What is Trading Data? Definition, Uses, Datasets & Vendors

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Eugenio Caterino
Editor & Data Industry Expert

What is Trading Data?

Trading data is a sub-category of financial market data. It provides real-time information about stock and market prices as well as historical trends for assets such as equities, fixed-income products, currencies and derivatives. Trading data also includes information about trades historically and over the course of a trading day, such as the latest bid, asking price and time of the last trade.

Best Trading Datasets & APIs

5.0(1)

Bitcoin Price Data - Kaiko Market Data. CeFi & DeFi | Historical and real-time Bitcoin prices | OHLCV | Trading volume | VWAP

by Kaiko
Available for 250 countries
260K Derivative contracts including options and futures.
10 years of historical data
99% API Uptime
Available Pricing:
Monthly License
Yearly License
Usage-based
Free sample preview
20% revenue share
Available Pricing:
One-off purchase
Monthly License
Yearly License
Usage-based
Free sample preview
Available Pricing:
Yearly License
Free sample preview
revenue share

CoinAPI: Crypto Trade Data | Trade-by-Trade Data | Real-Time & Historical | Trading data | 350+ Exchanges | CEX & DEX

by CoinAPI
Available for 250 countries
350 Exchanges
14 years of historical data
99% API Uptime
Starts at
$1 / purchase
Free sample preview

Social Pulse - real-time crypto data stream for quantitative trading

Available for 53 countries
100 crypto assets
1 years of historical data
Starts at
$1,500$1,350 / month
10% Datarade discount
1% revenue share
Pricing available upon request
Pricing available upon request

Risklio Event-Aware Trading Insights | US Stock Sentiment & Equity Market Insights

by Risklio
Available for 1 countries
28.5M texts
5 years of historical data
Pricing available upon request
Available Pricing:
One-off purchase
Monthly License
Yearly License
Usage-based
Free sample preview
Pricing available upon request
Free sample preview

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Top Trading Data Providers

Trading data providers supply real-time and historical information relating to stocks and securities traded on various global financial exchanges.

Trading Data Use Cases

Trading Data Explained

How is Trading Data collected?

Trading data is typically collected from stock exchanges such as the New York Stock Exchange (NYSE) or NASDAQ. This can be a useful source for trades that are made over the listed exchanges and can provide many different data poitns, such as trade prices and times.

However, some trades are unlisted, such as OTC trades, meaning they do not take place on the formal stock exchange. Information about these is harder to collect, but can be found in announcements and reports from the brokers and buyers themselves or from public records.

What are the attributes of Trading Data?

Typically a trading dataset will provide information about trades that are made over the course of the day. This includes various different details about the trades, such as the bid, bid size and ask size. This information is known as quote data.

Another attribute is information about recent sales, such as the latest sale of the size of the asset sold as well as the exact time the trade was made. A trading dataset will also tell you which exchange the trade was made on, such as the NYSE or NASDAQ. This information is called trade data.

A trade dataset will also often include historical trade data, such as trades that were made on the same exchange or that relate to similar commodities. This information is useful for identifying market trends and market predictions.

What is Trading Data used for?

Investors and traders rely heavily on trading data to inform their trading decisions. They use current market rates and historical data in conjunction to predict the most successful trades that will generate the highest amount of profit.

Market research agencies also use trading data to carry out market data analytics. This can be sold on to traders and investors who trade without brokers and don’t enter the financial and stock market data themselves. Market research agencies use trading data to compile useful reports that can be used to make well-informed trading decisions.

In-house analysts rely on trading data to forecast how the stock market may change in the future. They then pass this information on to investments and traders who will have hired them to do the research on their behalf.

How can a user assess the quality of Trading Data?

Due to the quickly evolving nature of the stock market, the best trading datasets will provide information which is constantly and consistently updated to match this. Investors and brokers need information that is accurate and up-to-date and the highest quality trading datasets will match this need.

It is equally important to ensure that the trading dataset provides historical information so you can perform market analysis and identify market trends in order to make the most well-informed deals when it comes to the stock market and trading.

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