By James Goater, Co-Founder and CEO, InTick
Over the fifteen years I have spent in listed derivatives, I have watched the execution market move relentlessly towards systematic, electronic trading built on bank and non-bank algorithms.
That shift has been anchored by two things: benchmarking slippage to the ‘arrival’ price, and the creation of autonomous algorithms specifically designed to work with little or no client input, in all market conditions and regardless of order size. This standardisation across markets and providers has resulted in previously fragmented data becoming unified, driving increasingly accurate pre- and post-trade analytics free from relationship bias. Once performance can be predicted ahead of execution, the final step is for traders to build this into an order distribution model, pushing additional flow to the statistically best performers in a fully systematic way, commonly known as an ‘Algo Wheel’.
This automation has allowed sophisticated trading desks to reduce or eliminate the time taken to make execution decisions, and instead focus on driving Best Execution (BestEx) via the selection and development of algorithms in partnership with providers.
For the vast majority of orders, those algorithms add enormous value, and the scale of adoption speaks for itself: in 2025, 85% of total volume across the largest global exchanges was executed on the Central Limit Order Book (CLOB).
What about the remaining 15%? And what is the correct balance?
The orders algorithms were never designed for
The remaining volume is transacted off-book, with the vast majority as privately negotiated block trades. For these blocks an order must meet a minimum block size and be executed under each exchange's strict rulebook. Typically, an exchange member negotiates a block transaction bilaterally on behalf of its buy-side client, either crossing two of its own clients inside the order book’s bid/ask spread, usually at the mid price, or sourcing a risk price from liquidity providers on the client's behalf. Many buy-side firms today hold direct relationships with liquidity providers and bypass intermediaries altogether.
A blocking minimum size represents a number of lots which the exchange considers to be a large order in that specific product; large enough that working it through the CLOB over any reasonable horizon to minimise price volatility would be likely to have a notable market impact. That impact arises either because there is not enough resting liquidity up and down the order book to absorb it, or because that order, even sliced, would represent such a high percentage of volume that the information leakage would reveal it no matter how sophisticated the algorithm hiding it. That logic holds right across the curve, from the most liquid benchmark contracts to newly listed ones and tailored products such as options.
An exception to the rule
The main exception is the monthly and quarterly rolls, principally in fixed income and equity index futures. Here the conditions are unique with ultra-low volatility and potentially hundreds of thousands of lots on the bid/ask spread, and trading activity focused on only a few days each roll period.
A large share of that depth, however, is posted by firms with no interest in the underlying contract at all. Their business is working large orders passively to fill the first-in, first-out (FIFO) order book queue with depth, making it exceptionally hard for natural buy-side liquidity to get to the front of the queue. The expectation is that this buy-side participant is forced to pay the spread rather than waiting for the market to move. The incentive for algorithms plays into the hands of the firms on both sides of the roll, with algorithmic logic tending to be conservative deciding to cross the spread early rather than risk having to explain to a client why it ultimately chose to wait and chase the market.
It is why most exchanges permit rolls to be blocked at sizes that are a small fraction of the CLOB bid/ask, allowing a cost-effective alternative, so that the buy-side is not forced into this game. The question is how much of the market takes advantage of this method of trading.
What we see in practice
If we take a recent Eurex Bund roll, we see that just 24% of total volume was blocked. Of the remaining transaction volume that traded across the CLOB, 55% traded in clip sizes of 4,000 lots or more and every one of them eligible to be blocked within the bid/ask spread.
The sums are not trivial. For a roll spread of one tick (0.01, or €10 per lot), blocking at the mid level rather than paying the spread is worth half a tick: €5 per lot. On a single 4,000-lot clip, required to achieve the mid price, that is €20,000. Aggregated across the entire blockable volume that traded through the CLOB instead and could conceivably have been blocked at the mid, it totals €9m, just for the Bund spread and that one week-long quarterly roll. It is something we consistently across exchanges and asset classes.
If block trading were going to win the majority of volumes anywhere, it would be here. It managed 24%. Even where the spread capture is visible, sizeable and permitted, the market consistently prioritises the certainty and measurability of electronic, algorithmic execution.
So why would entirely rational traders forgo the performance benefits of blocking? The answer lies in the constraints of the existing blocking infrastructure.
Three reasons blocking doesn’t rise to the challenge
Low electronification of solutions.
