Free Piotroski F-Score & Altman Z-Score API
Comprehensive quantitative health check for any US stock — including institutional-grade metrics normally behind expensive paywalls.
Endpoint
GET https://securitiesdb.com/api/v1/stocks/{ticker}/quant-healthWhat's Included
Piotroski F-Score (0-9)
Measures financial strength based on 9 binary tests across profitability, leverage, and operating efficiency.
Altman Z-Score
Bankruptcy prediction model. Below 1.81 = distress zone. Above 2.99 = safe zone.
Beneish M-Score
Earnings manipulation detector. Above -1.78 flags potential accounting irregularities.
ROIC vs WACC Spread
Return on invested capital minus weighted average cost of capital. Positive = value creation.
DuPont Decomposition
Breaks ROE into net margin × asset turnover × equity multiplier to reveal the driver of returns.
Full Metric Suite
Free cash flow yield, debt-to-equity, interest coverage, revenue growth, Sharpe ratio, max drawdown, and more.
Python Example — Screen for Quality Stocks
import requests
tickers = ["AAPL", "MSFT", "GOOGL", "META", "NVDA", "TSLA"]
quality_stocks = []
for ticker in tickers:
r = requests.get(f"https://securitiesdb.com/api/v1/stocks/{ticker}/quant-health")
d = r.json()["data"]
scores = d["scores"]
if scores["piotroski_f"] >= 7 and scores["altman_z"] > 2.99:
quality_stocks.append({
"ticker": ticker,
"piotroski": scores["piotroski_f"],
"altman_z": scores["altman_z"],
"roic_wacc_spread": d["value_creation"]["roic_wacc_spread"],
})
print("High-quality stocks:")
for s in quality_stocks:
print(f" {s['ticker']}: F-Score={s['piotroski']}, "
f"Z-Score={s['altman_z']:.2f}, "
f"Value Creation={s['roic_wacc_spread']:.1%}")Response Fields
| Section | Fields |
|---|---|
| scores | piotroski_f, altman_z, beneish_m |
| value_creation | roic, wacc, roic_wacc_spread, fcf_yield, ebitda |
| profitability | net_margin, gross_margin, fcf_payout_ratio, dupont_ |
| growth | revenue_growth_yoy, earnings_growth_yoy |
| leverage | debt_to_equity, current_ratio, interest_coverage, net_debt_to_ebitda |
| risk | sharpe_1y, sharpe_3y, max_drawdown_3y, max_drawdown_5y, volatility |
| valuation | pe_5y_avg, pe_vs_historical_pct |