📈 Stock Historical Data (Investing.com) Fetch reliable and structured historical stock data from Investing.com for any supported country and stock symbol. Ideal for traders, analysts, researchers, and data scientists who need daily, weekly, or monthly stock price history. --- ## 🧠 What This Actor Does This Apify actor scrapes historical stock data from Investing.com based on the following input parameters: - Stock symbol (e.g., AAPL, MSFT, BBVA) - Country (e.g., United States, Spain) - Date range (from_date and to_date) - Time interval (Daily, Weekly, or Monthly) - Sorting order (ascending or descending) --- ## ✅ Sample Input json { "stockSymbol": "AAPL", "country": "united states", "from_date": "01/01/2023", "to_date": "31/12/2023", "order": "ascending", "interval": "Daily" } --- ## 📤 Output The actor saves two main outputs: ### 1. Dataset Record json { "stock": "AAPL", "country": "united states", "from_date": "01/01/2023", "to_date": "31/12/2023", "interval": "Daily", "order": "ascending", "retrieved_at": "2025-06-30T14:23:45.123Z", "data_format": "json", "stock_name": "Apple Inc", "historical_data": [ { "date": "2023-01-03", "open": 130.28, "close": 125.07, "high": 131.03, "low": 124.17, "volume": 112117500, "currency": "USD" }, ... ], "total_records": 252 } ### 2. Key-Value Store (historical_summary) json { "stock": "AAPL", "country": "united states", "stock_name": "Apple Inc", "from_date": "01/01/2023", "to_date": "31/12/2023", "interval": "Daily", "total_records": 252, "has_data": true, "retrieved_at": "2025-06-30T14:23:45.123Z" } --- ## ⚠️ Errors & Validation The actor performs extensive validation: * stockSymbol, country, from_date, and to_date are mandatory. * Validates formats of date fields (must be in dd/mm/yyyy). * Ensures correct interval values (Daily, Weekly, Monthly). * Ensures order is one of the accepted values. If any validation fails, a descriptive error is thrown and logged. --- ## 📦 Example Use Cases * 🧮 Backtest trading strategies with accurate historical pricing * 📊 Visualize stock trends over time * 🏦 Financial reports, dashboards, or research * 🔁 Feed into machine learning time-series models --- ## 🧪 Tips * Always specify correct country for the stock symbol (e.g., BBVA is from Spain, not USA). * Use "Daily" for high-resolution, or "Monthly" for low-noise trends. * Works best when used in conjunction with Apify's scheduler or integrations. --- ## Support If you have any questions or encounter any issues, please consult the Apify documentation or reach out to us through one of the following channels: * Telegram: @pintoflow * Apify Platform: You can also contact us directly through this platform. ---