The TRADE 67 - Q1 2021 | Page 74

[ A L G O R I T H M I C T R A D I N G S U R V E Y ]
algos , presented in Figure 2 as a percentage of responses , differ between 2021 and 2020 . Overall , increases can be seen in seven areas of algo trading versus last year : ease-of-use , reduce market impact , lower commission rates , better prices , higher speed , customisation and pre-trade estimates . At the same time , decreases are seen in six areas : consistency of execution , trader productivity , greater anonymity , smart order routing , algo monitoring , routing logic . The emphasis seems to be on working orders at speed and with ease , and in a way that is cost effective . There is less interest on information leakage , execution consistency and trader productivity . It is clear that long-only funds of varying sizes are looking to at least two algo providers , with all AUM categories of long-only respondents reporting an average number of providers greater than two in the 2021 survey ( Figure 3 ). From a diversification and business-continuity perspective , managers are seemingly unwilling to place all of their eggs in a single basket and risk a provider outage . The smallest firms managing US $ 1 billion or less seem to be most comfortable with using approximately two providers , although the average number of providers is up in 2021 compared to 2020 for these smaller managers . Larger firms managing upward of US $ 1 billion are more likely to rely on three providers , though the average number of providers is down in 2021 compared to 2020 for the largest managers in this year ’ s survey . Going further , long-only managers with US $ 0.25 billion to US $ 0.5 billion in AUM show a year-on-year increase in the number of algo providers , rising to an average of 2.5 in 2021 which is up from 1.83 in 2020 . One explanation for this is that the unprecedented market volatility of the past 12 months compelled smaller managers with fewer resources to expand their range of partnerships . By contrast ,
Figure 2 : Reasons for using algos (% of respondents ) Feature
2021
2020
Ease of use
12.04
11.08
Consistency of execution performance
10.19
10.51
Increase trader productivity
10.32
10.45
Reduce market impact
10.45
10.29
Greater anonymity
8.96
9.93
Flexibility and sophistication of SOR
7.24
8.02
Algo monitoring capabilities
5.30
7.20
Lower commission rates
8.69
6.83
Better prices ( price improvement )
6.68
6.65
Higher speed lower latency
7.64
6.56
Customisation capabilities
6.21
5.74
Data on venue / order routing logic or analysis
3.84
5.07
Results match pre-trade estimates
2.45
1.67
larger managers in all categories above US $ 1 billion have reported declines in the average number of providers compared to 2020 . Cost pressures have accelerated the move to consolidate relationships , with managers representing over US $ 50 billion reporting using 3.89 providers ( down from 4.02 ), managers representing between US $ 10 billion and US $ 50 billion reporting using 3.47 providers ( down from 4.25 ), and managers representing between US $ 1 billion and US $ 10 billion reporting 2.94 providers ( down from 3.33 ). While having a handful of providers continue to represent an important diversification strategy for the largest long-only managers , downward pressure on research budgets across the industry have tapered enthusiasm over the past 12 months to add more and more providers . Nonetheless , despite the yearon-year direction of travel , larger managers are still associated with a higher number of providers than smaller managers . This is still down to the requirements associated with managing a larger multi-asset class portfolio . Looking beyond equity algorithms , the rise of algo use in the foreign exchange ( FX ) asset class has grown over the years for spot trading
Figure 3 : Average number of providers used by AUM ( USD billions )
2021
2020
Up to 0.25
2.13
2.14
0.25-0.5
2.50
1.83
0.5-1
2.64
2.00
1 to 10
2.94
3.33
10 to 50
3.47
4.25
More than 50
3.89
4.02
74 // TheTRADE // Spring 2021