THETRADETECH DAILY THE OFFICIAL NEWSPAPER OF TRADETECH 2021
Traders turn to tried and tested algo strategies in market volatility
As the percentage of funds trading via algos continued to rise , the long-only results of The TRADE ’ s Algorithmic Trading Survey 2021 reveal that traders relied on tried and tested VWAP and TWAP strategies during the market uncertainty .
2020 was a wild year for global equity markets and that is putting it mildly . After investors watched on in horror last March as the dramatic sell-off in markets seemed to spell financial Armageddon , it did not take too long for central banks and governments to realise the seriousness of the situation . An enormous program of bondbuying and rate cuts set the stage for a series of record-breaking rallies and heightened equity market activity as companies looked for financing and restructuring solutions .
Despite an unprecedented year-long restriction in economic activity , markets are now poised for a global recovery with investors bullish on the prospect of strong growth in business confidence and corporate earnings globally . The investments in technology and software that the financial services sector has made largely paid off through the relative seamlessness with which the industry has handled the turmoil of the past year . Just as the pandemic has underscored the centrality of large technology companies in the modern economy , it has been a reminder of the importance of sophisticated digital solutions for successful investment management strategies . In particular , the volatility , best execution requirements and the working from home environment of the past 12 months has created a fertile environment for algorithmic trading .
In this year ’ s survey of long-only funds the average score of respondents is 5.81 – an increase from both the 2020 score ( 5.71 ) and the 2019 score ( 5.74 ). In 2021 , the most impactful features of algorithms are ease of use , customer support and services , dark pool access , execution consistency and increased trader productivity ( Figure 1 ). Following from high scores of 5.96 and 5.92 respectively in the 2020 survey , support services and ease of use both scored 6.01 in this year ’ s survey . It is interesting to see ease of use increase its score year-on-year over the past four years , underlining the importance of usable and streamlined technology in the modern trading environment .
Two categories in this year ’ s survey recorded the joint highest year-on-year increase in their score , anonymity and algo monitoring . Both categories received an increase of 0.17 , putting anonymity at 5.89 and algo monitoring at 5.72 . Increase in trader productivity marks the second highest jump in score , having increased by 0.17 from 5.80 to 5.97 . This jump shows the growing role that algos play in boosting the performance of traders . While all scores in 2021 were up from 2020 , dark pool access recorded the smallest increase at only 0.02 . While dark pool access remains a highly rated feature of algos , the push from European regulators to shift trading onto lit venues means that long-only firms are increasingly looking for other features in addition to dark pool access .
Respondents ’ reasons for using 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 , 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
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