[ A L G O R I T H M I C
T R A D I N G
S U R V E Y ]
[ A L G O R I T H M I C
JP Morgan
T R A D I N G
S U R V E Y ]
Kepler Cheuvreux
J
P Morgan recorded an almost fivefold increase
in the percentage of responses it received from
hedge fund firms in this year’s survey, with almost
two-thirds of respondents managing over $10 billion
in AuM. JP Morgan received mixed scores from hedge
fund respondents in this year’s survey, with an overall
score of 5.61, a minor decrease of 0.08 year-on-year
and just below the survey-wide average of 5.72. The
bank recorded increased year-on-year scores in five
categories in this year’s survey, although some of these
were so fractional as to be almost negligible; the most
noticeable improvements according to hedge fund
respondents were in the customisation (up 0.20) and
dark pool access (up 0.22) categories, the latter also
the highest-scoring category for JP Morgan across the
areas of performance under review (5.98). Howev-
er, there were eight categories in which JP Morgan
recorded decreased year-on-year scores, including
reducing market impact (down 0.38), execution con-
sistency (down 0.29), anonymity (down 0.38), price
improvement (down 0.23) and execution consulting
(down 0.34). For the two new categories introduced
in this year’s survey – algo monitoring capabilities
and data on venue/order routing logic or analysis –
JP Morgan received average scores of 5.63 and 5.68
respectively.
JP MORGAN RATINGS FOR ALGORITHM PERFORMANCE
K
epler Cheuvreux saw a significant increase in the
percentage of responses it received from hedge
fund firms, with the vast majority of respondents com-
ing from the small and mid-sized AuM brackets and
just 20% of respondents managing more than $10 bil-
lion in AuM. Kepler Cheuvreux will have every right
to be disappointed with its scores in this year’s survey,
particularly as it was one of the standout performers
in the 2018 edition. The broker recorded an average
score of 5.63, just below the survey average of 5.72.
There were year-on-year decreases in scores across
10 of the 15 categories reviewed, most noticeably in
the reducing market impact (down 0.70), anonymity
(down 0.32), price improvement (down 0.35), ease of
use (down 0.59), customer support (down 0.57) and
flexibility and sophistication of smart order routing
(down 0.30) categories. However, there were marginal
year-on-year improvements in the increasing trader
productivity (up 0.14), cost (up 0.10) and customisa-
tion (up 0.18) categories. Kepler Cheuvreux’s highest
score came in the customer support category (5.97),
although this only ranked sixth-highest among the 12
algo providers profiled this year.
KEPLER CHEUVREUX RATINGS FOR ALGORITHM PERFORMANCE
Increase trader
productivity Reduce market
impact Execution
consistency Cost Speed Anonymity Price
improvement Customisation Increase trader
productivity Reduce market
impact Execution
consistency Cost Speed Anonymity Price
improvement Customisation
5.94 5.47 5.49 5.54 5.57 5.70 5.31 5.57 5.83 5.58 5.86 5.71 5.61 5.76 5.31 5.75
Ease of use Customer support Execution
consulting Dark pool access Flexibiltiy and sophistication
of smart order routing Algo monitoring
capabilities Data on venue/order
routing logic or analysis Average
score Ease of use Customer support Execution
consulting Dark pool access Flexibiltiy and sophistication
of smart order routing Algo monitoring
capabilities Data on venue/order
routing logic or analysis Average
score
5.82 5.68 5.20 5.98 5.64 5.63 5.68 5.61 5.63 5.97 5.73 5.24 5.47 5.44 5.54 5.63
KEY STATS
KEY STATS
5.98 5.20 56% 5.97 5.24 40%
Highest score
(dark pool access) Lowest score
(execution consulting) Most popular non-equity asset
traded via algo by respondents:
Exchange-traded funds Highest score
(customer support) Lowest score:
(dark pool access) Most popular non-equity
asset traded via algo by
respondents: Listed derivatives
+0.22 -0.38 56% +0.18 -0.70 44%
Most improved
year-on-year score
(dark pool access) Least improved
year-on-year score
(reduce market impact/anonymity) Most used algo
performance measurement
method: Implementation
shortfall TCA Most improved
year-on-year score
(customisation) Least improved
year-on-year score:
(reduce market impact) Most used algo
performance measurement
method: VWAP TCA
92 // TheTrade // Summer 2019
Issue 60 // TheTradeNews.com // 93