These results show the same trend – performance of semi-automated algos is superior with outperformance particularly marked in higher MDV type orders.
Where do we go from here
One reason for looking into this was to explore further scalability of our business i.e. if there is any deterioration in trading performance with maximum usage of algos. One Head of Execution Services had mentioned that our desk is the most scalable one he knows as we have been able to cope with large fluctuations in turnover without any change to headcount. This study shows that although efficiency can be enhanced by use of DMA tools and algorithms, the best results to the clients are achieved by a combination of trader judgement (e.g. by picking stock levels, market timing) and algorithms rather than use of fully automated algos. Differences in results are particularly marked in higher MDV orders. This has several implications for buy side trading desks. The average desk MDV (median daily volume) is a good indication of optimal algorithm usage for the desk. While desks with low average daily volume ( 20% or less as suggested by these results) may benefit from lower automation, higher average MDV desks do better with constructive trader input.
Amongst our automated algo suite, the algos we use most are the ones which enable us to accumulate or sell stock at certain levels while causing minimal market impact. Conversations with our brokers are therefore centred around refinement of their algos in such a way that allows us to trade size and yet not reveal our intent.
Automated algos too will continue to evolve to become less commoditised and more customised. We do have conversations with brokers around development of specialised, customised algos for us; however, we seem to perform better with those algos that require more manual intervention. Every desk will be different in this respect; that’s not surprising as there isn’t just one way to achieved desired outcomes.
Man vs machine – the Schroders story
