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Propeller-Head Ubiquity, Part 1: The Next Generation of Quantitative Trading

Paul Rowady, TABB Group

20 June 2014

Traditional, high-turnover quant equity strategies are saturated. As competition has heated up and the arms race of latency-sensitive infrastructure relative to the perceived theoretical alpha has shifted, quant firms have been seeking new sources of performance.

TABB Group has been closely studying and commenting on the evolution of quantitative trading for many

years. And though the fruits of quantitative research methods have permeated a vast spectrum of trading

strategies within the past several years, high-turnover versions of quant strategies traditionally attracted the

most attention. They still do. This is primarily because of their awe-inspiring departure from anything related

to human-scale methods as well as tales – and growing evidence – of their staggering risk-adjusted returns (and

absolute profits). Paradoxically, extreme success always defies attempts to remain hidden, providing attractive

scaffolding for pundits, media and students of the markets on which to build their narratives.

In June 2011, TABB Group published “Quantitative Research: The World After High-Speed Saturation.” (Ed.

Note: TABB also produced related videos as well – they can be found here and here.) Our hypothesis at that

time was that the “latency arms race” would result in fewer players capturing more theoretical capacity in core

markets, asset classes and products – a phenomenon we called the “tip of the spear” – thereby forcing all high-

speed quant players (that were committed to remaining in the game) into new or additional regions, asset

classes, products, and/or slower turnover frequencies. In other words, ultrahigh-speed trading in US equities

had become saturated around that time, and that players would need to diversify. Here’s an excerpt:

“If last year’s [2010] Securities Industry and Financial Markets Association (SIFMA) technology

conference was any indication, the saturation of latency eradication systems was palpable, indicative of the changes we face today. A handful of firms—wearing both sell-side and prop jerseys—are

successfully defending the limited capacity in high-frequency and micro-market structure arbitrage

strategies in the US. With the prohibitive costs of incremental speed and dwindling volumes, punctuated by regulatory zeal, the average quant team must face up to the inevitable: change or die.

Alpha is elusive, ephemeral and enigmatic. There is no guarantee of persistence.

“For many of the players, the required measure of change will be too much to handle. Over the past year, two prominent option-focused prop shops have yielded to the superior speed and prowess of

their competitors and taken their balls home. In one of these cases, you couldn’t possibly have thrown

more bleeding-edge, out-of-this-world low-latency technology at the problem. The impediments were beyond hardware, but more likely related to a lack of quantitative creativity. Undoubtedly, others will

follow.

For those willing to brave the journey ahead, there are plenty of juicy opportunities to explore, some

of which will certainly surpass the capacity and profit potential of current microstructure arbitrage trades. “But hunting for new sources of alpha requires new gear. Surrounding and feeding this new

gear is a requirement for new skills. Quants need to cultivate a new zest for solving even messier data challenges; they also need to develop a passion for the financial equivalent of a deep anthropological

dig.

The need for speed will never end. Only the disproportionate focus of the recent past will be

reallocated. “Cross-asset, cross-regional, multi-temporal, asymmetric versus symmetric trades, and even enhanced front-to-back automation will all benefit from this reallocation. Welcome to the age of

multidimensional arbitrage.”

In March 2014, we conducted a survey to help update our understanding of the pulse of the quantitative trading

landscape. Based on our understanding of quantitative history – and coupled with these latest survey results,

TABB Group is updating its vision and hypothesis for the quant landscape: First, saturation has spread beyond

US equities into other regions, products and asset classes. Today, fewer players are capturing more of the

available theoretical capacity for global high-speed alpha. Second, the future for quantitative methods has

never been brighter. Our multi-dimensional alpha concept is still intact. But the bridge from here to there will

require new skills and the digestion of a lot more data. Quantitative methods will permeate more of the

traditional investment strategy spectrum to the point of “propeller head ubiquity.” Oddly enough, ubiquity will

serve to shroud quants in a cloak of invisibility. Automated methods will become indistinguishable from

everything else. The only question now, is: On what timeline?

Although the metaphor might not be entirely accurate, we can’t help but think of the Roadrunner and Wile E.

