In a nutshell…
This blog draws on insights from an ETF roundtable at the Finance Hive Equities Meeting, hosted by Tradeweb, which brought together buy-side practitioners to discuss how automation is reshaping execution workflows.
Automation in ETF trading has moved from experiment to mainstream. For many desks, the question is no longer whether to automate execution, but where automation should stop – and where human judgement should begin.
Smarter dealer selection, the use of historical performance data and more dynamic request-for-quote (RFQ) design are driving tangible efficiency gains.
The boundary between automated and manual workflows is emerging as one of the defining execution questions for 2026.
Liquidity visibility, Net Asset Value (NAV) insight, and pre-trade analytics remain major gaps across the market.
A closer look…
In discussions at a recent Finance Hive roundtable hosted by Tradeweb, members described a common trajectory: automation is now the baseline, not the aspiration. Below defined notional thresholds , one-touch execution has become the default. Trades are assessed against pre-set rules for price tolerance, dealer selection, and settlement preferences before being sent to market, with many firms now relying on these workflows for the majority of their ETF activity.
That said, the benefits of automation are not felt evenly. Smaller and less liquid ETFs can be harder to price and more sensitive to dealer behaviour, while larger trades still require human oversight to manage risk, liquidity, and market impact. As one member observed, while automation accelerates execution, it does not remove the need for judgement, particularly when dealing with unusual size or complex exposure.
Where the market is heading
Smarter execution is about data, not just speed
Tools that show historical dealer performance, hit rates, and market depth are increasingly central to better execution decisions. Traders want not only competitive quotes, but also context and insight into where a trade is likely to land and why.
Underlying liquidity visibility matters
Participants continue to emphasise the importance of looking through the ETF to its underlying basket or futures. Commodities ETFs with transparent futures markets make this easier. In other strategies, fragmented quoting and inconsistent coverage still create blind spots that complicate execution decisions.
Standardised TCA remains elusive
There is still no agreed European standard for ETF transaction cost analysis. While bid-offer metrics are widely used, many desks find them insufficient. Measures such as EBBO, if broadly adopted, could offer a more meaningful way to benchmark execution quality.
Settlement logic is a persistent friction point
Holidays, differing settlement conventions, and company-specific preferences mean that automated workflows must be flexible rather than rigid. Firms are looking for systems that can reflect their settlement logic, rather than forcing manual workarounds.
Algo trading in ETFs continues to evolve, but does not dominate
Algorithmic execution exists and is gaining traction in specific use cases, particularly where risk needs to be spread over time. However, many traders continue to question its value relative to RFQ protocols. For a wide range of ETFs, the priority remains achieving execution certainty rather than optimising for marginal price improvements.
Three themes shaping the evolution
- Dealer selection intelligence
One of the most significant areas of innovation has been smarter RFQ counterparty selection. By incorporating historical performance metrics and peer data, execution platforms can prioritise more competitive liquidity providers, leading to more consistent outcomes over time. - Data driven decision-making
Pre-trade analytics, visibility into expected liquidity, and a consolidated view of pricing versus spreads are consistently cited as priorities for traders. Platforms that can integrate these insights directly into execution workflows are likely to see accelerated adoption. - Human judgement remains central
Automation is increasingly effective at handling volume, but complexity still brings traders into the loop. Decisions around risk, fair value, and tactical timing are not yet easily automated with confidence. Across the roundtable, automation was viewed as an augmentation of human expertise rather than a replacement.
Source: Equities EU Member Meeting, London, 22 January
A clearer path forward
Progress in ETF automation is evident, but uneven. While firms agree that automated workflows deliver meaningful benefits, future gains will depend on addressing fragmentation in analytics, liquidity insight, and settlement logic. There is growing demand for end-to-end workflows that connect idea generation, execution, and post-trade analysis within a single environment.
As a platform closely involved in ETF market structure and execution workflows, Tradeweb continues to hear these themes echoed across regions and client types. One Finance Hive member summed it up neatly: “the goal is to reduce the number of screens per se, it’s to reduce the number of decisions driven by incomplete information.” This sentiment reflects a broader industry shift toward execution platforms that combine scale, data, and flexibility, supporting more informed decisions without constraining trader judgement.
