What are the current pain points associated with accessing liquidity?
We regularly hear from clients, and we observe in our data as well, how much easier it is to trade in the US. Focusing on the challenges of moving liquidity should be done on a regional level. In Europe, that certainly is not an insignificant issue, but sometimes it can be a little overstated.
Firstly, we see a significant amount of liquidity being transacted through our high-touch trading operation. We run a big high-touch trading desk with very experienced personnel, and an incredibly broad range of clients that we’re trading on behalf of. What we’ve seen evolving over the years, is not necessarily the coming together of two orders that happen to offset each other, but where we have an awareness of a client’s interest in transacting in significant size; in a particular name; and in a direction and some sort of price level. We use our network of clients, and the trusted relationships we have, to see if we can generate the other side of that trade. Essentially, creating liquidity in that space.
Rather than waiting to see which client happens to have a contra-side order already on their desktop, which is ready to go, more often what happens is the initiation of a conversation with a buy-side trader. That buy-side trader would speak with their portfolio managers, and that portfolio manager could then potentially respond to the liquidity opportunity that is being presented to them. We’ve seen a significant uptick in the frequency of trading which occurs around that type of scenario, and that has increased the ability of clients to get business done in a meaningful size. That has been a very positive development for our clients, and we’ve seen a continued increase in our breadth of counterparts as a result.
The second component I think is very different and sits in the algorithmic space. The challenges that exist here are linked to how hyper-efficient firms have become at monitoring data that exists on tape, both pre-trade and post-trade. As a result, a price impact can occur from every interaction taken with a public market – be that a lit market or a dark pool. Within the lit market space, that impact is much greater – though, that might not just be about a trade, but rather about a child order placement. The effect we see of placing a passive order onto a lit order book is meaningful and carries a cost for the entire life cycle of that trade.
How can trajectory crossing help with gaining access to liquidity while controlling the price impact?
The size of the impact that can accrue from tapping into the lit market – either to trade aggressively across the spread, or to trade passively while trying to track liquidity and capture the spread – is significant in terms of the overall cost of trading. If we can reduce the requirement to have to interact with the market in that way, our data shows you can drive a performance uptick in overall parent-level execution performance. Trajectory crossing is one of several different mechanisms that exist to match buyers and sellers.
Trajectory crossing can meet a need that isn’t met by other instantaneous matching options for orders that don’t want to trade at midpoint right now, but do have a liquidity requirement accruing over the next ‘x’ minutes. A critical differential is that in the event contra-side orders do not offset perfectly, the smaller order can still pick up a price improvement from any price impact caused by the larger order transacting in public markets over the life of the trajectory cross. This is because the price of the match is determined at the end of the period not the start, like an instantaneous mid-point cross would be, and thus trades taking place on the tape in the window would contribute to the benchmark price used for the trajectory cross.
Trajectory crossing has been around for a long time, focusing on matching two offsetting VWAP orders. Jefferies has extended that to have all strategies think in time space, even high urgency liquidity seeking strategies. These have a desire for as much liquidity as they can right now, at midpoint, for example, and we have a range of internal and external options to achieve that. But, if that liquidity seeking strategy can’t capture all of its desired liquidity right here and now, why would it not be willing to take an incremental piece of liquidity from a VWAP order or a POV order that is going to be available not right now but over the next minute?
By combining this capability across multiple strategies, we can increase the amount of liquidity we can source. The value of that then becomes your reduction of usage of lit markets – the reduced amount of price impact and information leakage that you have along a trade order life cycle. Our data is very clear that the greater the percentage of an order that has been matched on a trajectory crossing basis, the better trading performance is against both arrival price and an interval VWAP.
How is the drive towards tech-based trading solutions impacting market competitiveness?
The complex nature of the market, and the ever more detailed and nuanced behaviours you’re required to deploy within a trading approach, have continued to increase the barriers to entry.
To become an expert in algorithmic trading, and to have a platform that is able to carry across the vast spectrum of liquidity venues that exist; the wider range of order types; the incredible number of algorithmic sub-tactics that exist, and have been developed for very specific purposes – which are then combined to meet the individual parent-order requirements at any given point in time, mean that any kind of new entrant into the space is faced with a significant gap in terms of functionality.
To close that gap, and become competitive in any way, is a financially significant – and time-consuming – undertaking that could potentially result in making it hard for new entrants to join, which could be deemed as anti-competitive.
On the other hand, in the world of algorithmic trading – particularly the sphere Jeffries operates in – we are a client implementation, secondary markets, trading firm. We aren’t trading our own prop, or anything similar, on these algorithms. We use them to make our clients’ implementation experience better. There are still a significant number of incumbent providers, and there’s sufficient variation in those providers – from an overall firm profile perspective to product specific ethos differences – to offer a good spectrum of options for clients, even if it’s harder for new entrants to break in.
How are smaller firms impacted when tapping into liquidity pools due to these advancements?
From a buy-side trading perspective, a smaller firm has no material disadvantage. Any client that approaches Jefferies, or transacts with Jefferies, will have access to the full execution suite that we offer irrespective of whether they are likely to transact a million dollars a day, or a billion dollars a day. Challenges are greater for smaller sell-side firms, given they may be lacking the technological capabilities to navigate across that landscape.
The other thing we have seen over the last couple of years is the additional alternative liquidity providers – who are dealing on a much more proprietary basis – having a bilateral relationship with buy-side firms while not intermediating between them and the market. These firms are generally smaller than traditional brokers in overall size, but can provide a viable liquidity proposition in some scenarios. What they don’t have is the requirement to be everywhere, all the time. They’ll be able to provide liquidity where it suits them (and to whom it suits them), and then they’ll step away when it doesn’t.