The Fixed Income Leaders’ Summit US kicked off on Monday 9 June in Washington DC, with the buy-side traders’ day. While no reporting is allowed on the panels, five ideas were clearly voiced by a range of panellists, which are worth considering as ways to drive innovation on the trading desk.
Engage in pilot programmes
A great way for asset managers to drive innovation is to engage with pilot programmes being run by service and technology providers. These pilots allow the asset manager to keep up with the latest ideas, to engage with and shape them, and potentially to onboard technologies early in order to lead the field, even where internal investment can be challenging to develop.
Centralise data
Having a single picture of the market hinges on a centralised view of data, whether that be via a single data warehouse or another model. Applying AI tools to a function requires a single pool of data in order to train its model. Pulling data together is not easy, but it is the starting point for investment research, trading decisions and ultimately automation of process form front to back office.
Innovation needs a culture in which to thrive
Having a highly innovative team can build a concept into a model, but using ‘bubble gum and band aids’ as one participant put it, only gets you so far. Taking a good idea and putting it into practice requires a fertile bed or it to grow, and company culture was repeatedly cited as the most necessary precursor for that. Buy-side traders need to foster that culture on desks, in the front office, and to push for that more widely so that they can make their vision for trading a reality.
AI helps organise and prioritise
The one thing everyone wants on their desk next year is AI – but with a purpose. One wealth manager noted that it had reduced 40 trading seats to 30 over the past three years, while tripling its trade count, thanks to automation of trading using AI-based services to increase systematic efficiency. Major asset managers are developing AI programmes to optimise data parsing and reduce time in decision making. While not all AI models are useful for all cases, for example, deep learning models are considered to have too high a latency to support high-frequency trading, if team members are well versed in AI model types and the prompts to use for a model, they can yield very positive outcomes.
Reimagine how you work, to fit where you want to be
A square innovation will not fit in a round trading desk, so teams – from IT to operations to trading – to need to be reimagined in order to function as needed. The bond markets are changing dramatically and firms that do not adapt to function in these markets more effectively will be hit the AOL model barrier – selling out of services to an increasingly dwindling set of out of date users.
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