“Education is all a matter of building bridges.” – Ralph Ellison
How trading firms, hedge funds and asset managers scale – as in, scale assets under management (AUM) or proprietary capital, headcount, data, technologies, and other operational ingredients to support a growing mix of market strategies when their initial market strategies reach boundaries of performance, liquidity, inventory or competitive challenges – is a significant point of fascination here at Alphacution. This is because scaling – real, sustainable scaling – requires simultaneous and interdependent success in both operational and trading strategies.
Scaling also becomes a critical issue to measure and monitor from a market macrostructure perspective if you believe the hypothesis that the capacity of alpha is finite, as we introduced in the Feed post, “The Privatization of Alpha.” Because if you believe that there are no constraints on the capacity of outperformance – or, “alpha” – then there is no need to pay attention to how various asset managers scale their strategies and their overall businesses. In this scenario, there is plenty of outperformance to go around, no matter how big everyone becomes.
However, if you believe there is some scarcity factor here – given limitations of securities product inventories, liquidity of those products, and the volatility of those products – then the growth of one trading firm may be coming at the expense of other trading firms; the concepts behind which we laid out in the series of Feed posts, “When Market Makers Ate Their Own,” “When #HedgeFunds Ate Their Own,” and “When #ETFs Ate the Beta.” – each of which relating to their respective zones in Alphacution’s asset management ecosystem map. And, since those few who are most successfully wielding technology (and workflow efficiencies) to discover and harvest alpha – most clearly observed and measured in our structural alpha zone – also tend to cause markets to become infused with a winner-take-all dynamic, then measuring the impacts and pace of impacts becomes increasing important for everybody else. You (should) know who you are…
Sure, there are occasionally those wildly successful managers who are content to harvest consistent dividends, year after year, without much focus on moving much outside their original box. In these cases, managers will typically return any outside money to the point where they become entirely proprietary. Jim Simons’ Renaissance Technologies is perhaps a prime example here.
And, yes, there are those managers that try to scale only to end up losing the baby with the bath water when their core strategy unexpectedly dries up, or when increasing scale becomes unwieldy – or, in the case of some, stealthy competitors eat the alpha right out from under their nose. In the market making and high-turnover strategy space, the roster of those who have had – or, are in the process of having – their pockets picked by faster and smarter players continues to grow.
On the basis of this chain of logic, it is not only fascinating – and important – to quantify the strategies and pace by which certain players grow (and occasionally dominate), it is therefore equally important to measure how they decline, too. It turns out that a broadly-defined asset management ecosystem – one that includes market makers and high-turnover prop traders along with hedge funds and ETF-issuing behemoths – is like a massive Sudoku puzzle; one where the geometry of both increasing and decreasing time series of factors provide contextual value for that which we don’t already know through observation, or the “empty cells” in this proverbial puzzle.
Alphacution is the only independent research and advisory platform performing this type of analysis – and it’s good to see that some folks in the neighboring zones of our map – the active and passive management zones – are beginning to realize that the dynamics and impacts being showcased through our modeling of the structural alpha zone (where the bulk of our current focus resides) represents a wave that is heading their way. Over the course of the coming year, we expect to complete the initial modeling phase of the structural alpha zone, and therefore, be well-positioned to expand our analysis to focus on the active management zone where virtually all hedge funds are located.
With these thoughts as preamble, let’s move to bring a taste of some of the analysis from our upcoming case study on the quant powerhouse, Two Sigma Investments – a punctuation of sorts on our previous case studies on Citadel and Susquehanna Investment Group (SIG) – into the picture:
Still focusing on the players and strategy spectrum within or tethered to our structural alpha zone, we have found so far that those few who have had the most success in scaling what amounts to a portfolio of market strategies – even in cases where core strategies dry up or, on the other end of the spectrum, reach capacity constraints (a factor that is a significantly greater threat in high-turnover land) – have some characteristics in common. Taking the assembly and deployment of sophisticated technology plus a maniacal sensitivity to workflow engineering as a baseline, the factor we are trying to showcase here in some detail is strategy diversification.
Now, effective strategy diversification is based on adjacencies. In this context, adjacency simply means the next closest strategy to the one(s) that is/are already deployed. And, though there are always exceptions and lots of nuance, the categories of adjacency typically come down to some version of multi-regional, multi-asset class, and multi-product class.
Early on, Alphacution found that the leaders and contenders in this zone of the map have tended to be delineated by diversification along product class lines, broken down by cash equities, options and futures. Citadel Securities led in equities (including ETFs), Susquehanna Securities led in options, and DRW Securities led in futures – where each of these firms represents the broker-dealer affiliate of those well-known parent organizations. Today, these lines are becoming blurred as leading firms find success across a matrix-like multiplicity of product class, regions, and asset classes. Nevertheless, the additional focus on these affiliates has become a very important factor in the prioritization of Alphacution’s modeling, which ultimately led us to the concept of a nested alpha architecture.
