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What is front of mind at Man Group for the remainder of the year when it comes to innovation in algo execution technology? Two key pillars of Man Group’ s strategy are to further develop our mid-frequency equities capabilities and to grow the size of the firm’ s credit business, both of which impact our approach to algorithmic execution.
For equities, the focus is on providing our researchers with the right toolkit to analyse new, rich datasets to extract idiosyncratic features and develop innovative trading strategies. Our aim is to reduce trading costs and unlock capacity for investment strategies. Data is one part of the equation and speed is the other. We are also focusing on improving the responsiveness of our systems, reducing tick-to-trade latencies, and selecting the right data centres to deploy our strategies. In recent years, Man Group has invested heavily in its Man Execution Algos( MEA) platform. It now hosts algorithms across equities, futures, options and credit. Investment through mid-frequency equities is enabling us to push the frontier with respect to the platform’ s trading and research capabilities.
The growth of the credit business is driving automation and smarter dealer selection logic. Capturing quotes and trades feeds and developing the tools that allow their easy introspection are primary objectives for the team this year. These will lay the foundation for the algorithms we aspire to build.
What is the business case for consolidating systems? Centralised capabilities are a key tenant of Man Group’ s Central Trading function, which was established in 2018 with the aim to deliver best-in-class execution to all investment divisions. Leveraging these capabilities across different asset classes and investment engines allow us to stay nimble and reduce the cost of entering new markets or for building proprietary algorithms for non-traditional markets. This is evidenced by the growth of our central execution algo platform which started off with a focus on equities but now hosts algorithms for most of the asset classes we trade.
Consolidation also provides an opportunity to continually adopt best practices from across the firm. A primary goal of our consolidation efforts is to support the growth of our business by reducing risk. By unifying alerting, order monitoring, and algorithmic controls into a comprehensive framework, we can expand into newer asset classes and support different trading styles in safe and scalable manner.
I firmly believe that reducing cognitive loads fosters innovation. Consolidation focuses efforts on strategic goals and makes
System consolidation as a strategic focus
The TRADE sits down with Man Group’ s head of algo execution technology, Pranav Malhotra, to explore the firm’ s future algorithmic strategy and the importance of consolidating systems to reduce cognitive loads.
best use of our engineering talent. The strong business case for consolidation is driving two large projects across our trading technology teams – the unification of various investment management specific order management systems( OMS) and execution management systems( EMS) functions into a centralised Man OMS and a centralised Man EMS.
How can desks best develop a unification layer on top of existing systems? What are the benefits of doing so? In my opinion, the key to building a unification layer is to have access to the right data. Applications within our execution systems can emit structured data, detailing how an order is transformed. Historically this data has been asset class specific, but we have built a normalisation layer and made it accessible via a centralised trading analytics platform.
A normalised view of trading activity provides enhanced visibility for our desk and enables the analysis of key execution metrics which are used in turn to refine our trading strategies. Our normalised access layer allows us to scale analytics capabilities built for one asset class across to others.
There are various interoperability technologies in the market that can be helpful when trying to build unification layers for desktop applications. We are constantly evaluating, and where applicable incorporating, the right tool for our use case.
How feasible is it attempting to consolidate analytics capabilities across asset classes and is this something your desk is trying to achieve? The foundations of our analytics platform are capabilities that are asset class agnostic. The high-level themes that we focus on are benchmarking, mark outs, experimentation frameworks and analytics tools for our proprietary algorithms.
A centralised team and focus on highly transferrable themes allow us to operate a consolidated analytics platform. We lean on deep expertise from within Man to understand the nuance of each asset class that we onboard to this platform.
Analytics for credit has been a focus for the team more recently, driven by our ambitions to grow in this space.
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