From voice to code: How FX liquidity became parametrised

First time I made a decision to go into e-trading was after I was working at Lehman Brothers on the e-procurement aspect. You possibly can see the ecommerce groups beginning to develop and the sentiments on the buying and selling desks began to vary in how liquidity was managed. My decisions within the e-trading area the place at all times constructed on expertise despite the fact that the mechanics of the trades between buyside and sellside the place relationship based mostly. Some within the e-trading area nonetheless argue relationships are key to liquidity…however are they?

Within the noughties a supplier knew which company treasurer would commerce on the London repair, which macro fund would present measurement into New York, and which hedge fund would pull liquidity the second volatility picked up. Costs have been fashioned as a lot by relationships and judgement as by provide and demand. Away from the buying and selling aspect the precise equipment of which buying and selling expertise was chosen from an array of distributors was additionally typically dictated by relationships between consumer and vendor.

As we enter 2026 I believe you’ll be able to argue that world has largely disappeared or is within the technique of disappearing. FX liquidity is now not negotiated; it’s parametrised. It arrives as streams, curves, confidence scores and reject chances. What used to stay in a supplier’s head now lives in configuration information and datasets.

This shift from voice to code is not only a narrative about automation. It’s a story about how FX liquidity itself was redefined. From human discretion to machine-readable parameters and the way that change reshaped buying and selling behaviour, market construction, information economics and the regulatory surroundings.

The voice market: liquidity as judgement

Within the voice-driven FX market, liquidity was inherently contextual.

A quoted value trusted:

Who was asking

How a lot they needed to commerce

Why they have been buying and selling

Once they have been more likely to come again

A supplier might widen a value not as a result of volatility had elevated, however as a result of they suspected the consumer had info. They might present measurement selectively, lean on inside flows, or warehouse danger based mostly on expertise somewhat than fashions.

Importantly, liquidity was elastic. It might be negotiated, delayed, reshaped, or withheld completely. The idea of a “agency value” was versatile, and execution high quality was inseparable from relationships. Knowledge existed — however it was secondary. The first sign was dialog both on the cellphone or on the Bloomberg/Reuters chat.

Digital buying and selling didn’t take away discretion — it encoded it

The primary wave of digital FX buying and selling didn’t remove supplier judgement. It translated it. Single-dealer platforms (SDPs) allowed banks to stream costs to purchasers, however these costs have been nonetheless formed by:

Shopper tiering

Historic behaviour

Inside danger limits

Supplier instinct

What modified was the interface, not the decision-making. Liquidity turned steady somewhat than episodic, however it was nonetheless deeply relationship pushed. The essential shift got here later, when multi-dealer platforms (MDPs) and algorithmic execution compelled liquidity to develop into comparable. In 2000 FXConnect, FXAll, Currenex and 360T launched and extra MDPs adopted. As soon as costs from a number of banks appeared aspect by aspect, discretion needed to be expressed in a manner machines might course of. That required parameters.

Parametrisation: the second liquidity turned machine-readable

In FX, this occurred steadily however decisively. Sellers started to specific liquidity by means of:

Unfold widths

Skew changes

Dimension tiers

Timeouts

Reject logic

Final look thresholds

Shopper tiering ranges (Gold, Silver, Bronze, and many others)

Every parameter encoded a bit of human decision-making:

How a lot danger am I keen to take?

How assured am I on this value?

How poisonous do I believe this circulate is?

How briskly do I wish to reply?

Liquidity stopped being a dialog and have become a perform.

From the buy-side perspective, this was transformative. As a substitute of negotiating, merchants might probe. They might ship RFQs, stream requests, and little one orders to deduce liquidity situations statistically somewhat than socially.

Execution algos then formalised the brand new language of liquidity

The rise of FX execution algorithms accomplished the transition.

Execution algos required liquidity to be:

Observable

Predictable

Quantifiable

An algo can not “sense the market” the best way a human dealer as soon as did. It wants inputs. Because of this, liquidity needed to be damaged down into measurable elements:

Fill likelihood

Market influence

Slippage distribution

Latency sensitivity

This compelled either side of the market right into a suggestions loop. Banks tuned their parameters to guard in opposition to antagonistic choice. Purchase-side companies measured these parameters implicitly by analysing outcomes. Over time, liquidity turned one thing inferred from information outputs somewhat than proven explicitly by means of relationships. On this sense, execution algos didn’t simply eat liquidity they contributed to reshaping it.