Coyote – with the quants starring as the Roadrunner and the rest of us observers – for better or worse – as Wile

E. Since mid-2011, the lather over high-frequency trading (HFT) has only grown, especially recently with the

publication of Michael Lewis’s “Flash Boys.” Beyond the ebbs and flows of the media circus, however, there

are many more tangible clues that have added up over the interim period that have provided rare glimpses into

the revenue breakdowns of leading proprietary quant shops – and that further serve to support or alter our

original hypotheses: that those firms engaged in the highest-turnover strategies, and primarily those focused on

US equities, would need to look elsewhere; to focus in other regions, asset classes, and products – and,

ultimately across all of these, including slower turnover frequencies. We have called that new era, multi-

dimensional alpha

Since mid-2011, the regulators, too, seem to be more “on their game’ when it comes to high-speed trading in

comparison to many other topics. The January 2013 rollout of the Market Information Data and Analytics

System (MIDAS) by the US Securities and Exchange Commission (SEC) is quintessentially indicative of the

idea that Wile E. may finally be gaining ground on the Roadrunner (see Exhibit 1).

Exhibit 1: MIDAS - Order Book Reconstruction Visualization Tool

Source: Securities and Exchange Commission

Unlike in the cartoons, however, TABB Group believes that Wile E. does periodically catch up to the

Roadrunner – that the observers and analysts can eventually attain enough insight into how certain

microstructure arbitrage strategies work. That part is really the story of alpha decay and natural information

leakage and why purveyors of these strategies need a continuous flow of new ideas. Because of this dynamic,

our original prediction on the growth of multidimensional trading was right, at least in part. Are we at the end

of the high-speed arms race? Could we have finally reached the theoretical capacity at the “tip of the spear”?

Could there be only one firm capturing all of it? And if so, what’s next?

2014 Quant Survey

TABB Group’s March 2014 survey of market participants targeted mainly quants, but generally any informed

observer of the evolution of quantitative trading strategies. Exhibit 2, below, is a breakdown of firm types from

the survey.

Exhibit 2: Survey Methodology – Breakdown of Firm Types (N = 51)

Source: TABB Group

However, before we dive in to the newest clues of the evolution of quantitative trading, it would make sense to

showcase the prism through which we are observing this landscape. It turns out that, though broad in terms of

the possibilities, the scope of those possibilities is finite. Most quant strategy discovery begins with identifying

sources of theoretical capacity.

Quantitative Theoretical Capacity Framework

At its base, this story is about automating that which formerly has been done manually. First, tasks in a

workflow become automated, and then significant components – if not, the entirety of the workflow – become

automated. Following full workflow automation is refinement, optimization, and higher-performance

automation. In some product classes, we are clearly at the stage of highest performance automation; and where

microscopic shifts in market structure implementations can open and close arbitrage opportunities in an instant.

Where do quants look for alpha? The optimal target must exhibit a convergence of factors, but generally comes

down to two: liquidity and level of automation. (A third factor – complexity – makes the scenario even more

ideal, but we will get to that later.) Those products that are liquid and highly automated represent a breeding

ground for high Sharpe Ratio (SR) strategies. This means that smaller players can leverage a small amount of

capital for high returns with low risks (see Exhibit 3).

Exhibit 3: Quantitative Strategy Framework

Source: TABB Group

The fact that quant equity strategies can have little or no exposure at the end of a day makes all the difference

in the world; since holding positions overnight creates margin requirements and an exceedingly more complex

level of portfolio construction, going home flat is a huge deal.

But as competition has heated up and the arms race of latency-sensitive infrastructure relative to the perceived

theoretical alpha has shifted, quant firms have been seeking new sources of performance. This means

migrating beyond the high-capacity/highest-Sharpe Ratio products (blue zone, above) closer to the fringes of

capacity and SR (green zone, above). Generally, this means new regions, products and asset classes.

This was the claim we made in mid-2011 – and more specifically in mid-2013 – that quant firms would need to

look in new product classes, asset classes, and regions. Turns out the Roadrunner was already a few steps

ahead of us.

In the next installment in this series, we showcase and respond to the findings of the March 2014 quant survey. In Part 3, we highlight publically available data from two leading high-speed trading firms that ultimately

complement the survey findings. And Part 4 summarizes TABB Group’s latest views on quantitative trading and methods.

