Proprietary Market Data
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The Ultimate Guide to Proprietary Market Data 2020
Learn everything about Proprietary Market Data. Understand data sources, popular use cases, and data quality.
Table of Contents
What is Proprietary Market Data?
Proprietary trading is when a commercial bank or financial firm invests for direct market gain rather than trading on their client’s behalf to earn commission. The key here is that the financial institution is trading for personal profit rather than for their clients. Proprietary market data is intelligence about proprietary trading and the proprietary trading market. Businesses like to have access to proprietary market data so they can analyze trades and make well-informed investments. This is key because the proprietary trading market can generate much greater profits than when trading for commission even with a smaller investment.
How is Proprietary Market Data collected?
Proprietary market data is collected through a wide range of sources. Stock market research firms compile information about the different trading that takes place on a daily basis. The stock exchanges themselves are a main source of proprietary market data as it is here that the trades are made and the profits won. Data providers also use public records, specialized online services and brokers to aggregrate proprietary market data into one useful dataset.
As markets become increasingly digitized, much information is now stored and available online as raw market data. This is collected and used to populate the contents of a proprietary market dataset.
What are the attributes of Proprietary Market Data?
Due to the popularity of proprietary trading, data providers have developed proprietary market datasets to provide a range of different types of data. Therefore, you may find many different data points in a proprietary market dataset, including:
Real-time information - Some datasets provide real-time market data feeds across different trading venues, such as the New York Stock Exchange (NYSE) or NASDAQ.
Indices data - Index data for proprietary market datasets can include summaries, constituents and daily corporate actions data.
Historical market intelligence - This includes information about historical proprietary market details as well as post-trade analysis.
Reference data - This can be intelligence about company transaction activity or compliance risk management and provides a useful reference base for traders.
What is Proprietary Market Data used for?
Traders and businesses rely on proprietary market data to give them an insight into the current state of the stock markets. As these companies are trading on their own behalf and for their own profit, they want more than ever to have access to the most complete and informative datasets to ensure they make the best trades possible.
Proprietary market information can be used to analyze the market and recognize trends that are emerging in the market, both on a day-to-day basis and over a period of time. For this reason, many businesses look for proprietary market datasets that also provide historical intelligence.
Essentially, any person or entity who is in direct contact and making proprietary trades is likely to use proprietary market data as it gives them a key insight into the state of the stock market.
How can a user assess the quality of Proprietary Market Data?
A high quality proprietary market dataset will continue real-time and regularly updated market information. The variability of the stock market over the course of the day means that intelligence that is up to date with the latest information is essential. Historical data is equally important in a proprietary market dataset because this can be used to identify long-term market trends and highlight areas which might be more profitable than others.
Before you buy any proprietary market data, make sure to read the data provider’s reviews. Due to the wide range of data available, always ask for a data sample before purchasing to ensure that data meets your personal needs.