[ S U R V E Y | A L G O R I T H M I C T R A D I N G ]
marking the largest year-onyear increase over the past five years. The most impactful algorithm features identified in this year’ s survey remained fairly consistent from 2024: Ease of use, customer support, increased trader productivity, and breadth of dark pools( Figure 1). While breadth of dark pools did overtake anonymity as the fourth most important category when compared to 2024( but only by 0.01), both factors validate the importance of minimising market impact for buy-side traders.
Another significant note was the fact that all aspects of service experienced a yearover-year increase, with the two largest increases recorded in the categories of routing logic analysis( 0.30) and algo monitoring( 0.26), indicating the growing expectations on the part of the buy-side to measure and understand the overall effectiveness of deployed strategies.
Factors for algorithmic usage Respondents’ reasons for using algorithms are presented in Figure 2 as a percentage of responses from 2023 to 2025. Over the last few years, we have seen very little change in the top reasons long-only respondents claim to use algorithms with around 43 % of traders indicating their top four reasons for using algos as ease of use, consistency of execution performance, reduce market impact and increase trader productivity.
Perhaps not surprisingly, given the heightened pressure on buyside traders to focus on lowering both explicit and implicit trading costs to further improve their overall trading performance, two of the largest increases in
Figure 2. Reasons for using algorithms(% of responses) Feature |
2025 |
2024 |
2023 |
Results match pretrade estimates |
3.00 |
2.64 |
1.84 |
Data on venue / order routing logic or analysis |
3.77 |
3.96 |
4.86 |
Customisation capabilities |
6.57 |
6.10 |
6.45 |
Lower commission rates |
6.71 |
5.77 |
6.95 |
Higher speed lower latency |
6.85 |
7.48 |
6.58 |
Algo monitoring capabilities |
6.91 |
6.58 |
6.29 |
Flexibility and sophistication of smart order routing |
7.21 |
7.19 |
8.14 |
Better prices( price improvement) |
7.64 |
7.07 |
6.94 |
Greater anonymity |
8.26 |
7.99 |
7.67 |
Increase trader productivity |
10.20 |
10.60 |
10.64 |
Reduce market impact |
10.48 |
11.41 |
11.43 |
Consistency of execution performance |
10.74 |
10.71 |
10.02 |
Ease of use |
11.66 |
12.51 |
12.18 |
responses were lower commission rates and price improvement.
Somewhat paradoxically, at least on the surface, the areas that saw the largest year-overyear decreases have historically been the ' the bread and butter ' reasons for using algorithms, including ease of use, reduction in market impact, low latency trading and increasing trader productivity. Based on discussions with the buy-side community, the reality is that these categories have become key for adoption of algorithms over the last decade and are considered as a minimum requirement for all algorithmic
Figure 3: Average number of providers used by AUM( USD billions)
trading services. As a result, the overall decline of their importance as differentiating factors when using algorithms appears to be a natural by-product of the buy-side community’ s continued high-levels of adoption.
Number of providers used declines Very much in line with past surveys, we continue to see a positive correlation between a firm’ s AUM and the number of algo providers they use( Figure 3). One interesting note is that for the first time since 2021, we actually saw a decline in average numbers across the majority
AUM( billions USD) 2025 2024 2023 Up to 0.25 2.88 2.82 2.55 0.25-0.5 2.23 2.50 2.43 0.5 to 1 3.06 2.91 2.90 1 to 10 3.03 3.04 3.88 10 to 50 4.16 5.14 4.19 More than 50 4.70 4.77 4.99 Not Answered 3.20 3.90 3.28
60 // TheTRADE // Q1 2025