GILEAD SCIENCES, INC. (GILD) Key Metrics API

• cURL
• Python
• JavaScript

curl "https://financialdata.net/api/v1/key-metrics?identifier=GILD&key=API_KEY"

import requests

                                                url = 'https://financialdata.net/api/v1/key-metrics?identifier=GILD&key=API_KEY'    
                                                response = requests.get(url)

                                                print(response.json())
                                            

const url = 'https://financialdata.net/api/v1/key-metrics?identifier=GILD&key=API_KEY';
                                            
                                                const response = await fetch(url);
                                                const data = await response.json();

                                                console.log(data);
                                            

[
  {
    "trading_symbol": "GILD",
    "central_index_key": "0000882095",
    "registrant_name": "GILEAD SCIENCES, INC.",
    "fiscal_year": "2025",
    "period_end_date": "2025-12-31",
    "earnings_per_share": 6.84,
    "earnings_per_share_forecast": -0.47,
    "price_to_earnings_ratio": 17.9444444444444,
    "forward_price_to_earnings_ratio": -261.148936170213,
    "earnings_growth_rate": 1700.0,
    "price_earnings_to_growth_ratio": 0.0105555555555556,
    "book_value_per_share": 18.25,
    "price_to_book_ratio": 6.72547945205479,
    "ebitda": 15139000000.0,
    "enterprise_value": 172868560000.0,
    "dividend_yield": 0.026216764373179,
    "dividend_payout_ratio": 0.470387779083431,
    "debt_to_equity_ratio": 1.22204113993745,
    "capital_expenditures": 2582000000.0,
    "free_cash_flow": 7437000000.0,
    "return_on_equity": 0.374840329471876,
    "one_year_beta": 0.345040391052869,
    "three_year_beta": 0.349431345773952,
    "five_year_beta": 0.412782327633938
  },
  ...
]

The API endpoint returns key financial metrics such as price-to-earnings ratio, price-to-book ratio, free cash flow, etc. This information is particularly important for value investors looking to identify undervalued stocks. Data is available for several thousand US and international companies.