Access Daily Stock Data from 2000 to Present

This API is designed for a variety of applications, including quantitative and algorithmic trading, financial dashboards, AI and machine learning model training, portfolio analysis, and investor research tools. Its flexible query parameters and structured JSON output make it easy to integrate into platforms requiring long-term market insights, supporting developers, analysts, and researchers in building financial solutions.

Key Features

• 📅 Daily Historical Data - Retrieve daily OHLC data from 2000 to today.
  Users can access daily price history by specifying a symbol and date range, enabling long-term analysis of market trends. This feature supports applications like backtesting trading strategies or building historical performance charts, providing a robust dataset for in-depth financial analysis.

• 📊 Support for Multiple Security Types - Access data for equities, ETFs, mutual funds, and indexes.
  By inputting a single ticker symbol, users can pull historical data for a variety of securities, streamlining workflows for portfolio managers or researchers comparing performance across asset classes. This unified approach ensures consistency and efficiency in applications like portfolio tracking or benchmark analysis.

• 🗓️ Flexible Date Range Queries - Query data with customizable start and end dates.
  Developers can specify precise date ranges using from and to parameters in YYYY-MM-DD format, allowing tailored data retrieval from as early as 2000. This flexibility is perfect for applications requiring specific historical periods, such as studying market cycles or long-term investment returns.

• 🔐 Secure Authentication - Access data with a Base64-encoded application key.
  The API requires a T parameter for secure authentication, ensuring only authorized users can access historical data. This feature enables developers to confidently integrate the API into production environments, safeguarding sensitive financial applications.

Available Data Fields

Each API call returns a collection of historical stock data with the following columns. Always reference the columns array when parsing to ensure correct data mapping, as column order may vary.

JSON Response:

• The response is an object, containing the following keys:

Parameter	Meaning	Data Type
rows	A collection of historical stock data, with one row for each day of history	Array of Array
rows[...]	A single day of historical data for a security	Array
columns	The list of column names which correspond to each row	Array of String

Columns:

• Please make sure to reference the columns array when parsing the data - do not assume that the data in the rows will always be in a particular order.

Name	Meaning	Data Type
Date	Date	Unix Epoch Time (seconds since Jan 1, 1970 UTC)
Open	Open price	Double
High	High price	Double
Low	Low price	Double
Close	Closing Price	Double
Volume	Cumulative Volume	64 Bit Integer
Adjusted Close	Adjusted Closing Price	Double

Query Parameters:

Parameter	Meaning	Data Type
T	Application Key which authenticates you with cloudquote (required)	Base64 String
symbol	One symbol to look up (ex: GOOG)	String
from	The earliest date to retrieve historical data for (inclusive)	Date String - (YYYY-MM-DD)
to	The latest date to retrieve historical data for (inclusive)	Date String - (YYYY-MM-DD)

Use Cases

• 🤖 Quantitative and Algorithmic Trading - Backtest trading strategies with decades of historical data.
  Users can query extensive daily datasets to test trading algorithms, using fields like Adjusted Close and Volume to simulate long-term market conditions. This supports the development of robust strategies for risk management and performance optimization.

• 📈 Financial Dashboards & Portals - Create interactive charts with historical OHLC data.
  Developers can integrate API data to build visualizations like candlestick charts or trend lines, showcasing long-term price movements. This enhances user engagement on platforms by providing intuitive insights for investors tracking historical performance.

• 🧠 AI and ML Model Training - Train predictive models with comprehensive historical data.
  The API’s Adjusted Close and Volume fields enable data scientists to build models for forecasting price trends or volatility. By leveraging clean, long-term data, users can improve model accuracy for applications like market prediction.

• 📊 Portfolio Analysis & Benchmarking - Evaluate long-term performance against market benchmarks.
  Analysts can retrieve historical data for multiple securities to compare portfolio returns against indices, using Adjusted Close for accurate assessments. This supports strategic decision-making for asset allocation and portfolio rebalancing.

• 🔍 Investor Research Tools - Identify long-term trends and historical patterns.
  By leveraging fields like High, Low, and Adjusted Close, researchers can develop tools to uncover market trends, breakout patterns, or historical volatility, empowering investors to make informed decisions based on decades of data.

Why Choose FinancialContent's getPriceHistory API?

• 🚀 Rock-Solid Reliability - Dependable access with high uptime guarantees.
  Built on a fault-tolerant infrastructure, the API ensures 99.99% uptime, delivering consistent performance for mission-critical applications like trading platforms or analytics tools, even during peak market hours.

• 🔄 Seamless Data Integration - Combine historical data with other FinancialContent feeds.
  The API supports integration with real-time or intraday data streams, enabling users to create comprehensive solutions that blend long-term historical insights with current market updates for holistic analysis.

• 📈 Scalable Data Processing - Handle large-scale queries effortlessly.
  Designed for high-volume workloads, the API efficiently processes requests for extensive date ranges and multiple securities, making it ideal for enterprise-grade platforms analyzing thousands of tickers over decades.

• 📚 Developer-Centric Support - Comprehensive resources and expert assistance.
  FinancialContent offers detailed documentation, code samples, and responsive support to ensure smooth integration. From onboarding to advanced use cases, our team helps developers maximize the API’s potential.

Optimized for High-Speed Access

The getPriceHistory API is engineered for top-tier performance, adhering to industry best practices for efficient data delivery. Our RESTful endpoints use compact JSON formatting to minimize payload size, enabling fast parsing and reduced bandwidth usage. Advanced caching accelerates repeated queries, while globally distributed servers minimize latency for users worldwide. Rate limiting and pagination are optimized to maintain stability under heavy loads, and asynchronous request handling ensures smooth processing of large historical datasets. This performance-driven design empowers developers to build responsive applications with minimal delays.

Sample Request

GET /api/getPriceHistory?T=your_base64_key&symbol=GOOG&from=2020-01-01&to=2025-07-11

Sample Response (JSON)

{
  "columns": ["Date", "Open", "High", "Low", "Close", "Volume", "Adjusted Close"],
  "rows": [
    [1577836800, 1336.14, 1368.68, 1335.79, 1367.37, 1247200, 1367.37],
    [1577923200, 1367.09, 1378.24, 1358.04, 1360.66, 1182600, 1360.66],
    ...
  ]
}