| Of relevance to: | All firms carrying out algorithmic trading in wholesale markets |
The Financial Conduct Authority (“FCA”) and Prudential Regulation Authority (“PRA”) have been reviewing firms’ algorithmic trading activity and issued supervisory publications. For firms solo-regulated by the FCA, please refer to the FCA supervisory publication. Firms regulated by the PRA and FCA should refer to both supervisory publications.
Firms operating in wholesale markets increasingly use algorithms for a number of purposes across their trading activity. In particular, driven by the rise in electronic trading platforms and the increased availability of data, algorithms are now often used for making both execution and investment decisions.
Investment decision algorithms make automated trading decisions by determining which financial instrument should be purchased or sold.
Order execution algorithms optimise order-execution processes by automatic generation and submission of orders or quotes, to one or several trading venues once the investment decision has been taken.
It is essential that key oversight functions, including compliance and risk management, keep pace with technological advancements. In the absence of appropriate systems and controls, the increased speed and complexity of financial markets can turn otherwise manageable errors into extreme events with potentially wide-spread implications. As a result, algorithmic trading continues to be an area of focus for the FCA and other regulators across the globe.
The FCA supervisory publication highlights examples of good and poor practice observed during their cross-firm reviews on themes relating to algorithmic trading, ahead of the implementation of the Markets in Financial Instruments Directive (“MiFID II”).
There are examples of both good and poor practices highlighted in this report. The good practices present ways, but not the only ways, in which firms might comply with applicable rules and requirements, whereas the poor practices highlight areas where firms would now need to do further work to comply with the applicable requirements.
It is apparent firms have taken steps to reduce risks inherent to algorithmic trading but the FCA notes that firms need to do more work to identify and reduce potential conduct risks created by their algorithmic trading strategies.
In the UK, the algorithmic trading requirements were introduced through Chapter 7A of the Market Conduct Sourcebook (“MAR”). Further specification is provided in the European Commission Delegated Regulation 2017/589 of 19 July 2016 (also known as RTS 6).
The FCA will continue to assess whether firms have taken sufficient steps to reduce risks arising from algorithmic trading. These will include MIFID II investment firms and those non-MIFID investment firms, such as collective investment firms engaging in algorithmic trading, which are subject to the relevant requirements under Article 17 of MiFID II.
Key areas of focus
The FCA has identified five key areas of focus, based on the combined findings of the reviews, and with consideration of MIFID II requirements. They cover:
- Defining algorithmic trading
Key objective: To ensure firms establish an appropriate process to identify algorithmic trading, manage ‘material changes’ and maintain a comprehensive inventory of algorithmic trading across the business. - Development and testing
Key objective: To ensure firms maintain robust, consistent and well understood development and testing processes which identify potential issues across trading algorithms prior to full deployment. - Risk controls
Key objective: To ensure firms develop suitable and robust pre- and post- trade controls to monitor, identify and reduce potential trading risks across algorithmic trading activity. - Governance and oversight
Key objective: To ensure firms maintain an appropriate governance and oversight framework which demonstrates effective challenge from senior management, risk management and compliance on algorithmic trading activities. - Market conduct
Key objective: To ensure firms appropriately consider the potential impact of their algorithmic trading on market integrity, monitor for potential conduct issues and reduce market abuse risks.
