How did you first get involved in the ETF market?
I had spent much of my career in ETF market making, so I’ve really had a front-row seat to the industry’s evolution. When I joined MCAP back in 2022, I was coming from that background and looking at how the market had developed over time.
If you think about where ETFs are today versus when I first started over 25 years ago, the growth has been phenomenal. The product has opened access to markets and diversification in a way that simply didn’t exist before. I’ve often said, somewhat confidently, that ETFs might be the greatest financial invention of our time.
That might sound bold, but when you look at how they’ve democratised investing and allowed individuals to build diversified portfolios with ease, it’s hard to argue they haven’t fundamentally changed the landscape.
ETFs trade on equity venues, but the underlying liquidity is quite different. How has that shaped the way the market works?
That’s precisely the issue. Structurally, ETFs trade alongside equities, so they inherited a lot of equity-style trading behaviour and infrastructure.
For a long time, the industry relied heavily on equity algorithms and execution tools that were originally built to trade stocks like Apple or Microsoft. But ETFs are fundamentally different products. Their liquidity profiles are very different because they’re tied to baskets of underlying securities.
Building technology capable of pricing those baskets, understanding liquidity in the underlying assets and streaming quotes continuously creates significant complexity.
We are trying to increase available execution choices and reduce inefficiencies with QwickRoute aRFQ.
Where did RFQ come into that picture?
About 10 to 15 years ago, ETFs started to adopt request for quote (RFQ) workflows. RFQ has existed for decades in fixed income, and it turned out to be very effective for larger ETF trades. The value proposition was simple. If an institutional investor wanted to execute a large allocation, RFQ allowed them to request quotes from multiple market makers simultaneously rather than calling dealers one by one. Platforms like Bloomberg and Tradeweb helped make that process more efficient.
But at its core, RFQ was really just replacing the phone with a screen. The underlying process didn’t change dramatically.
And today it’s still widely used, which I find interesting because you have this incredibly modern financial product being traded largely through a 30-year-old fixed income protocol.
Has that model scaled with the growth of the ETF market?
Not really, and that’s part of the problem. If you look at the numbers in the US, roughly $255 billion notional in ETFs trades every day. Of that, only around $15 billion goes through RFQ workflows.
That tells you something important: the vast majority of ETF trading isn’t benefiting from that model of liquidity discovery.
The reason is that RFQ tends to be fairly manual and somewhat disconnected from the rest of the electronic trading workflow. For traders managing high order volumes, stepping outside their standard OMS or execution workflow to run an RFQ simply isn’t scalable.
So, a lot of ETF trading ends up being executed through equity algorithms instead, even though those tools weren’t really designed with ETFs in mind.
Is that the gap MCAP set out to address?
When I joined MCAP, they had been working on a way to modernise that process and integrate it into the electronic workflows.
QwickRoute grew out of that work. The idea is to take the benefits of RFQ, engaging multiple liquidity providers and improving price discovery, but embed it directly into the execution systems traders already use. Instead of being a separate, manual process, it becomes something that can be automated and integrated.
How does QwickRoute actually work?
At its core, QwickRoute is an auction-based trading network built around what we call the aRFQ execution protocol.
Rather than traders manually initiating RFQs, orders can be routed into QwickRoute directly from their execution systems. Once an order arrives, the protocol automatically engages market makers in an RFQ-style process, but in a much faster and more automated way.
Traditionally, RFQs might take minutes to complete. With QwickRoute, we’ve reduced that to roughly one or two seconds.
That speed and automation mean the process can now work not only for large institutional trades, but for a much wider range of order sizes. It essentially allows ETF orders of all sizes to interact with market maker liquidity in a way that historically was only available for very large trades.
Who has been adopting the platform so far?
We started in the US and initially focused on wealth management platforms and RIA networks. These firms typically have centralised trading desks that handle large volumes of ETF orders coming from advisors and portfolio managers.
On any given day, those desks might receive hundreds of trade requests alongside constant phone calls asking about liquidity or execution strategies.
Running manual RFQs in that environment is incredibly disruptive to workflow. What QwickRoute allows them to do is integrate that liquidity discovery directly into their order management or execution systems, making the process more scalable and consistent.
What kind of growth have you seen?
The growth has been pretty significant. Traditional RFQ workflows are limited by how many requests a desk can manage manually. With an automated process, that ceiling disappears.
In theory, the QwickRoute platform can handle thousands – even tens of thousands – of orders per day because the workflow is fully electronic.
