“You can’t connect the dots looking forward, you can only connect them looking backwards. So you have to trust that the dots will somehow connect in your future.” – Steve Jobs
It’s truly amazing what we find deep down in the weeds…
The solution to any puzzle starts with the pieces that are easiest to fit into place. Translation: Solutions can start most easily where the most granular data is readily available and easiest to interpret. In this case, and though not (yet) flowing smoothly from a firehose, that means regulatory disclosures based on long positions reported by various trading and asset management firms that correspond with the quarterly-updated 13F securities list managed by the Securities and Exchanges Commission (SEC).
At Alphacution, the core mission is to solve, and keep re-solving, a very large puzzle made up of many other smaller puzzles which, themselves, may contain even smaller, more detailed puzzles… Think of this like the claim made by the Kirk Lazarus character in the movie, Tropic Thunder – “I’m a dude, playing a dude, disguised as another dude…” – which, btw, just so happens to be metaphorically-consistent with the nested alpha idea that we have been playing with recently – and, ultimately is supportive of our 360º contextual modeling vision that allows us to use market micro-structure findings to make more empirically-based interpretations of market macro-structure impacts. Yep, that’s a mouthful…
In other words, we have made a ton of progress assembling models of various firms’ focus on US listed equity strategies (which also include ETFs and options and lots of other equity-related product classes). And, furthermore, our initial focus on exploring the nested alpha architecture concept has mainly leveraged a temporal vector – also focused mainly on equities – to describe how that architecture can be established across zones within our ecosystem map. This is another way of a saying that a single product class – mainly equities – is being traded at two or more average native turnover frequencies, as indicated in the chart below (and showcased in more depth in the recent Feed post, “Two Sigma Investments: How to Build a Nested Alpha Architecture.”)
The first point we want to make here is that nested alpha strategies that trade the same product class at different timing frequencies (i.e. – the intra-product class temporal vector) is not the only “vector” where the nested alpha concept can be applied. Consider Alphacution’s US listed market structure schematic (below) which attempts to present all the liquidity venues (inner rings) and top bank and non-bank market makers and prop shops (outer ring) in one diagram that ultimately is intended to represent the bulk of the activity in our structural alpha zone. (Soon, Alphacution’s research roadmap will lead to the completion of its initial rankings of this activity by firm. Stay tuned for that…)
Here, we want to call attention to the center of the diagram which represents a collection of each of the specific liquidity venues segregated by lit and dark venues (by variance of background shading of the inner-most rings) and color-coded by product class; as in, cash equity and equity-linked products (in blue), options (in yellow) and futures, including options on futures (in green). More on this schematic can be found in our introductory Feed post from February 2019, “Top 100 Players in US Listed Market Structure” and for extra credit, further expanded and explored in a piece from June 2019, “The Physics of Market Structure – Part 1.”
It is here that we begin to arrive at the central thrust of this Feed post:
Because it is here that we showcase the potential for another key vector within the nested alpha architecture concept; an inter-product class strategy vector where strategies are based on cross-product pricing inefficiencies that exist between cash equities, ETFs, options, futures and a few others. Once upon a time, these structural arbitrage opportunities could be harvested regularly by floor traders. Today, unprecedented levels of workflow automation delivered off the backs of tons of technology and scores of wicked smaat people is required to be even minimally competitive in harvesting these types of opportunities.
In parallel with this evolution, it used to be that players would tend to stay in their core product class. Futures traders stayed mainly in futures; option traders mainly in options (with natural crossover into underlying securities); and, equity traders stayed mainly in equities (with little or no crossover into options and futures). After all, there was plenty of capacity to grow a highly profitable trading business while remaining in one’s wheelhouse.
Alphacution wrote about this dynamic in one of its all-time most popular Feed posts from March 2018, “Virtu Financial: More Acquisitions on the Way, If…” Here’s the relevant excerpt from that piece:
“…market-making and other latency-sensitive prop trading groups have largely stayed in their original wheelhouses (the wheelhouses and cults of personality of their founders, with few exceptions), which are now roughly segmented into small groups of leaders defined by product class: Cash (equities), futures and options.”
Now, this assessment from March 2018 has a backward-looking bias because it’s based on historical data, all of which updates quarterly or annually. Today, the bias is similar, but the assessment has changed: There is more cross-product strategy development going on in our structural alpha zone than ever before. Strategy capacity constraints (among leading players with historical product class focus) plus increasing impacts of technical dominance are the two primary drivers behind that phenomenon; a phenomenon that not only has implications for those who possess these powers, but everyone else in the ecosystem, too…
Said differently, those players who are able to wield the combined performance of technology and human capital to lead – or, become dominant – in one product class are now more likely than ever before to be able to use that foundational engine across additional nested alpha strategy vectors.
So, let’s return to last week’s teaser “DRW, Jump Trading: A Brawl Breaks Out in the Futures Market” wherein we showcase the following chart comparing the total assets of the broker-dealer units of DRW and Jump Trading beginning 2001 and ending 2018 (below):
All we are looking to point out here, for now – without getting too far into the weeds as to why (including defending the probability of false positives) – is simply the clear evidence that something seems to have changed recently between two of the leading head-to-head quantitative competitors in the futures market – starting in 2017 – after tracking within a range of one another on this metric for the prior 16 years (see below).
