Man vs machine – the Schroders story
By Jacqueline Loh, Head of Asia Trading, Schroders.
Schroders Asia first started using direct market access tools and algorithms for trade execution in 2006. Since then, the proportion of trades carried out via electronic execution has grown significantly in terms of volume of traded turnover. This would not have been possible without the increased sophistication of algos and refinement of TCA (transactions costs analysis) analytic tools to measure trading performance. In line with Schroders’ best execution policy of implementing trades with minimal total impact costs to clients, electronic trading was initially introduced to help traders minimise impact costs by gaining better overall control of their trades. It was not a conscious effort to pay less commission, although that later turned out to be one of the indirect results.
The journey over the past few years has been a very profitable and enlightening one. We made new discoveries every day, such as which broker provides the most hardy algos, which algos work best in which Asian markets, which ones were particularly suited for volatile markets. We continuously monitor the quality of our low touch and high touch execution, and the relative proportions of these to ensure that we are making optimal use of all the execution venues available to us.
The past few years have spawned a myriad of DMA and algo providers for Asia electronic trading, accompanied by a vast array of algorithms. It therefore made sense to try to differentiate between the algos as well as determine whether we were utilising algos in ways that added value.
Objective of the study: To determine if there are any significant differences in trading performance, measured against two benchmarks (arrival price and VWAP), between results achieved using fully automated algos and semi-automated algorithms.
Using data for all of 2014, we classified all the trading strategies used by the Asia trading desk into the following two categories:
– Semi-automated algos
Definition of automated algos: All auto schedule, auto participant type algos.
Definition of semi-automated algos: Algos with a high degree of trader input such as picking price levels and market timing.
The performance of all these algos were compared against two benchmarks – arrival price and VWAP.
These are the results obtained from our two algo providers.
From the above graphs, it is clear that semi-automated algos outperform automated ones against both benchmarks – arrival price and VWAP. Divergence in performance is increasing with difficulty of trades, as represented by high ADV trades.