Building a successful multi-asset trading desk

The TRADE sits down with Sunil Patil, senior trader at APG Asset Management, to discuss how to succeed in a multi-asset trading environment, exploring technology implementation, data optimisation, and the intricate puzzle of TCA.

What is the principal consideration for desks when looking at the merging of asset classes?

In multi-asset trading, merging desks can be a viable option if the desks’ flows are not heavily reliant on specialisation and can benefit from a broader understanding of the market. It is crucial to have sufficient overlap in trading tools, knowledge, and interests for a successful integration. It’s also of prime importance that in the process of merging there’s still at least one trader who acts as a specialist and single point of contact to ensure accountability.

Based on our experience of merging desks, there are clear advantages in fostering the exchange of ideas and optimising desk staffing, leading to improved overall performance and effectiveness of the merged desk.

When looking to build a talented multi-asset desk, what is the main thing you look for?

Operating a successful multi-asset trading desk demands not only deep subject matter knowledge but also a delicate balance of technical and quantitative expertise. Constantly evolving and innovating trading tools and processes is a necessity to avoid falling behind and mitigate the risks of complexities and errors. Whether it’s a principal or agency desk, we place a lot of importance on minimising avoidable errors and maintaining a high standard of performance, with adherence to benchmarks and execution policies.

In the contemporary trading landscape, comprehensive trade analysis and support form an integral part of the trading desk’s responsibilities. Any trade is incomplete without a meticulous pre- and post-trade analysis. The advantages of a multi-asset desk become evident through the synergies derived from different asset classes. Some asset classes may outpace others in terms of available data and trading technology, pointing to potential avenues of development for the rest.

How does the multi-asset aspect affect which technologies you employ, and workflow processes you prioritise?

Dealing with multiple assets presents a complex challenge with no one-size-fits-all solution currently available. Two main approaches emerge: building a platform from scratch, though costly and resource-intensive, or leveraging multiple solution providers to combine resources and technologies, which appears more favourable for asset managers facing resource constraints.

At APG, a strong emphasis is placed on adopting forward-compatible technologies and tools to avoid deploying solutions that may become outdated within a few years. Additionally, there is a significant focus on self-development of code and processes atop basic infrastructure. After years of focus on digitisation, we now have a thriving community of quants and developers. This community serves as a hub for sharing insights and offers various pathways for collaborative learning.

Regarding process prioritisation, relevant desks have the authority to make judgments unless the decision affects multiple desks. In such cases, a more democratic approach is taken, and every aspect is thoroughly analysed. Ultimately, client needs, and robust policy frameworks steer us in prioritising tasks and ensuring our commitment to excellence.

How can data be optimised/aggregated to make multi-asset trading more efficient?

This is probably the holy grail of a modern multi-asset trading desk. The key lies in prioritising data standardisation, ensuring seamless data collection, mapping, and cleaning processes across diverse asset classes. Integrating data from order management systems (OMS) and execution management systems (EMS) needs further augmentation with market tick data sourced through various APIs. Integrating ‘alternative data’ on top of this adds an interesting dimension, expanding analysis possibilities.

Data usage licenses bring significant challenges, necessitating careful consideration when choosing the right data provider to avoid unexpected and substantial data costs. Similarly, the design of the data architecture poses another hurdle, as data dispersion across different silos can lead to cumbersome interactions, extractions, and potential system unreliability. Ensuring a cohesive and well-organised data architecture becomes crucial to facilitate efficient data handling and minimise any possible disruptions.

Even with a robust architecture and a reliable data provider in place, the data must undergo thorough cleaning and mapping to be effectively utilised for meaningful tasks and analysis. This data refinement process is critical to derive valuable insights and optimise decision-making. In the end, your analysis is only limited by the resources you throw at it and it’s really a never-ending quest.

How does being multi-asset impact your use of TCA?

TCA is a vital task for any trading desk, and in the world of multi-asset trading, it becomes even more intriguing. Each asset class has its own unique quirks and complexities, so we need tailored data analysis processes, benchmarks, and parameters for each one. TCA for FX will be totally different from TCA for cash equities, for example. 

To tackle this intricate puzzle, we rely on multiple TCA providers alongside our in-house tools and methodologies. Over the years, we’ve put in the effort to select the best benchmarks and practices, shaping an approach that works best for us. At APG, TCA isn’t just a regulatory requirement; it’s also a smart way to improve our trading desk’s performance and overall efficiency. Think of it as a low hanging fruit and the ROIs are huge.