Tick Data Comes to BigQuery
A huge batch of tick data, used by financial traders to track the minimum upward or downward movement of stock prices, has been added to Google Cloud Platform, allowing financial analysts to plug pricing and trading data into the cloud vendor’s BigQuery cloud data warehouse.
Refinitiv, a London-based fintech provider, said its “Tick History” data set includes historical data gleaned from real-time trades, including transactions from more than 500 exchanges dating back to 1996. The combination of historical tick data with BigQuery’s machine learning capabilities would allow traders to construct and test trading strategies while complying with financial regulations, the partners said Tuesday (Feb. 11).
Refinitiv said tick data accessible via BigQuery also would enable analysts to interpret trading patterns and develop new algorithmic trading models while saving time and money on data management and regulatory compliance. Among the competitive advantages of the combination is a reduction of data movement since trading would not have to be loaded into an analytics engine. Elimination of data preparation tasks would allow data scientists and quantitative analysts more time to develop and test new trading algorithms, the partners said.
The fintech partnership underscores how AI-based analytics and ever-larger sets of historical trading data stored on cloud platforms are automating financial markets. A recent studyforecasts the global algorithmic trading market will grow at an annual rate of about 10.3 percent through 2022.
A separate report by Refinitiv found that 64 percent of companies it surveyed said cloud data management would play a larger role in their operations over the next five years. “Combining Google Cloud’s machine learning tools with Refinitiv’s Tick History data in BigQuery is a step-change for customers looking to develop new trading models,” said Catalina Vazquez, a director at Refinitiv.
The archive of historical tick data is drawn from real-time transactions. Refinitiv said its Tick History platform delivers data on 70 million active and retired securities. A web-based user interface and REST API are used to provide on-demand delivery of 22 years of trading data. A drill-down capability allows users to test algorithms and uncover trading insights.
Recent surveys of the booming fintech market found that financial services vendors are embracing cloud-based analytics that allow them to control sensitive data in-house while leveraging public clouds like Google’s (NASDAQ: GOOGL) to provide cheap access to computing and storage. The addition of access to BigQuery ups the ante by eliminating data movement and accelerating data delivery.
Along with analytics engines, fintech vendors specializing in areas such as real-time intelligence tools for trading and risk management are also deploying graph databases to next-generation trading platforms based on standard components like Python.