[ A L G O R I T H M I C
T R A D I N G
S U R V E Y ]
Figure 4: Number of providers used (% of responses)
14.36
14.89
14.89
41.13
2019
9.22
19.86
Provider count
1
2
3
4
28.20
17.95
2020
12.68
15.67
39.55
2018
10.26
13.43
29.23
18.66
5+
clearinghouse and fostering more
electronic trading. The development
of new algos is a natural extension
of this phenomenon. Thus, it may be
that these managers are holding the
number of algo providers somewhat
consistent while diversifying the
types of algos used by asset class and
strategy.
Stripping away the AUM filter on
the number of providers selected
by long-only managers yields some
interesting results (Figure 4). This
year's survey suggests long-only man-
agers are either all in when it comes
to committing resources to algos or
sticking with two or so providers. The
population of participants indicating
they are “one and done” has shrunk
year-over-year and is now only 19.86%
of managers versus 28.2% in 2019.
This trend is likely driven by managers
looking to mitigate counterparty risk.
Deutsche Bank’s July 2019 announce-
ment that it would exit global equities
trading, cutting 18,000 jobs and trans-
ferring 75 billion euros in risk-weight-
ed assets as part of a major overhaul,
drives this point.
The group of firms relying on five
or more algo providers has grown
substantially in the past 12 months.
In 2019, 29.23% of participants fell
into this group. This year, a whopping
41.13% of surveyed firms have a large
group of providers they work with.
The reason for this is two-fold. On one
hand, a combination of business rela-
tionships and specialised tech (offering
better features and functionality that
foster ease of use, consistent execution,
and enhanced trader productivity—all
buttressed by better customer support)
may be the likely driver. Alterna-
tively, fund managers may need to
pay a wider number of providers for
research and other broker-provided
services, which pushes them to take on
additional algo providers.
Just because you can do it
doesn't mean you should
The distribution of algo usage by
value traded has changed since 2019
(Figure 5). For example, the group
of managers trading roughly 50% to
60% of their portfolio using algos has
increased to 22.16% of participants
from 9.85% 12 months ago. This group
represents the largest percentage of
survey participants, edging close to
one-quarter of managers. Addition-
ally, the year-over-year increase is
the largest of any bracket. Similarly,
long-only funds allocating 40% to 50%
of their portfolio value into algos grew
to 12.75% from 7.06% a year ago—the
second-largest increase of any bracket.
At the lower end of the spectrum,
8.43% of participants trade 5% to
10% of their portfolio’s value using an
algorithm (versus 4.76% 12 months
ago). Increases are also apparent in the
20% to 30% bracket, where 7.65% of
long-only funds increased the value of
their portfolios traded by algos from
5.25% over the same period.
There is a perception that more firms
are pushing a larger percentage of their
book into algorithms, and this will
likely continue, even beyond equities.
However, firms prefer to balance the
amount of trading that is algorith-
mically dealt against other means of
transacting. The percentages of funds
have fallen in all of the three largest
categories: 60% to 70%, 70% to 80%,
and over 80%. In some cases, manag-
ers may have discovered through trial
and error that algos are not right for
every instrument that can be algorith-
mically traded. In these instances, cost
factors such as execution consistency
and market impact may have fallen
short of expectations.
Long-only managers were asked to
select the types of algorithms they used
from providers (Figure 6). In 2020,
the highest concentration of surveyed
Issue 63 // thetradenews.com // 79