It turns out that there is one more category of strategy adjacency called multi-temporal, and it is the most complex and technology-dependent category of them all. First explored, in part, in a report I wrote for TABB Group in 2011 – “Quantitative Research: The World After High Speed Saturation” – multi-temporal strategy diversification simply means to trade one or more (listed) product classes at two or more native turnover frequencies (TOFs). Common example: equity market making (TOF ~ sub-second to intraday) and statistical arbitrage (TOF ~ days to weeks).
The idea, in the case of this initial report, was essentially for high-frequency traders (who were struggling to keep up with competitive forces brought on by a technology “arms race”) – or, those who wanted to get into or stay in the quant game – was to identify new sources of alpha with slower turnover frequencies…
This is where multi-temporal strategy diversification evolves to include a nested alpha architecture: With few exceptions, all of the players on the outer ring of our Top 100 Players in US Listed Market Structure Schematic (pictured below) are registered as broker-dealers. And, all of these are also market makers, where market making and highest-speed trading are now one and the same.
But, more than the value in capturing spreads through market making / high-speed trading, it turns out that a BD affiliate for a broader asset management or hedge fund platform, presumably with slower trading strategies, is a very useful thing to have because of 1) the potential for savings in execution costs for the hedge fund side, 2) the potential for tactical market information that can be factored into slower alpha models, and 3) the potential for fundamental overlays from the hedge fund side to be used in portfolio construction in cases where there is a very large market making book. This architecture – broadly speaking, a quant hedge fund with a market making affiliate – is what must be in place to cause two or more sources of alpha, with information asymmetries that occur as two or more distinct temporal “waves,” to become “nested” in a way that is mutually symbiotic.
Moreover, where this strategy architecture becomes more interesting is in how they have been built. It turns out that there are two examples – an outside-in bridge and an inside-out bridge – wherein the “bridge” represents a straddling of the structural alpha and active management zones of our map, outside-in means the initial strategy was launched outside the structural alpha zone and inside-out means the initial strategy was launched inside the structural alpha zone (see below):
A few examples of firms that are leveraging a nested alpha architecture, and yet are at different stages of development, include:
- Citadel Advisors / Citadel Securities: The leading success story in the deployment of nested alpha and the most dominant player overall in listed markets, highlighted in an Alphacution case study (available to premium subscribers). Outside-in bridge strategy.
- SIG / Susquehanna Securities / G1 Execution Services: The leading player in options and leading contender overall (across equities, ETFs and options), particularly with the acquisition of G1 Execution Services – also highlighted in an Alphacution case study (available to premium subscribers). Inside-out bridge strategy.
- Tower Research Capital / Latour Trading: Sizable trading book plus low average position size suggests that their TOF is shorter / faster than the leaders above.
- Wolverine Trading / Wolverine Asset Management: Relative to the leaders above, a mid-sized option market making prop shop with an asset management arm that begins with a convert arb strategy around 2003 that migrates over the past 5 years to a hedged equity strategy (>50% (13F long) position weighting in equities, <10% in calls, and ~20% in puts).
- Two Sigma Investments / Two Sigma Securities / Timber Hill: Among the most successful quant hedge fund operations of the last 15 years, Two Sigma is the most recent of the leading trading platforms to discover the value of a nested alpha architecture, and then work to implement an outside-in bridge version of the strategy with the launch of their broker-dealer, Two Sigma Securities, in 2009 and the acquisition of Interactive Broker’s option market making unit, Timber Hill, in 2017.
With the upcoming publication of our next case study on Two Sigma, this is where we will bring this post to a close, for now, with the following thoughts: As Alphacution has been building out the first major phase of buy-side modeling, the key leaders – particularly those related to our nested alpha architecture concept, Citadel and SIG – have already been established. Their challenges are unique because they already trade just about everything in the listed (13F) universe that we track, and therefore, directly face off with a multiplicity of capacity issues.
Two Sigma is unique in a different way because it is in the process of building a nested alpha architecture for the listed universe, and therefore, watching them build it out from where they are now is likely to provide unique insights into the viability of this multi-temporal strategy expansion at such a different point in the cycle than other notable examples mentioned above.
Here’s a representative picture of that development to date:
UPDATE: Now, after all of what has been presented above, it turns out that we have explored some of the nested alpha concept before, perhaps even a bit more eloquently. Find that exploration in the executive summary to our case study, “Deconstructing Citadel Securities” below:
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