Key Metrics API for NORTHROP GRUMMAN CORP /DE/ (NOC)

• cURL
• Python
• JavaScript

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

import requests

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

                                                print(response.json())
                                            

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

                                                console.log(data);
                                            

[
  {
    "trading_symbol": "NOC",
    "central_index_key": "0001133421",
    "registrant_name": "NORTHROP GRUMMAN CORP /DE/",
    "fiscal_year": "2025",
    "period_end_date": "2025-12-31",
    "earnings_per_share": 29.14,
    "earnings_per_share_forecast": 28.96,
    "price_to_earnings_ratio": 19.5679478380233,
    "forward_price_to_earnings_ratio": 19.6895718232044,
    "earnings_growth_rate": 2.64177527298344,
    "price_earnings_to_growth_ratio": 7.40712052161979,
    "book_value_per_share": 116.19512195122,
    "price_to_book_ratio": 4.90734886649874,
    "ebitda": 5654000000.0,
    "enterprise_value": 93652135000.0,
    "dividend_yield": null,
    "dividend_payout_ratio": null,
    "debt_to_equity_ratio": 0.973371716444764,
    "capital_expenditures": 1908000000.0,
    "free_cash_flow": 2849000000.0,
    "return_on_equity": 0.250809643756747,
    "one_year_beta": 0.050122257896196,
    "three_year_beta": 0.102265570108473,
    "five_year_beta": 0.230488445964041
  },
  ...
]

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.