"""What happens to a DCF's terminal value when the growth rate you picked is not safely below the discount rate you picked. This is the evidence behind /guides/terminal-growth-above-discount-rate/. It is kept in the repo and published so the claims on that page can be checked rather than taken on trust. Re-run it and the JSON regenerates; if a number on the page and a number in the JSON disagree, the JSON is right and the page is out of date. The Gordon growth terminal value formula is TV = FCF * (1 + g) / (r - g) and it is only defined for r > g. It does not fail loudly when that stops being true. For g just under r the multiplier 1/(r-g) explodes to absurd multiples with no error; for g >= r the formula returns a negative number that still looks like an ordinary output. Nothing in the arithmetic itself objects. A natural way to pick "the growth rate" without thinking about it is to take a company's own trailing growth and carry it straight into the terminal year. This script does exactly that, live, for the same 20 large filers surveyed in the first two guides on this site: it pulls each company's last five fiscal years of revenue and free cash flow (operating cash flow minus capex, the same subtraction the free-cash-flow guide covers) from SEC EDGAR, computes the 5-year CAGR of each, and checks that CAGR against one fixed discount rate -- 9%, the middle of the range most default DCF templates use for a diversified large-cap, and the value this site's own calculator falls back to before a user changes it. A company-specific WACC needs a market cap and a beta, which is not something SEC EDGAR carries, so the comparison here is deliberately a single stated constant, not a per-company estimate. What is live is the growth rate on the other side of the comparison. Usage: python research/terminal-growth-survey.py Writes: research/terminal-growth-survey.json """ import io import json import os import time import urllib.error import urllib.request from datetime import datetime UA = "Fairvalue Radar (privacy@fairvalueradar.com)" HERE = os.path.dirname(os.path.abspath(__file__)) ANNUAL = ("10-K", "20-F", "40-F") DISCOUNT_RATE = 0.09 COMPANIES = [ ("AAPL", 320193), ("MSFT", 789019), ("NVDA", 1045810), ("AMZN", 1018724), ("GOOGL", 1652044), ("META", 1326801), ("TSLA", 1318605), ("JPM", 19617), ("XOM", 34088), ("JNJ", 200406), ("WMT", 104169), ("PG", 80424), ("KO", 21344), ("PFE", 78003), ("INTC", 50863), ("CVX", 93410), ("T", 732717), ("BA", 12927), ("GE", 40545), ("MRK", 310158), ] REVENUE_TAGS = ["RevenueFromContractWithCustomerExcludingAssessedTax", "RevenueFromContractWithCustomerIncludingAssessedTax", "Revenues", "SalesRevenueNet"] OCF_TAGS = ["NetCashProvidedByUsedInOperatingActivities", "NetCashProvidedByUsedInOperatingActivitiesContinuingOperations"] CAPEX_TAGS = ["PaymentsToAcquirePropertyPlantAndEquipment", "PaymentsToAcquireProductiveAssets"] def fetch(url, tries=4): """A 404 is an answer, not a failure: it means the company has never used that tag under that namespace. Anything else is retried.""" req = urllib.request.Request(url, headers={"User-Agent": UA, "Accept": "application/json"}) for attempt in range(tries): try: with urllib.request.urlopen(req, timeout=30) as r: return json.loads(r.read().decode("utf-8")), None except urllib.error.HTTPError as e: if e.code == 404: return None, "404" time.sleep(1.5 * (attempt + 1)) except Exception: time.sleep(1.5 * (attempt + 1)) return None, "unreachable after %d tries" % tries def annual_series(payload): """One fact per annual, full-year period, newest