MiFID II broadens the scope of the systematic internaliser (SI) regime, not only to cover more asset classes, but also to apply more stringent rules, with the aim of improving pre-trade transparency and improving price efficiency and client executions. To examine the far-reaching consequences and practical implications for liquidity seekers and providers, against a backdrop of tougher Best Execution […]
Discussion into possible use cases for deep learning within financial services, particularly in risk and investment management, as well as the challenges that arise from an infrastructure and data storage perspective.
The trend of financial firms – on both the sell side and the buy side – outsourcing their trading infrastructure to specialist providers at co-located data centres. The prospect of outsourcing such a vital part of a trading firm’s operations has enormous implications, from cost to performance to business models.
In this article we look at the future of middle-office systems for banks and trading firms. Many of these companies are now relying on hodgepodge solutions, systems that essentially rest upon legacy technology and have been in need of modernisation for years. Meanwhile, as regulatory requirements have increased, demands on middle office systems have risen. […]
The third video in our series on trade surveillance processes and technologies. In this we take a look at what the future holds, in particular how artificial intelligence, machine learning and behavioural modelling approaches can help predict and prevent manipulative or abuse market activity.
As firms prepare for new regulation, capturing and storing transaction data will no longer be enough. Regulators will also want to see granular data on quotes, accurately timestamped. This will present substantial technological hurdles. What kind of cost-effective solutions cans firms put in place, and what are the benefits to be gained by taking a […]
Francesco Lo Conte, Managing Director of Esprow, discusses challenges that firms face around the testing of trading algorithms under MiFID II, and lays out some best practices in how to address those challenges.
The use of Artificial Intelligence is becoming increasingly widespread in the financial services industry. Whether it’s in the research and development of trading strategies, analysis and management of risk, or assisting with regulatory and compliance functions, there are a growing number of use cases for AI and machine learning. What are the implications of this […]