© 2009-2014 by The TABB Group, LLC and contributors | info@tabbgroup.com | +1-646-722-7800

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Propeller-Head Ubiquity, Part 2: Special Sauce and High-Turnover Diversification

Paul Rowady, TABB Group

27 June 2014

As quant firms have been forced to expand the search for theoretical alpha to new asset classes, regions and products, the ingredients of their ‘special sauce’ may be shifting too. And the search may be getting harder and harder.

This is Part 2 of a 4-part series on the next generation of quantitative trading. View Part 1.

The components of competitive advantage – or “special sauce,” in the vernacular – for quantitative trading

firms are among the most intensely discussed and often misunderstood topics on the global markets landscape.

To better understand these competitive ingredients, TABB Group conducted a survey in March 2014. Our line

of questioning divided the “sources of competitive advantage” framework into four components: human

capital, software and processing, data, and hardware and infrastructure.

When asked to rank these components, survey participants were clear in their opinions overall. Human capital

– translated by TABB as developer, analytical and management skills – is the most important ingredient for

special sauce in quantitative trading/methods; and, surprisingly, hardware and infrastructure – the stuff that is

perceived to deliver the speed – was ranked last. Software and processing vs. data as competitive components

were ranked almost evenly (see Exhibit 1).

Exhibit 1: All Survey Participants - Sources of Competitive Advantage (n=27)

Source: TABB Group

These rankings were different from what we expected. However, looking more deeply into the results,

proprietary trading firms expressed differing opinions from the broader sample – and ones more in-line with

our original expectations (see Exhibit 2).

Exhibit 2: Proprietary Trading Firms - Sources of Competitive Advantage (n=14)

Source: TABB Group

When these results are taken in conjunction with the results from the expected change (1-2 years from now) in

sources of competitive advantage (see Exhibit 3, below) and overlaid with our experience with quantitative

trading strategies, we reach the following conclusions:

Hardware: Hardware and infrastructure is a declining source of competitive advantage for a vast majority of quant players. TABB Group has been calling this the democratization of infrastructure for the past year or more. Going forward, quantitative firms will 1) off-load more of their infrastructure needs, and 2) simultaneously migrate more infrastructure to one focused more on computational engines able to execute more complex calculations at much higher speeds than today.

Human Capital: TABB believes that human capital should always be ranked highest relative to the other components of competitive advantage, independent of trading strategy or stage of workflow. Human capital is the one source of special sauce that is least susceptible to democratization. This is where we found the strongest shift in opinions in the survey data. Furthermore, TABB believes that certain players’ high ranking of hardware and infrastructure is actually a misinterpretation of the value of their human capital. With proprietary infrastructure remaining a key competitive advantage by a declining list of firms, persistence of this special sauce can only happen by virtue of the skills and creativity of their employees.

Data: Though we might have expected a different outcome from these results, it is true that data – or at least, raw market data – is the most democratized of the four components in our framework. For certain asset classes and products in the most developed regions, both historical and real-time market data is incredibly clean. Scrubbing unclean market data used to be a competitive advantage. Now it is not. Along the road ahead, new strategies will require a mix of new and different data sources.

Exhibit 3: All Survey Participants – Expected Change in Sources of Competitive Advantage (n=27)

Source: TABB Group

Low-Hanging Fruit

TABB Group has been monitoring closely the diversification of high-turnover – and the broader spectrum of

quantitative – trading strategies for many years. Our claim in 2011 that ultrahigh-speed trading in US equities

was saturated is further borne out in our most recent findings. The difference between 2011 and now, however,

is this: While US equities were saturated – where leading quant firms were often consuming the alpha of other

slightly slower quant firms – other regions, asset classes and products were not nearly as saturated.

The question now is whether any of these lower-hanging opportunities still exists within the scope of

ultrahigh-turnover strategies. Or has saturation proliferated into other assets, products and regions? The answer

to these questions will have a strong impact on the next generation of quantitative research and the

development of new automated trading strategies.

Asset Class Diversification

Survey participants’ rankings of current and future comparisons by asset class support TABB Group assertions

that there continues to be a need for diversification into additional asset classes, particularly fixed income (see Exhibit 4).