Ok. Now, let’s try to build on this evidence by taking a very unexpected turn into some additional evidence that is truly fascinating on its own:
Latour Trading is the market making unit of well-known high-frequency prop shop, Tower Research Capital (TRC). Alphacution published its first Feed post on TRC/Latour – “Tower Research Capital: Keeping It Real…Tiny” – in May 2019, wherein we note some surprises relative to expectations based on our initial modeling of their 13F disclosures. Certainly, the fact that the market making unit and the prop trading unit are operating under different names – unlike just about everyone else in the space, except for the former Interactive Brokers Group – Timber Hill tandem; the latter piece now absorbed by Two Sigma – adds to the fog surrounding this unique example of our nested alpha architecture concept.
After a recent modeling update based on Latour’s FOCUS reports (on SEC Form X-17A-5) – and a meticulous reading of the notes (where we commonly believe that far more than the devil is living in details like these) – Alphacution is able to present an extremely rare and fascinating estimation of Latour’s trading gains – including volatility yardstick – for the 9-year period beginning 2010 and ending 2018 (see chart below). Based on reported data – and coupled with our assumptions – there is a case to be made that Latour – the market making unit of high-turnover equity powerhouse, TRC – may have never made its money in equities, with the possible exception of 2018.
Here’s a sketch for how we get to this picture and claim:
Latour has disclosed gains on futures, minimum performance fee rate paid by its parent (TRC) to Latour, and the amount of that performance fee for much or all of the 9-year period, 2010 – 2018. What we don’t know is the rate schedule (above the minimum) for the performance fee and for sure whether the gains on futures trading are disclosed as gross or net of expenses. So, we have assumed the minimum performance fee rate for each year to estimate total trading gains – and the gains on futures as gross to estimate trading gains on equities (including ETFs) against the estimate of total trading gains (which is calculated on the performance fee rate).
In those cases where the performance fee may have been earned at a higher rate (which is likely in some years), then total estimated (gross) trading gains would have been less, and therefore, estimated trading gains on equities would have been lower (all else equal). However, if gains on futures trading have been reported net of expenses, then the estimated trading gains on equities would have ended up being higher (all else equal).
Taking errors in our assumptions separately (where one is more accurate than the other), then there is a probable case to be made that the profitability of equity market making would have occurred sooner. Taking errors in our assumptions together (where both are not accurate), then there is a probable case to be made that the profitability of equity market making was relatively consistent throughout the period.
- We can say that Latour’s overall market making operation appears to be responsive to volatility (given a visual interpretation of the data presented along with claims made in disclosures – which is not a novel revelation, since all market making strategies that we have modeled to date display positive correlations with volatility);
- There remains a probable case to be made that the trajectory of futures trading is accurate; that gains in futures trading may have been in a long-term decline over the period; and,
- The profitability of equity market making component of the overall strategy may be lower than commonly perceived.
We just want to make sure – despite some bolded, italicized and underlined text – that we are not being overly sensationalistic about performance claims made based on the prior chart, given the likelihood of variance therein that have been discounted by our assumptions.
But, all this being said, it does bring us back to the competitive issue implied in the title of this Feed post because we can demonstrate that there are inter-product versions of our nested alpha concept. Here’s how we get to that claim, which is yet another fascinating aspect of the scenario found in the reported data: In the chart below, Alphacution presents Latour’s year-end long and short exposures in futures by average notional contract value (based on calculations made from reported data) for the six-year period beginning 2013 and ending 2018.
Now, since we know that the TRC/Latour’s US strategy architecture has its foundation in equities (and not FICC – or, fixed income, currencies and commodities), then we can assume that the futures exposures are likely to be concentrated in the most liquid equity-based contracts on the Chicago Mercantile Exchange (CME); namely, S&P 500 Index futures (including E-mini and Micro E-mini contracts). And, since we can calculate the (year-end) average notional value of those exposures, we can further assume that a component of this nested strategy architecture is an arbitrage between the variously sized S&P 500 futures contracts (i.e. – an intra-product class version). For instance, at year-end 2018, the average notional futures contract values imply that Latour is basically net short the big S&P 500 futures contract and net long the small S&P 500 futures contracts.
And yet, simultaneously, this play is also a component of a much broader strategy that is squarely in the wheelhouses of both DRW and Jump, among others.
Now, hold that thought for a minute – and let’s turn to take a quick look at the cash (equities) side of the book detailed in the same reporting: In the chart below, Alphacution presents gross equities securities value segmented by exposure to single-stock equities and ETFs for the five-year period beginning 2014 and ending 2018. Here, we see that the balance in (year-end) value between a portfolio of individual stocks and ETFs is either fairly equal (as in 2016 and 2017) or weighted – sometimes, dramatically – towards ETFs (as in 2014, 2015 and 2018).
