The TRADE 2018 APAC Algorithmic Trading Survey | Page 9

[ 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 ]
Societe Generale
S
ociete Generale was another firm to record a num-
ber of high scores from respondents in this year’s
survey, with an overall average score well above that of
the survey-wide average. The firm outperformed the
survey average in all of the 12 categories under review,
as well as scoring above 6.00 for all algo functional-
ities assessed. Its highest scores came in the customer
support (6.47), improving trader productivity (6.43)
and execution consistency (6.39), while it was also one
of only three firms in the survey to score above 6.00 in
the crossing category (6.05). Societe Generale notice-
ably outperformed the survey average for cost (0.68),
customer support (0.67) and execution consulting
(0.5).
Respondents for Societe Generale were evenly split
across AuM brackets, with just over one-quarter com-
ing from the highest end of the scale (more than $50
billion). Just under two-thirds of respondents for the
firm indicated increased use of algos year-on-year.
Improve
trader
productivity Reduce
market
impact Execution
consistency Cost Speed Anonymity Price
Customisation
improvement Ease of use Crossing Execution
consulting Customer
support
6.43 6.26 6.39 6.37 6.29 6.32 6.15 6.31 6.05 6.38 6.47
6.15
UBS
U
BS received largely favourable scores from respon-
dents in this year’s APAC algo survey, although
there are areas for improvement for the firm to concen-
trate on. UBS only just outperformed the overall survey
average score, while scoring above 6.00 in four of the 12
categories reviewed by respondents – speed (6.17), an-
onymity (6.15), ease of use (6.14) and improving trader
productivity (6.05). The firm outperformed the survey
average in nine of the 12 functional categories, only just
failing to do so for cost (-0.29), customer support (-0.20)
and execution consistency (-0.15).
The majority of respondents for UBS were in the
lower end of the AuM brackets, with around half of
firms managing below $10 billion, while around one-
third were from the highest bracket with more than
$50 billion in AuM. Just over 20% of respondents for
UBS indicated that they are recorded increased usage
of algos over the past year.
Improve
trader
productivity Reduce
market
impact Execution
consistency Cost Speed Anonymity Price
Customisation
improvement Ease of use Crossing Execution
consulting Customer
support
6.05 5.89 5.72 5.40 6.17 6.15 6.00 6.14 5.50 5.96 5.60
5.94
Issue 58 // TheTradeNews.com // 97