Why “liquidity” in FX now not means what it used to

In a parametrised market, liquidity is just not depth on the high of guide. It’s a conditional likelihood.

A decent value is barely significant if:

It’s agency

It survives latency

It fills on the anticipated measurement and value

It doesn’t disappear on an execution try

For this reason FX liquidity typically seems to be plentiful till it isn’t. Throughout regular situations, parameterised liquidity performs properly. Fashions are calibrated on steady regimes, reject charges are low, and spreads behave predictably.

Underneath stress, parameters flip:

Dimension thresholds drop

Final look home windows tighten

Skews widen asymmetrically

Streams pause completely

What disappears is just not liquidity itself, however the assumptions embedded within the parameters. Is that this when relationships matter or when the info aligns?

The buy-side response: measuring what can’t be seen

As liquidity turned parametrised, buy-side companies tailored by changing into information companies. The final 10 years have seen this improve quickly throughout the buyside, though maybe much less so with company treasurers.

Buyside Execution desks started to seize and analyse:

Quote-to-trade ratios

Reject causes

Time-to-fill distributions

Venue-specific efficiency

LP behaviour by pair, measurement, and time of day

This information turned was key to a change in mindset on the buyside. Over time, subtle buy-side companies stopped asking “the place is one of the best value?” and began asking:

The place is probably the most dependable liquidity?

Which LPs behave persistently in stress?

How does liquidity decay as measurement will increase?

These questions can solely be answered statistically — one other signal that liquidity had develop into abstracted from human interplay.

Venue evolution: from execution to information infrastructure

The parametrisation of liquidity may be put ahead as one other strategic cause exchanges acquired FX platforms. I’ve written on this in earlier articles however offers equivalent to CME and EBS, LSEG and Refinitiv, Deutsche Börse and 360T and BidFX and SGX. They weren’t merely about quantity. They have been about proudly owning the rails on which parameterised liquidity flows.

Venues more and more act as:

Normalisers of heterogeneous liquidity

Distributors of analytics

Repositories of historic behaviour

In a world the place liquidity is outlined by parameters, the flexibility to standardise, measure, and replay these parameters turns into strategically crucial. Execution is ephemeral. Knowledge persists.

What was misplaced — and what was gained

The parametrisation of FX liquidity introduced simple advantages:

Decrease transaction prices

Higher transparency

Scalability throughout areas and time zones

Decreased reliance on particular person sellers

However one thing was misplaced as properly.

Human discretion as soon as absorbed ambiguity. A supplier might select to indicate liquidity regardless of uncertainty, based mostly on judgement. Parameterised methods are much less forgiving. When uncertainty rises, the default response is usually to withdraw. For this reason FX liquidity can really feel binary for some purchasers: plentiful till instantly absent.

The subsequent part: adaptive parametrisation

The way forward for FX liquidity is rarely going to be a return to voice, nor a easy extension of present algos. It’s adaptive parametrisation.

This contains:

Dynamic skewing based mostly on real-time circulate toxicity

Machine studying fashions for reject likelihood

Venue choice that adapts intra-order

Suggestions loops that replace parameters constantly

However even right here, the core fact stays, that liquidity continues to be being expressed by means of parameters. The distinction is that these parameters are actually adjusted sooner and with extra information. The market has not develop into much less human — it has develop into human judgement at scale, encoded in methods. Among the eFX platforms have seen this and anybody dialled into trying behind the press releases can see that strategically some platforms are properly upfront of others by way of future proofing.

We haven’t even approached how AI will have an effect on these MDPs and the buying and selling/liquidity on them. It’s a topic for a bigger piece however take a look at what a number of the sharpest minds within the biz say about AI and its influence on buying and selling companies operationally. See the remarks not too long ago within the press from Citadel CTO Umesh Subramanian and Schonfelds Ryan Tolkin.

Conclusion: liquidity as a design selection

FX liquidity didn’t disappear. It was redesigned. What was as soon as negotiated turned calculated. What was as soon as implicit turned specific. What was as soon as private turned statistical. Understanding trendy FX markets requires understanding this transformation. Not simply how algos work, however how liquidity itself was became code and what which means when the assumptions behind that code are examined.

Readers can see extra of John McGrath’s articles on his Substack web page: johnjmcgrath.substack.com