You don’t need to be Einstein to work out that three-dimensional data unlocks bond liquidity
Fact – Mifid II has not solved the European corporate bond market liquidity challenge. The problem is that in order to overcome this long-standing issue, the market cannot “keep doing the same thing over and over again and expect different results.” Einstein’s daily walks often sparked his most creative and effective ideas. To harbour any hopes of creating a more liquid place to trade, market participants need to release themselves from the shackles of past perceptions and start thinking freely and imaginatively.
Thankfully progress is being made. Over the past eighteen months or so, numerous dealers and asset managers have been locked in talks about how to consume and better understand Fixed Income (FI) data in order to drive improvements in execution activity.
Following these discussions, which are still ongoing, it has quickly become clear how polarised the market is around evaluated prices, and how other very useful data is completely ignored. With this in mind, there is a need to expand data ranges beyond dealer prices, axes, IOIs and reported trades, to a more pre-trade focus of watch lists, actual live orders and the extraordinarily huge number of failed to trade RFQs.
Once the breadth of data increases, both dealer and asset management trading data needs to be collected and combined with in-depth analysis. These three dimensions would need to be broader in scope, much higher integrity and most importantly, directly serve the different objectives of dealers and buy-sides.
However, the core issue that needs to be solved is how to aggregate all the data generated by the individual asset manager with the specific dealer data they wanted to see. Key to this is creating a value proposition for both by combining all their inputs into a system that is highly targeted, insulated from leakage and aggregated to create exceptional market insight.
It also requires a commercial model that does not prejudice data provider and consumer. In this case though, asset managers and dealers are both data provider and consumer. Asset managers own watch lists, live orders, failed to trade and successful RFQs and dealers’ own prices, axes and IOIs. Both own traded volumes. Our task was to provide the third dimension of connectivity, aggregation and analysis.
Eighteen months on, and we current find ourselves at the epicentre of connecting the top five dealers to a growing list of asset management clients. The interesting thing is how varied these clients are. The systematic credit investors are intense users of matchable data to generate reactive prices. Some of the insurance/pension clients want to consume vast quantities of dealer data and run their own quantative analysis. The private wealth managers need historic data to auto-route and execute huge numbers of low-touch orders.
It is normally quite difficult to be aware of reaching a tipping point until some time afterwards when there is enough evidence to support the claim. But the momentum is building between asset managers and dealers to consume each other’s data in a highly symbiotic manner that will contribute significantly to a more efficient market structure. The great man once said “imagination is the highest form of research”. While there is still a way to go, it appears that bond market participants may finally be starting to use their imagination to think differently about the use of data to boost liquidity.
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