[ 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 )
ALGO 2020 ALGO 2021
5 + 32.54
41.13
4
9.22 10.75 provider count
3
14.89 15.52
2 12.54
14.89
1 19.86
28.66 0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00 45.00
and , recently , has begun to extend to FX derivatives such as non-deliverable forwards . New regulations , such as the uncleared margin rules , are driving FX derivatives into the 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 . Analysing the number of providers chosen by long-only managers without segmenting results into AUM categories reveals some curious findings ( Figure 4 ). Like last year , 2021 ’ s survey suggests that long-only managers either go hard or go home when it comes to committing resources to providers . The proportion of participants indicating that one provider is sufficient has grown from around 19.86 % in 2020 to just shy of 28.66 % in 2021 . This is in part driven by the growing familiarity and relationships between long-only managers and their providers . The proportion of firms relying on five or more algo providers has fallen from 41.13 % in 2020 to 32.54 % in this year ’ s survey . The reason for this phenomenon is that cost pressures have pushed managers to consolidate and streamline their relationships , even though clearly a significant number of providers still see the diversification benefits of leveraging a handful of different algo providers . The distribution of algo usage by value traded has changed considerably over the past year ( Figure 5 ). The proportion of participants trading 80 % or more of their portfolio via algo trading almost doubled from 10.98 % in 2020 to 20.75 % in 2021 . At over a fifth of all long-only respondents to this year ’ s survey , this group of managers trading 80 % + of their portfolio algorithmically now represents the largest proportion of survey participants . Additionally , the year-on-year increase for this group is the largest of any bracket . Long-only funds allocating 20 % to 30 % of their portfolio value into algos grew to 12.19 %, up from 7.65 % in 2020 in the second largest increase of any bracket . At the lower end of the spectrum , 6.82 % of participants trade between
5 % and 10 % of their portfolio ’ s value using an algorithm ( versus 8.43 % a year ago ). The most significant yearon-year decrease was seen in the 50 % to 60 % segment , which declined from 22.16 % of long-only funds trading via algos last year to 9.65 % in this year ’ s survey . At first glance it seems that more firms are pushing a larger proportion of their book into algorithms and this is partly a consequence of the developments in technology and software that has enabled algo trading in equities as well as other asset classes . The percentages of funds trading via algos have risen since last year in the three largest categories : 60 % to 70 %, 70 % to 80 % and above 80 %. All the same , the fact remains that the percentage of respondents trading 50 % or more of their portfolio algorithmically has remained essentially the same : 49.41 % versus 49.22 % last year . This is a reminder that for all the benefits of algorithmic trading , the industry still values the role of human discretion and it remains the case that many instruments and asset classes do not lend themselves easily to algo trading . Long-only managers were asked
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