[ 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 ]
“ Machines are faster in digesting data and turning it into actionable information .”
ERIC BOESS , GLOBAL HEAD OF TRADING ,
ALLIANZ GLOBAL INVESTORS
grid based and structured autoexecution rules . Instead allowing them to become more agile and data dependent when it comes to execution strategies for specific orders .
While AI is currently being used for the automated routing of simpler trades and smaller orders , this can be taken further still . For example , to determine which broker should be used according to an order ’ s level of difficulty using real-time data including axes , trades , wire time behaviour and related markets .
“ The next step would be broker selection : If we balance information leakage against price discovery and only ask a limited set of counterparts , the key question becomes who to ask ,” says Eric Boess , global head of trading at Allianz Global Investors . “ Experienced traders do all this naturally , but machines are faster in digesting data and turning it into actionable information .”
Real-time analysis in the fastpaced world of trading becomes vital . As new market data sets continue to emerge , AI is able to analyse that data , ensuring that traders are ahead of the curve and able to adjust their strategies alongside everchanging market dynamics . The use of AI allows trades to be executed autonomously while also adapting to market conditions and developing from past trading scenarios .
“ This not only streamlines the trading process but also minimises human errors , leading to more consistent and profitable outcomes ,” adds Heleine . “ AI ' s ability to analyse past trading patterns and forecast future liquidity conditions is invaluable , especially in a market known for its occasional illiquidity . Such predictive insights ensure traders can time their trades optimally , mitigating risks and maximising returns .”
Execution The role AI plays in fixed income is proving to be
34 // TheTRADE // Q3 2023