Real-time market data for trading, analysis and automation – direct access to prices, tick data, the order book and history via a standardised interface.
Whether algorithmic trading, backtesting, market analysis or custom dashboards: market data APIs form the technical foundation of modern financial applications.
Schematic C# example · TPRAccess for .NET
A market data API provides market data via a programming interface (API). Instead of pulling data manually in trading software, applications retrieve and process the information automatically. Typical data sources:
Traditional trading software is excellent for manual analysis. Many professional users, however, need direct access to the underlying data – so that programs can react to market events on their own.
Different data types are available depending on the data feed.
Without relevant delay – for day trading, scalping, signal generation and market monitoring.
For backtests, quantitative strategies, order-flow analysis and high-frequency research.
Minute, hourly and daily prices and tick histories for developing and testing strategies.
Earnings metrics, revenue trends, dividends, balance-sheet and valuation figures.
DAX, MDAX, SDAX, Euro STOXX 50, Dow Jones, S&P 500, NASDAQ and more.
The TAI-PAN interface TPRAccess provides market data on a push basis for .NET / C# – from login and master data through the real-time feed to charts, market depth and the options matrix.
| Area | Function |
|---|---|
| Connection & login | Sign in via DevID & user credentials |
| Master data & search | Catalogue structure and symbol search |
| Watchlists | Manage your own watchlists |
| Real-time push feed | Push-based live prices |
| Candle & Intraday Charts | Historical and intraday price series |
| Market depth | Order book / Level 2 data |
| Options matrix | Option chains per underlying |
For many applications, delayed price data is not enough. In short-term trading in particular, even a few seconds of delay can be decisive.
Via a market data API, programs can receive market data, calculate signals, make trading decisions and prepare orders – reproducibly and at scale.
Before a strategy goes live, it should be tested against historical data. High-quality API data lets you validate trading ideas, optimise strategies, assess risk and calculate key figures. The better the data quality, the more reliable the results.
Many companies integrate financial market data directly into their systems – with automatic, continuous data supply. Typical projects:
Data can be integrated into almost any application.
Manual processes are reduced or fully replaced.
Usable from small projects to professional platforms.
Create your own metrics, indicators and models.
Data is available automatically and doesn’t have to be maintained by hand.
A powerful market data API should cover as many markets as possible.
Not every API offers the same quality. Key criteria:
Which asset classes and fields (prices, volume, market depth) the interface provides.
How quickly prices are available after the market event.
How far back the retrievable history goes for backtests and research.
Stable availability and transparent usage limits.
Good documentation significantly reduces integration effort.
Market data APIs are used today in numerous areas:
AI systems also need high-quality input data. The quality of the results depends directly on the quality of the underlying market data. API data can be used for:
Especially relevant for professionals – but ambitious private investors also benefit from automated data processes:
TAI-PAN provides the TPRAccess interface – a .NET/C#-based API with a push feed for real-time prices, master data, watchlists, historical data and market depth.
No, TPRAccess is a push-based .NET interface. Prices are delivered via callback as they occur, without constant polling – ideal for low-latency applications.
Real-time prices, tick data, historical price series, master data, watchlists, order book/market depth and the options matrix – for stocks, futures, forex and other asset classes.
Yes. The documentation with code examples and a downloadable .NET sample project are available at tai-pan.de/apis/dotnet-framework.
From real-time prices and historical tick data to fundamentals, almost all relevant market information can be processed automatically.
Anyone looking to develop strategies, automate processes or build professional financial applications needs a powerful market data API with high data quality, low latency and extensive market coverage.