The TRADE 2018 APAC Algorithmic Trading Survey

[ A PA C A L G O R I T H M I C T R A D I N G S U R V E Y ] Bank of America Merrill Lynch B category (4.82). Over half of respondents for BAML manage more than $50 billion in assets, with the remainder split evenly between the other AuM brackets. Just over three-quarters of BAML’s respondents said they are using algos to execute more than 50% of the value their flow, with just over two-thirds using algos to trade over half of their overall flow. Around half of BAML users noted their usage of the firm’s algos had increased year-on-year. ank of America Merrill Lynch (BAML) received generally favourable scores from respondents but was unable to outperform the survey average across any of the 12 categories under review. The bank’s highest ratings were awarded in the improving trader performance (5.47), ease of use (5.48) and execution consulting (5.59), while BAML underperformed against the survey average in the reducing market impact (-0.62), anonymity (-0.66) and crossing (-0.68) categories. BAML’s lowest score came in the crossing Improve trader productivity Reduce market impact Execution consistency Cost Speed Anonymity Price Customisation improvement Ease of use Crossing Execution consulting Customer support 5.47 5.20 5.29 5.27 5.34 5.18 5.17 5.48 4.82 5.59 5.43 5.27 Citi C results for Citi were largely in-line with the survey average, indicating that respondents were, for the most part, satisfied. Half of Citi’s respondents came from the largest AuM bracket (more than $50 billion), with a relatively even split among small and mid-sized firms making up the rest. Just over half of respondents indicated that they are using algos to trade more than 60% of their overall flow, while one-quarter said their algo usage has increased over the past year. iti performed well in this year’s APAC algo sur- vey and will have reasons to be pleased with the results. The firm just outperformed the survey-wide average and received high scores for its custom- er support (6.58), execution consulting (6.44) and improving trader productivity (6.30) functionalities. While there were areas where the firm underper- formed against the survey average – most notice- ably for anonymity (-0.38) and cross (-0.39) – these discrepancies were largely negligible. Several of the Improve trader productivity Reduce market impact Execution consistency Cost Speed Anonymity Price Customisation improvement Ease of use Crossing Execution consulting Customer support 6.30 5.72 5.84 5.52 5.75 5.46 5.60 5.88 5.11 6.44 6.58 94 // TheTrade // Winter 2018 5.91

The TRADE 2018 APAC Algorithmic Trading Survey | Page 6