last. A quarterly or cumulative-quarter fact under the same tag is dropped by its duration, the same guard build-stock-pages.py uses.""" units = (payload or {}).get("units", {}) rows = units.get("USD") or next(iter(units.values()), []) by = {} for f in rows: if f.get("form") not in ANNUAL or not f.get("end") or not f.get("start"): continue days = (datetime.fromisoformat(f["end"]) - datetime.fromisoformat(f["start"])).days if days < 300 or days > 400: continue prev = by.get(f["end"]) if not prev or f.get("accn", "") > prev.get("accn", ""): by[f["end"]] = f return [by[k] for k in sorted(by)] def pick_series(cik, tags): """Among candidate tags, keep the one whose newest annual fact is newest -- an abandoned tag still answers, so the first hit is not necessarily live.""" best, best_tag = [], None for tag in tags: time.sleep(0.2) payload, err = fetch("https://data.sec.gov/api/xbrl/companyconcept/CIK%010d/us-gaap/%s.json" % (cik, tag)) if err: continue series = annual_series(payload) if series and (not best or series[-1]["end"] > best[-1]["end"]): best, best_tag = series, tag return best, best_tag def cagr(series, years): if len(series) < years + 1: return None a, b = series[-1 - years]["val"], series[-1]["val"] if a <= 0 or b <= 0: return None return round((b / a) ** (1.0 / years) - 1, 4) def main(): out = {"readOn": time.strftime("%Y-%m-%d"), "source": "SEC EDGAR XBRL companyconcept (revenue, operating cash flow, capex)", "discountRateAssumption": DISCOUNT_RATE, "note": "discountRateAssumption is a single stated constant, not a per-company WACC -- " "SEC EDGAR has no market cap or beta to compute one. The CAGRs are live.", "companies": []} for ticker, cik in COMPANIES: rec = {"ticker": ticker, "cik": cik} rev_series, rev_tag = pick_series(cik, REVENUE_TAGS) ocf_series, ocf_tag = pick_series(cik, OCF_TAGS) capex_series, capex_tag = pick_series(cik, CAPEX_TAGS) fcf_series = [] if ocf_series and capex_series: capex_by_end = {f["end"]: f["val"] for f in capex_series} for f in ocf_series: if f["end"] in capex_by_end: fcf_series.append({"end": f["end"], "val": f["val"] - capex_by_end[f["end"]]}) rev_cagr5 = cagr(rev_series, 5) fcf_cagr5 = cagr(fcf_series, 5) rec["revenue"] = {"tag": rev_tag, "annualFacts": len(rev_series), "cagr5": rev_cagr5} if rev_series else {"state": "no annual facts"} rec["fcf"] = {"ocfTag": ocf_tag, "capexTag": capex_tag, "annualFacts": len(fcf_series), "cagr5": fcf_cagr5} if fcf_series else {"state": "no annual FCF series"} naive_g = fcf_cagr5 if fcf_cagr5 is not None else rev_cagr5 rec["naiveTerminalGrowth"] = naive_g rec["naiveGrowthSource"] = "fcf" if fcf_cagr5 is not None else ("revenue" if rev_cagr5 is not None else None) if naive_g is None: rec["verdict"] = "insufficient data" rec["terminalValueMultiplier"] = None elif naive_g >= DISCOUNT_RATE: rec["verdict"] = "breaks the formula: g >= r, terminal value is negative" rec["terminalValueMultiplier"] = None else: multiplier = (1 + naive_g) / (DISCOUNT_RATE - naive_g) rec["terminalValueMultiplier"] = round(multiplier, 1) rec["verdict"] = ("near-break: multiplier above 30x a single year's FCF" if multiplier > 30 else "within range") out["companies"].append(rec) print("%-6s naive_g=%-8s source=%-9s multiplier=%-7s verdict=%s" % ( ticker, naive_g, rec["naiveGrowthSource"], rec["terminalValueMultiplier"], rec["verdict"])) io.open(os.path.join(HERE, "terminal-growth-survey.json"), "w", encoding="utf-8").write( json.dumps(out, indent=1)) print("\nwritten: research/terminal-growth-survey.json") if __name__ == "__main__": main()