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.