unknown scenario') c = CASES[case] vals = [discount, terminal_growth, net_cash, minority_value, scale, available_cash] if not all(math.isfinite(x) for x in vals): raise ValueError('All inputs must be finite') if not 0 <= terminal_growth < min(discount, c['roic']) or scale <= 0 or minority_value < 0 or available_cash < 0: raise ValueError('Require 0 <= g < discount and ROIC; positive scale; nonnegative NCI') rev = REVENUE_2026 nwc = .18 * rev annual_2026_fcf = EBIT_2026 + .02 * rev - 1.0 - .18*(rev-REVENUE_2025) stub_cf = annual_2026_fcf * STUB pv = stub_cf / (1+discount)**STUB cumulative = stub_cf minimum = cumulative rows = [] for i, year in enumerate(range(2027, 2042)): previous = rev if i < 10: growth = (1+c['growth'][i]) * scale**.1 - 1 margin = c['margins'][i] else: # At the final fade year the explicit growth equals terminal growth. j = i - 10 growth = c['fade'][j] + (terminal_growth-.03)*(j+1)/5 margin = c['margins'][-1] rev *= 1+growth ebit = rev*margin tax = max(0., ebit)*TAX nopat = ebit-tax idx = min(i, 9) da = rev*c['da'][idx] next_nwc = rev*c['nwc'][idx] delta_nwc = next_nwc-nwc ordinary_capex = rev*c['capex'][idx] arsenal2 = A2[i] if i < 10 else 0. raw_reinvestment = ordinary_capex + arsenal2 - da + delta_nwc adjustment = 0. if i >= 10: blend = (i-9)/5 target = nopat*growth/c['roic'] # Explicit additional capital required to converge to mature ROIC. adjustment = blend*(target-raw_reinvestment) reinvestment = raw_reinvestment+adjustment fcf = nopat-reinvestment t = (date(year, 12, 31)-AS_OF).days/365 pv_fcf = fcf/(1+discount)**t pv += pv_fcf cumulative += fcf minimum = min(minimum, cumulative) rows.append(dict(year=year, revenue=rev, growth=growth, ebit_margin=margin, ebit=ebit, cash_tax=tax, nopat=nopat, depreciation=da, ordinary_capex=ordinary_capex, arsenal2_capex=arsenal2, nwc=next_nwc, change_nwc=delta_nwc, fade_reinvestment=adjustment, total_reinvestment=reinvestment, fcf=fcf, pv_fcf=pv_fcf, cumulative_fcf=cumulative, discount_years=t)) nwc = next_nwc terminal_nopat = rev*(1+terminal_growth)*c['margins'][-1]*(1-TAX) terminal_fcf = terminal_nopat*(1-terminal_growth/c['roic']) terminal_value = terminal_fcf/(discount-terminal_growth) pv_terminal = terminal_value/(1+discount)**rows[-1]['discount_years'] ev = pv+pv_terminal return dict(case=case, valuation_date=AS_OF.isoformat(), units='USD billions', discount=discount, terminal_growth=terminal_growth, terminal_roic=c['roic'], net_cash_assumption=net_cash, available_cash_assumption=available_cash, minority_value_assumption=minority_value, stub_year_fraction=STUB, stub_fcf=stub_cf, rows=rows, pv_explicit=pv, terminal_fcf=terminal_fcf, pv_terminal=pv_terminal, enterprise_value=ev, gross_equity_value=ev+net_cash, equity_after_assumed_nci=ev+net_cash-minority_value, terminal_share=pv_terminal/ev if ev > 0 else None, peak_cumulative_funding=-minimum, incremental_funding_proxy=max(0.,-minimum-available_cash), first_positive_fcf=next((r['year'] for r in rows if r['fcf']>0),None)) def reverse(target: float, **kwargs) -> dict: """Solve the 2036 revenue scaling needed to support a gross equity reference.""" lo, hi = .01, 10. if not value(scale=lo, **kwargs)['gross_equity_value'] < target < value(scale=hi, **kwargs)['gross_equity_value']: raise ValueError('Target is outside the reverse-DCF bracket') for _ in range(90): mid = (lo+hi)/2 if value(scale=mid, **kwargs)['gross_equity_value'] < target: lo = mid else: hi = mid result = value(scale=(lo+hi)/2, **kwargs) return dict(target=target, scale=(lo+hi)/2, revenue_2036=result['rows'][9]['revenue'], revenue_2041=result['rows'][-1]['revenue'], revenue_cagr=(result['rows'][9]['revenue']/REVENUE_2026)**.1-1, residual=result['gross_equity_value']-target) def export(destination: Path) -> None: destination.mkdir(parents=True, exist_ok=True) results = {name:value(name) for name in CASES} payload = dict(as_of=AS_OF.isoformat(), unit='USD billions', warning='Author scenarios; gross equity before minority/senior claims. Cash is assumed, not disclosed.', cases={name:{key:item for key,item in result.items() if key != 'rows'} for name,result in results.items()}, assumptions=CASES, arsenal2_schedule=A2, reverse={str(t):reverse(t) for t in [61.,100.]}, sensitivity=[dict(discount=r,terminal_growth=g,gross_equity=value(discount=r,terminal_growth=g)['gross_equity_value']) for r in [.10,.11,.12,.13,.14,.15,.16] for g in [.02,.03,.04]]) (destination/'model-results.json').write_text(json.dumps(payload,indent=2)+'\n') with (destination/'forecast.csv').open('w',newline='') as f: writer = csv.DictWriter(f,fieldnames=['case']+list(results['Base']['rows'][0])) writer.writeheader() for name, result in results.items(): for row in result['rows']: writer.writerow({'case':name,**row}) print(json.dumps({k:{f:round(v[f],3) if isinstance(v[f],float) else v[f] for f in ['enterprise_value','gross_equity_value','peak_cumulative_funding','incremental_funding_proxy','first_positive_fcf','terminal_share']} for k,v in results.items()},indent=2)) print('Reverse DCF:',payload['reverse']) if __name__ == '__main__': export(Path(sys.argv[1]) if len(sys.argv)>1 else Path(__file__).resolve().parent)