September 13, 2023


Exberry enables its matching engine customers to access BMLL’s granular venue analytics to understand how their venue compares to its peers.


Interesting times for stock exchanges lie ahead in the face of increased competition on a number of different fronts. Some are encountering competition from upstart ventures and having to spur activity by launching highly differentiated markets offering new asset classes.


Others are having to confront corporate listing expansion, including challenges of simultaneous “intralisting” on multiple exchanges. This is all occurring against a backdrop of exchanges – in Europe at least – faced with the imminent launch of a consolidated tape. The creation of such a consolidated price feed for trades across EU trading venues is expected to increase price transparency, thereby heightening scrutiny of the markets they provide.


With requirements to retain revenues and ideally increase them, exchanges are having to make efforts to increase market share and expand into new markets. But how can trading venues safeguard the success of these efforts?

Data is your friend

Long gone are the days of comfortable concentration rules, with today’s exchanges increasingly under competition by either national or international dual listings, or MTF-like structures upon which a listed security can be made available for trading on several venues simultaneously.

Additionally, start-up and established markets are increasingly launching alternatives, mimicking the offerings of local flagship instruments, and syphoning away much needed liquidity and revenues. The resulting situation is that stock exchanges need not only understand the complex details of these new competing markets, but the intricacies of their own offerings, as well as the types of products and services that will attract the end customer. 


By understanding markets in minute detail, exchanges will be better placed to interpret why and how liquidity is forming across different markets, and react accordingly. For example, to counteract the launch of a secondary market on a national level, an existing exchange should first establish if market share is actually growing and whether there is a general increase in trading. 


This detailed information can be gained by doing a deep analysis of granular historical market data. For example, a comprehensive understanding of which types of clients trade at which venues, or how the market reacts when an order is placed or trade executed will help gain a deep understanding of the inner workings of your market. The quality of the liquidity in both the markets of a venue and of its competitors can then be analysed in detail. Areas of improvement can subsequently be identified by working with market makers to improve liquidity, or offering better, more detailed explanations to banks, brokers and the buy-side about why deeper or better quality liquidity is occurring at a particular venue. Following on from this, exchanges can propose adjustments to the market via new or altered order types and rule changes in order to remain at the front foot of competition.


Another example comes in the form of increased international competition from multilateral trading facilities (MTF) or Alternative Trading Systems (ATS). Again, by performing an in-depth analysis of historical trading data at the most granular level that includes full market depth, or Level 3 market data, a better understanding can be gained of how exchanges rank against each other, and how the markets behave in reaction to internal and external factors, such as sweeping orders or large-in-scale trade publications (amongst others). For competing venues, the same analytics as described above can be used to compare the trading of similar instruments. Through modelling and testing, an exchange can understand if particular alterations could help improve a situation and drive liquidity to that venue, for instance, if an offering of a new order or execution type could increase participation, or if there would be merit in innovating and offering a completely new asset class. Moreover, access to granular data and a data science environment with a backtesting simulator could help model and predict the consequences of introducing a new order type in consultation with market participants. 


Ultimately, in order to perform these types of in-depth analyses, exchanges need access to detailed data reflecting market moves, liquidity profiles, spreads, order resting times and fill probabilities to their clients.

Granular venue analytics

BMLL is an excellent example of an independent data science provider of these data-led insights. Based on the most granular Level 3 historical data, BMLL’s curated data and the BMLL Data Lab environment are available to conduct scalable research and derive data insight. These help customers better understand the venue performance and gain confidence in the venue’s ability to attract liquidity.


Exberry now offers the BMLL ‘Data Science as a Service’ platform integrated out of the box, and available to its clients, removing the need for exchanges to build their own data engineering capabilities. Venues using Exberry’s matching engine and operating within the asset classes that BMLL cover, have access to BMLL-curated data and the BMLL Data Lab environment. In addition, Exberry makes it easy for venues who utilise the Exberry matching engine to have the ability to import their own datasets, that are stored within Exberry, into their BMLL environment for analysis via the various API’s that are offered out of the box. Essentially, Exberry customers can use BMLL’s granular venue analytics to understand how their venue compares to its peers, and to easily access data science insights to analyse how their venue interacts with the market to optimise venue positioning.


How the Exberry/BMLL integration works:

Simon Ellis, Head of Partnerships at BMLL explains, “The BMLL Data Lab provides users with more than 6.5 years of harmonised historical data from over 80 global venues, combined with easy to use APIs and analytics libraries in a secure, low-code cloud environment. Exberry exchange and marketplace customers can now access powerful data insights to monitor performance and ultimately demonstrate superior venue quality and liquidity.”

Decisive innovation in the face of competition

Exchanges need to act decisively in an increasingly competitive market, whether that is by offering a highly differentiated exchange targeting growth companies and alternative asset classes, or by competing against facilitated access to global capital and liquidity. 


Through the BMLL Data Lab, Exberry’s clients have immediate access to granular venue analytics and Data Science as a Service. Once exchanges have a chance to better understand liquidity dynamics and venue performance, they stand in much better stead to not only withstand competitive pressures and offer a definitive value proposition within the market, but also be confident in their delivery of new and innovative solutions to their clients.

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