The global exchange environment is on an exciting trajectory as securities exchanges and other players in the financial services industry are adjusting the way in which they operate in response to changing regulatory requirements and the fast pace of technological developments and other innovations.

Financial markets are defined by data. Share prices, indices, spreads, bids and offers – the global capital market system not only represents billions of dollars flowing across the globe, but also billions of pieces of information. Billions of data points.

Given the vast amounts of data generated in the capital market industry, it seems counter-intuitive that we appear to be lagging behind other industries in terms of our ability to fully leverage this data. Until recently, much of the innovation in the financial services industry, described as the rise of ‘fintech’, has focused either on automating or simplifying the provision of services or connecting market participants in new ways. Crowdfunding platforms now connect investors to small businesses, while robo-advisers are automating the provision of investment advice.

I recently attended the World Federation of Exchanges (WFE) working committee meeting and this narrative dominated the conversation from all corners of the globe. This digital disruption, coupled with the technology that underpins it, also presents new opportunities, especially in terms of how we source and analyse the vast amounts of data at our disposal.

A recent white paper released by New York’s Nasdaq stock exchange argues that fintech applications are driving a seismic change in the use of data in the capital market industry. Nasdaq believes that ‘the ability to mine and normalise data, update analytics in real time and present it in a consolidated view’ will soon become a crucial competitive advantage.

This ability will bring together developments known as the rise of big data, artificial intelligence and machine learning.

Big data refers to far more than just vast amounts of numbers. It includes unstructured data such as video, email and text messages, social media and voice data. Artificial intelligence and machine learning are in essence advanced statistical models that are applied to evolving datasets. These models can themselves evolve in response to the changes the data exhibits, and they can combine data from various sources to enhance real-time understanding of events.

For example, applications are able to collect data from news media, blogs, stock market news feeds such as SENS and real-time trades to give investors greater insights when making investment decisions. Companies such as StockTwits, Dataminr and Scutify in the US and TheySay in the UK are already analysing social media across different channels to provide clients with indicators of investor sentiment.

Ultimately, all of these new technological applications provide new ways to analyse and interpret those factors that we know influence markets, but until now have been unable to express or quantify – factors such as market analysts sharing their views through research reports or media interviews, or traders discussing market movements on Twitter. In the past we may have attributed these to the realm of ‘animal spirits’, but machine learning can now allow us to detect and follow patterns that the human brain would not have been able to detect otherwise.

During the previous wave of technological disruption in the capital market industry, online trading and market news services such as SENS helped ensure that market-moving information was released to all market participants at the same time. This increased market transparency and reduced information asymmetry, much to the joy of regulators. But markets may soon be characterised by a new form of asymmetry – that of insights.

In a world where all trading happens based on real-time online data feeds, investors have more information than ever before. In this market, access to information will no longer be what gives traders or investment managers the edge to generate the best returns for clients. They also need to be able to interpret these vast amounts of information as quickly and insightfully as possible.

As always, these market trends will not only be shaped by technological innovation but also by the regulatory environment in which they are implemented. In Europe, the financial sector is preparing for the implementation of the second iteration of the Markets in Financial Instruments Directive (MiFID II) in January 2018. The MiFID regulation will, among other measures, force investment houses to unbundle their research functions from the execution of trades on behalf of clients. This will no doubt force all market participants to reconsider the true value of the research they are producing or buying. The answer will soon depend on one question: does it truly leverage the universe of data at our disposal?

Nicky Newton-King
Chief Executive Officer

July 2017
Image: Wilnicque Rall