With the addition of this graphic, Alphacution can begin to tie a bow around key findings and conclusions for this story:
It is likely that the market making operation of TRC/Latour is executing both inter- and intra-product class versions of a nested alpha architecture whereby fleeting pricing inefficiencies between various equity futures contracts and ETFs priced off of similar groupings of individual stocks has been deployed with great success since Latour was launched in July 2009. By adding what we know about the prop trading component of the strategy architecture – in the form of TRC Investments, LLC – we can extend these claims to include the temporal version of the nested alpha architecture. (Note that this outline of various nested strategy vectors does not begin to introduce evidence for intra- and inter-regional strategy vectors represented by additional TRC entities, like Tower Research Capital Europe Ltd., Tower Research Capital Europe B.V, and Tower Research Capital (Singapore) Pte. Ltd., among others.)
But, it is also likely from what has been presented above, that competition on the futures side has been heating up – DRW, followed by Jump, being in leading competitive positions on that score – thereby collectively causing a decline in the success of the futures component of TRC/Latour’s US nested alpha apparatus…
Why is all this so important?
Competitive threats may now have moved beyond the calibration of our common peripheral vision… So, no matter where you are on our “map” relative to the players showcased here, you are still in the path of their impacts. This is another way of saying: If you are searching for a more intelligent strategic response to evolutionary shifts in the competitive landscape, Alphacution is here to help…
Now, here’s one more fascinating nugget of awesomeness as a treat – Halloween is getting closer, after all – for those of you who have endeavored to consume this meal thus far and still have room for dessert:
Competitive challenges for TRC/Latour in futures, ETFs and individual equities notwithstanding, there is one notable gap in their nested alpha assembly. Can you guess what it is? Options. At least in the US, there is no evidence in the disclosure data that this trading operation has developed any prowess in option trading – and that fact is a medium- to longer-term disadvantage since the leading market making players in cash equities, ETFs and options are no longer a distinctly different roster of competitors, but a very short list of the exact same players.
Now, if we have just been spit-balling here, and the likes of DRW and Jump have been trying to poke TRC/Latour in the eye for having the stones to compete on their turf, what might DRW’s and Jump’s additional response be to that potential threat?
Answer: Go poke around on TRC/Latour’s turf.
Now, of course, DRW, Jump and others are not trying to settle scores specifically with TRC/Latour by developing capabilities in adjacent market opportunities. They all need to look to new horizons anyway – and, if our assumptions are even remotely correct, TRC/Latour’s profitability experience on the futures side may only be evidence of a symptom of the broader macro-structure impacts where alpha capacity constraints and player concentrations have converged to the point of now being more noticeable, given our uniquely broad assembly of the available data.
The leading futures players need to discover and harvest new sources of alpha – just like the equity-focused players and the option-focused players and the few leading inter-product class players, as well – because their core strategies are all under threat from generally increasing competitive threats brought by those leading firms who wield combined technology and human capital in increasingly productive – and sometimes, dominant – ways.
So, to complete tying the bow on this one – and stick the landing by coming full circle back to where we started – Alphacution presents the largest 13F position for DRW, Jump and Latour, all from Q2 2019:
What are the chances that DRW’s (21,964 contracts) and Jump’s (21,954 contracts) largest position – a SPDR S&P500 ETF put option position – is within 10 contracts of each other for the same quarter-ending Q2 2019?
It’s another puzzle… 😉
Support the Feed!
Note: Business credit cards and bank accounts can be used via our PayPal payment portal.
Alphacution is in the intelligence business.
For those of you who are eager to derive greater value from this work and apply that intelligence to your own business interests, Alphacution is offering unaffiliated individual subscription options priced at $275 per year or $25 per month, cancellable at any time. Both of these options include a rebate on purchases of deeper, more substantive reports and case studies.
In other words, the entire value of an individual subscription paid up to the point of purchasing a single report will be deducted from the purchase of that report. (Rebates not to exceed the maximum value of an annual subscription.)
Enterprise subscription packages for individuals affiliated with trading firms and custom content/service engagement options are available upon request at email@example.com.
Now, for those of you who don’t expect to take advantage of the offers outlined above but want to continue to enjoy the insights, intelligence and occassional entertainment that remain openly available on the Feed, I want to make this specific plea:
Free doesn’t mean there are no costs. In fact, in this case, there have been extraordinary costs in the accumulation of experience and sight, meticulous curation and assembly of data, and creative visualization of and storytelling around our findings.
So, if you value quality content – here or anywhere else – then you need to find a way to support that content at some level simply because you want it to continue to exist. Our post, In Support of Digital Content – which was adapted from other notable digital era content developers – makes a more expansive case for this perspective.
Bottom line: Your efforts to support via one-time or recurring contributions will help guard against this content needing to move from the currently preferred audience-driven model (for its level of independence) to a sponsorship-driven model (which can be found on most other industry media outlets).
So, if none of the subscription options suit you, one-time and recurring support contributions can be made at any level here:
Of course, as always: If you value this work, please continue to “like it,” share it, comment on it – or discuss amongst your colleagues – and then send us firstname.lastname@example.org.
As our “feedback loop” becomes more vibrant – given input from clients and other members of our network, especially around new questions to be answered – the value of this work will accelerate.
Don’t be shy…
Unsubscribe from prior subscriptions without further obligation, at any time, here: