Buy-Side Technology Comes of Age

Jon Glennie, Global Head of Equities Trading Technology at J.P. Morgan Asset Management

Jon Glennie, Global Head of Equities Trading Technology at J.P. Morgan Asset Management

A leading technologist from one of the world’s largest asset managers notes the impact cutting-edge technology is having on the buy-side trading desk

Briefly discuss your current role and responsibilities at J.P. Morgan Asset Management?

I am the Global Head of Equities Trading Technology and in this role I am responsible for the full end-to-end technology tooling supporting our four trading desks around the world to manage orders, access market liquidity and analyze trading performance.

How has technology changed during your years in the business?

Historically, much of the investment and innovation in the broader financial services industry has been on supporting sell-side trading desks as the markets they support become increasingly electronic. Whilst the technology innovation in the sell-side has not died away, the buy-side has started to realize the benefits to their operations and ultimately their clients by investing in technology and developing more innovative technology solutions to the aid the performance of their trading desks.

From my perspective the biggest mind-set shift the industry over recent years, has been the realization of how technology and great technologists can benefit the large institutional buy-side.  Here at J.P. Morgan Asset Management, we have gone the step further by integrating technology and technologists into the trading function, where we have software engineers sitting side-by-side with traders in all of our trading locations.  This tight knit, one team mentality, helps the engineers better understand the trading function and quickly innovate to develop new solutions that optimize our trading platforms. 

Ultimately, we operate as one trading function with the common objective of achieving the best trading outcomes for our clients.

What are the main innovation trends shaping institutional equity trading currently?

I see two common themes in buy-side trading technology – understanding how to leverage and harness increasing volumes of data to make more informed execution choices, and how to streamline the trading workflow. 

At J.P. Morgan Asset Management we have been driving innovation in both spaces.  For our low touch flow that is typically algorithmically traded, we have been increasingly leveraging machine learning techniques and applying them to our past execution data.  This process allows us to provide a recommendation on which broker and execution strategy to trade a particular order with.  Critically, with the sell-side evolving their execution algorithms all the time, our in-house built model continuously learns from traders and trading data inputs to refine this recommendation.

In certain markets, the smaller more routine orders are fully automated, which allows traders to add value to the larger and less routine flow hitting the desk.  For larger orders, which may follow multiple execution strategies, data and analytics are able to provide insight into where liquidity might be best sought.

Additionally, industry-wide I can see consolidation onto fewer trading technologies to help ensure a globally consistent and streamlined workflow in trading organizations.  For us at J.P. Morgan Asset Management we have moved all our flow to Spectrum Trading, our in-house-built unified OMS, Trading Automation and Analytics platform.  This shift has provided traders with the tools to manage, monitor and analyze the $1.3tn of order flow that we trade annually in a single integrated platform.

What are the associated challenges/opportunities for the buy-side?

As the buy-side embraces technology innovation more, there is the ongoing challenge associated with attracting the very best technologists to our industry.  Historically the buy-side technology teams have implemented vendor platforms or worked using now legacy technologies, which may have hampered recruiting efforts in the past.

I moved to the buy-side relatively late in my career and now three years into the journey I genuinely believe some of the most innovative and transformational technology initiates in financial services are now on the buy-side and in revolutionizing how the buy-side trading desk operates.

What are the focus areas for buy-side resource allocation, in 2019 and looking ahead to 2020?

For the coming years I believe there will be a continued focus on how to harness technology to both optimize the trader experience and automate the more routine flow to drive efficiencies on the trading desk. Data and analytics will play a critical role in achieving this.

In order to move with agility across these large datasets I can see firms looking increasingly leverage public cloud technology to be able to cheaply spin-up data research environments.  This does present its own challenges around securing the public cloud for proprietary datasets.  At J.P. Morgan firm-wide we are working with major public cloud companies to create secure environments in the cloud that meet our security standards at the same time as yielding the benefits of cloud technology.

Additionally, I can see traders playing an increasing role in providing input into the investment process, highlighting more trading opportunities and market insights to the portfolio managers.  By implementing smarter and more integrated technologies traders will be able to disseminate market insights more efficiently to interested investors that could result in investor placing an order they would otherwise not have sent.

How are new data and innovation tools enabling buy-side trading desks to boost efficiency?

Leveraging data and increased technology innovation has become essential for any buy-side desk to remain competitive.  Clients are increasingly interested in the costs of implementation of investment decisions and so having the data to evidence best execution first off is a must.  Being able to leverage this data intelligently and provide recommendations on how to trade most effectively will progressively become a feature of the buy-side desk.

In making the desk more efficient, we will also enable the frictionless launch of new products without the need to scale up the trading desk to handle increased flow.

What are the key areas of focus in equities trading technology at J.P. Morgan Asset Management, including recent accomplishments and current/future initiatives?

Our major focus has been on taking a tech start-up mentality to how we build, test and deploy our technology solutions. This mindset is reflected in the fact that we now release our software at least once per day (typically 450 per year), adding incremental benefit to the trading tools available to the traders and moving away from “big bang” releases. 

Only through our heavily automated process, executing in excess of 29,000 tests prior to every release, have we been able to ensure the quality of the software released at this rapid rate. Not only does this frequent software release rhythm reduce risk, but it has also encouraged traders to provide ideas to further innovate across the platform.

One such example of this spirit of innovation is BETSI, our Symphony Bot that integrates the Symphony messaging platform into Spectrum Trading.  Through this platform traders can communicate market and stock specific news to investors around the globe, allowing us to streamline the communications between the desk and sell-side.   Using automated chat-bots we can now simplify RFQ to the sell-side as well as identify matching IOIs from brokers all within the single UI, enhancing the user experience while minimizing risk mistakes in rekeying data from chat screens and emails.

The launch of a tool such as BETSI demonstrates the benefits of the tight knit relationship between traders and technologists. This, coupled with the support of a platform that can release multiple times per-day, can deliver new innovative solutions to the trading desk from Proof of Concept to a production operating system in a matter of weeks.

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