FMP
Jan 05, 2026
The transition from manual market observation to systematic data analysis requires a shift in how you view information architecture. Professional workflows are not built on isolated data points but on a cohesive progression of discovery, validation, and visualization. By following a structured pathway, you move from the initial curiosity of finding a specific ticker to the high-level capability of managing production-ready dashboards and complex valuation models.
This guide serves as an onboarding roadmap designed to build your confidence as you navigate the FMP ecosystem. You do not need to read these sections linearly; instead, you can jump directly to the segment that matches your current analytical hurdle or development requirement. Whether you are a new user establishing your first API connection or an intermediate developer refining a multi-asset monitor, these resources provide the technical logic and specific endpoints required to execute your strategy with precision.
The first milestone in your journey is establishing a clean universe of tradable assets. Confidently identifying the correct ticker, exchange, and asset type is the prerequisite for any reliable data request. Without a verified list of symbols, analysts risk data drift, where models pull information from dual-listed ADRs or OTC markets when they intended to target primary exchange listings.
The guide on how to find company and exchange symbols with FMP explains how to use search logic and metadata verification to resolve these ambiguities. By the end of that resource, you will have the ability to filter for specific instruments like ETFs or common stocks across global markets, ensuring your downstream models operate on a foundation of total data integrity. This stage of the learning path is about removing the Day Zero uncertainty that often slows down financial development projects.
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API Name |
Endpoint Description |
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Searches for ticker symbols, company names, and exchange details for equity securities and ETFs across global markets. |
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Provides a comprehensive list of all supported global stock exchanges to identify exactly where specific securities are traded. |
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Retrieves a complete directory of global stock market indexes, including symbols, names, and their respective denominations. |
Once you have identified your symbols, the next capability involves gaining visibility into live market movements. Professional data management involves more than just seeing the latest price; it requires understanding the metadata surrounding the trade, such as bid/ask spreads and volume spikes. The guide on how to get real-time market data and quotes provides a confidence-building pathway for users moving from static research into active monitoring.
For many users, this section is relevant for simple yet essential use cases like basic portfolio tracking, monitoring price movements in real time, or setting up basic price alerts. For more advanced institutional or high-frequency workflows, the guide demonstrates how to implement batch quote endpoints to calculate intraday exposure without the heavy infrastructure burden of a full-scale tick-by-tick feed. This ensures you can monitor 50 or 500 positions with the same level of accuracy and network efficiency.
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API Name |
Endpoint Description |
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Delivers up-to-the-minute prices, daily changes, and volume data for individual stocks to support live market monitoring. |
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Allows users to retrieve real-time quotes for multiple stocks in a single request for efficient portfolio tracking. |
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Provides end-of-day price and volume data adjusted for dividend payouts to offer an accurate view of historical stock performance. |
Analyzing the past is the only way to validate a strategy for the future. By following this how to get historical market data and why it matters for model validation foundational guide, you gain backtesting confidence, accurate return calculations, and the ability to conduct reliable trend analysis over long time horizons. The goal here is to move beyond raw numbers and understand the mechanics of data adjustment.
A 10 percent jump in a stock price might be a genuine market move, or it might be an unadjusted 2-for-1 stock split. Historical data must be adjusted for corporate actions to be useful for any serious model validation. The guide covers how to pull full price histories and intraday bars while accounting for the splits and dividends that skew performance metrics. This ensures that your backtests reflect the true economic reality of the market rather than data artifacts.
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API Name |
Endpoint Description |
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Delivers full historical end-of-day price data including open, high, low, close, and trading volume for any stock symbol. |
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Enables users to analyze stock performance with dividend adjustments factored into the end-of-day price series for total return calculations. |
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Provides comprehensive historical end-of-day prices for stock indexes, including metrics such as volume-weighted average price. |
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Supplies essential financial performance indicators like P/E ratios and net income to assess a company's valuation relative to its history. |
Price action is a trailing indicator that reflects fundamental reality. To make informed decision-making outcomes—such as screening for quality, conducting peer comparisons, or performing a thorough financial health assessment—you must move from price data into fundamentals. This stage of the learning path is where you learn to extract the underlying drivers of a company's growth or distress.
The guide on how to access company financial statements for deeper analysis walks you through the process of extracting income statements, balance sheets, and cash flow statements directly from corporate filings. By programmatically pulling these figures, you can automate the calculation of margins, debt ratios, and free cash flow. This removes the manual entry errors inherent in reviewing PDFs and allows for a faster, more objective comparison across an entire sector or asset class.
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API Name |
Endpoint Description |
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Provides standardized revenue, expense, and profit data over annual or quarterly periods directly from corporate filings. |
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Details a company's assets, liabilities, and shareholder equity to help analysts assess capital structure and solvency. |
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Tracks the movement of cash through operating, investing, and financing activities to reveal a company's true liquidity. |
This is the capstone moment of your foundational journey, where symbols, real-time prices, historical context, and fundamental reality all come together into a single, visual interface. A chart is only as good as the data alignment behind it; if your time-series are not normalized to the same frequency, your comparative analysis is invalid.
The guide on how to get data to build market charts and dashboards focuses on preparing your datasets for integration into front-end charting libraries or BI tools. You will learn how to structure JSON responses into the arrays required by modern visualization packages, ensuring your internal tools provide a clear and accurate representation of the market data you have meticulously collected and validated in the previous steps.
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API Name |
Endpoint Description |
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Provides the exponential moving average of a security's closing price to identify short-term price trends. |
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Supplies the daily OHLC prices and volume needed to construct historical candlestick and bar charts for technical analysis. |
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Delivers detailed intraday data at one-minute intervals, including price movements and volume spikes for high-resolution charting. |
Establishing a market data foundation is an iterative process. Once these core workflows are integrated, the next phase involves refining your models with specialized data. The FMP Blog offers extended resources for moving into advanced territory, such as sector analysis, economic indicator tracking, and sentiment modeling.
You might consider exploring our guides on sector performance snapshots to identify macro shifts or tutorials on tracking institutional 13F filings. These advanced resources build upon the foundational elements described above, allowing you to layer market sentiment and alternative data into your existing analytical environment.
These five guides represent a complete lifecycle for market data management, but their true value lies in the confidence they provide to you as a reader. You now understand where to start, what each dataset is for, and how these guides fit together to form a reliable analytical architecture. By following this path, you transition from searching for basic symbols to managing a fully realized market dashboard, spending less time cleaning data and more time deriving insights. We invite you to implement these foundational pieces to create a reliable, scalable infrastructure for your financial research and trading operations.
You can use the FMP Company Name Search API to query by the company's name; it returns the matching ticker symbol along with its primary exchange details.
Yes, the Stock Price and Volume Data API provides full end-of-day prices, and the Dividend Adjusted Price Chart API specifically accounts for dividends and splits for accurate backtesting.
The FMP Batch Quote API is specifically designed for this purpose, allowing you to fetch the latest prices and volume for a list of symbols in a single request.
Standardized APIs eliminate the manual errors and latency associated with reading filings, providing machine-readable data directly for modeling.
Yes, the 1 Min Interval Stock Chart API provides high-resolution data at minute intervals, which is essential for day traders and algorithmic strategies.
Data is delivered in JSON format, which is compatible with all modern charting libraries and BI tools, making the integration process straightforward.
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