BMLL has moved to expand its regional Asia-Pacific offering with the launch of India equities trading data, The TRADE can reveal.
Level 3 equities data from the National Stock Exchange of India (NSE India) dating back to January 2021 and Level 2 data from the Bombay Stock Exchange dating back across the same period will now be available to BMLL clients via its Data Lab.
Paul Humphrey
The move comes as part of a continued expansion by BMLL, which has added several new regions to its offering in the last year.
India data, BMLL chief executive Paul Humphrey tells The TRADE, is in particular demand from US clients thanks to demand for trading in the region.
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“Many customers that we speak to find getting access to quality data in those markets problematic so we will have both venues at full depth in one harmonised format in our environment which we think will be somewhat unique,” he explained.
“When our team have been on the road show with our clients, one of the popular questions we get in the US is when are you adding India? They like trading there.”
Asia-Pacific has been of particular focus to BMLL as of late. Most recent in the data provider’s additions to its universe was the inclusion of China trading data in December last year. BMLL now offers a range of Level 2 or Level 3 data across the Hong Kong Stock Exchange, Shanghai Stock Exchange and Shenzhen Stock Exchange.
“We said it [China trading data] was unique and six months into it, clients are using that data that they can’t get anywhere else in that format,” said Humphrey. “There is a route where members can go directly to the exchange together for depth of course but that’s in raw format and that requires heavy lifting that really only a handful of firms in the world can actually perform.”
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The firm now offers data across venues in Europe, North America, South Africa and Asia Pacific including China, India, Singapore, Australia, and Japan.
BMLL buys the historic data in raw format from the source and then goes through the process of harmonising it on behalf of its clients.
“Our clients can see in the raw format so they know that we haven’t lost any of the data attributes, but we also present it in a consistent and normalised way without losing any of its attributes,” added Humphrey. “I continue to read comments about data reliability and consistency and that cleaning data almost certainly results in the degradation of data quality.”
“We buy our historic data from source – that’s a starting point direct from the matching engine or partner collects it for us. The less you start from this point, the less you can you hope to provide historical data with only minimal errors. We preserve all the row fields from the original data but we also have a normalised layer for managing trade condition codes, market states across multiple markets and regions.”