Creating a fully cross-border infrastructure is a priority for Euronext in it's as it looks externally for growth opportunities, according to the stock exchange’s CTO.
“Really the idea is to move from an exchange to a full market infrastructure,” says the exchange’s Alain Courbebaisse. “Our approach would be to prepare the next potential acquisition by creating a geographical agnostic kind of post-trade infrastructure exactly as we did for the trading infrastructure with Optiq that is dealing today with Paris, Amsterdam, Lisbon, Dublin, and Oslo soon.”
“The difficulty of M&A is that it is something that you cannot predict,” says Courbebaisse. “You need assets to be available for you to look at them, so we are scrutinising the whole market and we are kind of very determined and ready for any opportunity that will allow us to achieve, either more diversification in terms of asset class, more diversification in terms of geographies and more diversification about revenue. So really reinforcing a subscription kind of revenue service to corporate data, so we are very opportunistic.”
Euronext announced its three year strategy in October, with an aim to creating operational efficiency through an integrated technology backbone. The stock exchange is in the process of migrating all of its infrastructure to cloud, with step three of the integration to the exchange’s Optiq platform set to go ahead at the end of November. The firm has invited its customers to test the order entry gateway and matching engine on all derivative market segments during a dress rehearsal of the system on November 9.
Pillar four of the strategy focuses on operational excellence. This, Courbebaisse says, will force the exchange “to streamline and re-engineer all processes with the goal to deliver them as close as possible to the customer.”
Part of the strategy focuses on improved data management - in particular market data analytics.
“We have a lot of data analytics, and new services that we want to develop and propose to our customers that will really leverage our big data, artificial intelligence, machine learning kind of setup,” says Courbebaisse. “As any kind of exchange we do have a decent revenue with the market data but we want to go one step further and propose even better and more analytics to add to our customers, to our issuers, mixing structured and unstructured data, using the data to create smart indices
Creating smart indicies will require the use of deep learning, according to Courbebaisse.
“If you work on established indices in order to back trade them and so on, and to fine tune the indices, this is a perfect illustration of what deep learning can do because you do have a historical series, you do have a model and you can really have a deep learning process that will backwardly try to optimise the composition of the indices."