Market data contains all relevant information financial market participants require to carry out business. As such, market data includes data on instruments prices and related instrument infor- mation. The latest trading price for financial securities (i.e. equities, derivatives, currencies, or xed income), order book overviews and volume information are a few elds where security dealers and investors rely on market data for their decision-making when determining which instruments to buy and from where and from whom to buy them.
Even worse, without high quality market data, “market participants cannot meet regulatory requirements such as getting the best price on trades, reporting transactions and valuing assets”.
What Exactly Is Market Data?
By definition, market data is the published feed of data generated when securities are traded. Market data in its “raw” form can be divided into two categories:
- Pre-trade data as “all bids and asks at the venue”;
This is data leading up to a specific trade, i.e. the collection of tasks and bids for different instruments. Additionally, secondary pre- trade market data can be distinguished into two levels:
- Level 1 market data “contains the top of the order book, i.e. best bid/ask”, whereas
- Level 2 market data “contains the full order book, i.e. all bids and asks”.
- Post-trade data as “data on executed trades”.
Post-trade market data contains all the information about what was traded, when, at what price and volume, and between which participants.
Both pre- and post-trade data include the following information: price, volume, identification of the traded security (ISIN, WKN, etc.) and a timestamp.
Raw Market Data
The “raw” market data as above is simply described as a registry of all the activity of market participants. However, this raw market data is only relevant within a digital environment. If the data is to add value to human analysis, it requires processing.
At the simplest level of processing, the raw data is formatted in order to be displayed on screen. With more elaborate processing, the data can be used to compare and analyze financial markets and instruments.
Hence, raw data can be further processed into meaningful market data, useful to analyze individual instruments (for instance the average pricing, volatility, total traded volume), or more aggregated measures (i.e. the total trading volume across different trading venues, price initiatives, or the volatility of a specific type instruments).
The Boom of Market Data Businesses
According to a recent Burton-Taylor International Consulting report, the global spending on financial market data, analysis and news reached an historical high in 2018, when the global spend broke the US $30 billion mark.
The report shows that all three major trading regions (Americas, Asia and EMEA) experienced strong growth in the previous year, averaging an outstanding 7%.
A key reason for this growth was the high demand of market data by Risk and Compliance users, but is reflected in a 9.5% compound annual growth rate (CAGR) over the past five years. Here, Pricing, Reference & Valuation products as well as Portfolio Management and Analytics products were the biggest drivers for growth with an average annual growth rate of 12.2% and 8.9% respectively.
With that in mind, the biggest winners of the demand for market data are Bloomberg, Refinitiv (combined with Reuters News), S&P Global Market Intelligence, Moody’s Analytics and FactSet Re- search Systems. S&P Global Market Intelligence, Moody’s Analytics and FactSet Research Systems.
“At 32.5%, Bloomberg continues to command highest revenue share and man- aged to increase terminal counts by over 5,000 users”, Burton-Taylor stated.