Listed derivatives have seen virtually no progression towards electronic blocking. What exists is either traditional risk-based Request-for-Quote (RFQ) models, which are limited to a buy-side client's existing relationships, or solutions built in isolation for each risk provider, which require manual comparisons across providers. In either case, the liquidity pool anyone can trade against is severely limited. Much of the innovation in other asset classes depends on venues behaving like mini-exchanges or Multilateral Trading Facilities (MTFs) for over-the-counter (OTC) products that can be packaged flexibly based on whatever two clients may want to trade. That works because an OTC instrument can be created to order. A listed contract cannot, it exists only on its own exchange, under that exchange's rules, product by product. So the venue model doesn't transfer. The need for centralised liquidity does. The practical result is that most listed derivative block orders can still only be requested manually, by phone or chat, which asks a trader to deviate from the automated, systematic, measurable process they use for everything else on the desk.
2. Liquidity is fragmented, and every route to it involves an uncomfortable trade-off.
Traditionally, desks build a panel of trusted, disclosed relationships with bank execution desks and non-bank market makers. Each of those relationships is bounded by the markets that its own desk can price together with the breadth of its own client base to match liquidity against, so there is a permanent incentive to grow the panel and deepen the liquidity available. That incentive can also be counterproductive. Ever more eyes on an order will make leakage harder to contain, and more counterparties make a manual request-and-compare process slower and more error-prone. BestEx justification, broker-versus-broker Transaction Cost Analysis (TCA) and hit-rate tracking are all difficult when the request is sent over chat, and harder still when the comparison you actually want is the one against how the algorithm would have performed.
3. Ceding execution means ceding visibility.
The alternative is to ask a broker partner to work the order into their liquidity provider network in an inter-dealer broker capacity, much as a buy-side trader might. The advantages are real, with access to a wider set of liquidity pools, and the ability to keep the client name anonymous, which limits leakage indirectly. What our clients describe is a loss of control over what happens after that. Brokers use partners they trust, but who do they ask in turn? That is not an argument that the service lacks value; the service is highly valuable. It is that the process is opaque, and cannot be measured or proven.
Put the three together and the rational response to fragmentation turns out to be more outgoing manual requests — the precise thing a systematic desk is built to avoid. That, I think, goes a long way towards explaining why so many traders choose the algorithm over the block even when the spread capture is sitting there in plain sight.
A vision for the future
The Wheel has revolutionised electronic trading, allowing trading desks to accurately quantify and compare algorithmic providers' performance and make statistically informed decisions in a systematic way. Its greatest limitation is that it precludes the largest, trickiest orders and the desk may even prioritise the benefits of a consistent process over the pain of blocking, to the detriment of performance. The Wheel needs to evolve. Central to this is making the negotiation of a block trade fully electronic and compliant with each exchange's own rules and guidelines, so that it can be benchmarked and, critically, ensuring that all market liquidity is centralised and accessible to all, regardless of direct trading relationships. In this way expected performance can be compared, not just across algorithmic providers but across liquidity sources: a ‘Blocking Wheel’. It is then a logical step to join these wheels into an autonomous model, picking the best execution method without constraint, or even working the orders concurrently in an algorithm whilst searching for a block. Finally, a Third Wheel that’s aspirational.
What we are building
InTick is that Blocking Wheel. An exchange- and broker-neutral block trading platform, built specifically for the complexities of listed derivatives, putting no single client’s interests above any other.
It sits as a secure buffer between buy-side intent and market execution, so traders can request and match pricing anonymously and information leakage is contained by design. Our all-to-all network enables firms to build on the relationships they already have while complementing those with additional pricing, without the need to face those providers at all.
Because that pricing is accessed directly, anonymously and systematically — alongside the algorithm rather than instead of it — the whole workflow becomes measurable. Hit rates, provider performance, the opportunity cost of the algorithmic alternative, BestEx evidence: all of it can be benchmarked to the standard the market already takes for granted in CLOB execution.
We founded InTick because we have lived this problem on the desk, and we built it with technologists who understood from the outset that replicating a familiar workflow faithfully is harder, and far more valuable, than replacing it. The market does not need to be taught a new way to block. It needs the friction taken out of the way it already blocks today.
If your desk blocks today, or has decided to use algorithms instead, I would be interested to know whether you recognise any of these frictions. Please get in touch with us for a demo.
Sources: Exchanges are ASX, CBOE, CME, Euronext, Eurex, EEX, HKEX, ICE, TMX, Nodal, LME, JPX, SGX. Data from websites & LSEG.