THETRADETECH DAILY THE OFFICIAL NEWSPAPER OF TRADETECH 2024
Antish Manna :
Leveraging algo strategies to ensure the best outcomes
Head of execution analytics , multi-asset , at Man Group , Antish Manna , sits down with The TRADE to explore how to leverage algorithms to achieve the best results , touching on machine learning , broker collaboration , and ensuring minimal bias .
How has the way you determine what is an optimum algo strategy changed in recent years and what is driving this change ? I have to say that in some ways it hasn ’ t changed at all ; first and foremost , our role is to understand the objective of the investment strategy we are trading for and ensure the algo strategy we pick matches that objective . That won ’ t shift . We do , however , have to stay abreast of and adapt to developments in the marketplace , for example , the steady growth of closing auction volumes and close facilities . On the latter , we work really closely with our brokers to adapt our algo strategies to benefit from those changes , where possible through strict A / B experimentation .
At Man Group we have invested in our experimentation framework over recent years , which has improved both our ability and capacity to explore and optimise through experimentation . What has also evolved is the maturity of our execution analytics platform , which means we can more effectively monitor and analyse key execution metrics – it enables better , faster and more in-depth work . We think this leads us to faster insights and , ultimately , a stronger partnership with our portfolio managers who can also access and consume the same analytics . Given the significant market volatility over the past couple of years , we think the ability to have good and trustworthy analytics is imperative .
What metrics do you use to monitor algos and broker selection on algo wheels ? We use machine learning , and specifically reinforcement learning , to optimally route flow to broker algos within what we call panels ( what others might refer to as algo wheels ). We think there are multiple benefits to this model : it is a systematic process and devoid of human bias ; it offers a statistical framework to balance exploration and exploitation ( because panels allocation doesn ’ t get stale ); it ’ s complementary to experimentation , and finally , it offers a clear incentive for brokers to improve .
How do you normalise your data to ensure you ’ re comparing apples to apples ? The ability to fairly access execution outcome is extremely important and we spend a lot of time and effort on this . Specifically , there are a few areas where we focus : firstly , where possible we construct panels which have a similar order flow , whether in terms of order characteristics , alpha signature or both , as a way to maximise homogeneity . We also use automation and probabilistic routing to minimise biases , and transaction cost ( TC ) models that factor in the key drivers of cost . Where appropriate , we also use simulation techniques to reduce noise . Finally , a combination of statistical analysis , segment analysis and trend analysis is utilised to look at execution through different angles .
How much of your algo development and execution analytics do you outsource ? We do both proprietary algo development and execution analytics in-house and that choice has been made for a few reasons . With regard to algo development , firstly we think the information we have on our alphas and strategies gives us an edge when we ’ re planning the optimal path and approach to execution . Another key factor here is that we can control the pace and focus of development , and finally , being actively involved in the process and deep into the details has improved our team ’ s DNA and understanding of markets . The same applies for execution analytics – we ’ re aiming for a best-in-class platform , so every component needs to shine . What we ’ ve built is best placed to service the diversified business of Man Group .
TheTradeNews . com 25