[ I N D E P T H | A R T I F I C I A L I N T E L L I G E N C E ]
The importance of data In fixed income , a growing number of machine learning techniques are required to help aggregate and make sense of the very broad and quite disparate set of data which exists in fixed income markets .
What AI enables is the ability to aggregate – in realimportant part of a trader ’ s role and AI can help assist in this process . However , liquidity is subjective and can mean different things to different people . Historically , metrics have been created that are fairly linear but inherently , liquidity tends to be feature based and dynamic in markets .
“ The latest AI model approaches are really well suited to help humans understand what liquidity conditions are and how they rapidly change , and then use that information to execute within changing markets ,” adds Bruner . “ There is this inherent nonlinear , picking up the patterns and features in large , complex multidimensional data sets , where AI can be really well suited to helping people understand liquidity .”
In fixed income , a large instrument universe with sparse
“ AI ’ s performance is not defined by the large amount of data it uses , but about learning from the representative dataset .”
MILES KUMARESAN , FOUNDER AND CHIEF EXECUTIVE OF WAVELABS
data exists where one may not see much observable liquidity on a certain ISIN . However , when you start to look at a collection of instruments , axes , real quotes or trades , AI is able to provide more observable prices .
“ With some of these machine learning or AI models , you can start to use AI to help you to impute where certain pricing or where liquidity should be , based off a broader set of data ,” notes Chris Murphy , chief executive of Ediphy .
“ The optimal right now is man and machine working together in tandem . We ' re going to see an acceleration of people deploying machine learning algorithms to assist in that process . All of these models are only as good as the data they ' re trained on . Because traditionally in fixed income , there has been a paucity of real high-quality data that you can rely on , you need to be a little bit more careful about whether the model is sitting on top of weak foundations .”
36 // TheTRADE // Q3 2023