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

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.