Exhibit 4: Quantitative Strategy Rankings – Current and Future Comparison by Asset Class

Source: TABB Group

Our survey finds clear expectations for increased focus on FX and fixed income, which have the greatest

potential (comparative theoretical capacity to equities notwithstanding) among all asset classes. However, in

the case of fixed income, we are concerned that the pace of transformation to more automated trade workflows

is slower than expected – or desired. The pace of adoption of electronic execution of a broad spectrum of fixed

income products (cash and derivatives) may not supply enough opportunities when compared to the demand

for new high-turnover strategies.

Product Class Diversification

Product class diversification is primarily focused on cash, futures and single-stock options, where “cash”

represents cash equities and equivalents, like exchange-traded funds (ETFs) and exchange-traded products

(ETPs), but does not include cash bonds and is presumed not to include spot FX (even though technically it is

the ultimate cash product) – and where futures represent multi-asset exposures. Since options on futures

typically have low liquidity, the options category here relates primarily, if not totally, to single-stock options

(see Exhibit 5, below).

As with expected asset class diversification (above), survey participants also expect the focus on the more

mature products in quant strategies to decline, although for different reasons. The issues in cash equities are

well noted herein. Newer products, such as swap futures, are worthy of experimentation across the expanded

spectrum of rates products, but their current low level of liquidity and concentrated adoption may not justify

the investment right now. Cleared swaps are similar in terms of potential for experimentation, but the timing

might not yet be good – and the average trade sizes are still way too large for most quant shops.

The one exception in core cash equity strategies has been the intense interest in and addition of ETFs and

ETPs, which have highly similar characteristics to equities with the added potential for “index arbitrage-like”

overlays.

Exhibit 5: Quantitative Strategy Rankings: Current and Future Comparison by Product Class

Source: TABB Group

Single-stock options markets are not only fiercely competitive with a number of seasoned incumbents; they

also represent uniquely complex computational challenges. As a result, it will be fascinating to see how well

high-frequency quant firms born in the equities arena enter and grow in the options arena. Other than fixed

income, options also may offer compelling potential, but they represent markets that are very difficult in which

to compete and harvest alpha.

TABB Group believes that this is a space that could see some (M&A) transactions. So far, leading equity-

centric HFT quants have been able to migrate smoothly into futures products, competing well with futures-centric firms such as Infinium Capital, Jump Trading, and Chopper without the need to partner. It remains to

be seen whether the same dynamic will play out in options. Maybe this is what Virtu is really after with its IPO

– a better currency for transactions. That said, the jury is still out on how well New York-Chicago mergers

actually work in practice.

Regional Diversification

Regional diversification is a classic move to extend the theoretical capacity of core alpha. The original options

market-making powerhouses of the 1970s and 1980s, inclduing O’Connor & Associates, first took their special

sauce from Chicago to New York, Philadelphia and San Francisco. From there, they sought to “O’Connorize”

derivatives markets in London, Tokyo, Sydney and elsewhere. It’s a fairly well-worn path.

So, too, have noted quant firms – especially high-turnover quant firms – marched from Chicago, New York,

Amsterdam and a few other locations to set up shop outside of their home turf. Though often proving

successful in highly developed markets, liquidity, and therefore, theoretical capacity, falls off dramatically

from there. So, while there are numerous other markets where core quant strategies will work well, the level of

profitability may not justify the technology investment in the current environment. Survey responses suggest

that there is movement of focus from developed markets to developing and emerging markets (see Exhibit 6).

Exhibit 6: Quantitative Strategy Rankings: Current and Future Comparison by Region

Source: TABB Group

As we look back across developments in asset classes, products and regions, we can’t help but wonder if the

saturation we saw in 2011 in US equities has spread across the full spectrum of high-turnover strategies. If

high-turnover strategies for cash equities, futures and options in developed markets are pretty much at the point

where leading HFT firms are consuming the alpha of other HFT firms, then that is likely a signal that the pure

speed game is just about played out for new and most existing high-speed firms.

High-Hanging Fruit

Shifts in quantitative trading strategies can be detected by shifts in the types of data being consumed. The

slower the turnover, the more other types and sources of data are required beyond tick-level market data. These

sources can be broadly bucketed into categories such as market data, reference data, fundamental data,

commentary (including traditional news, industry research, and social media), and the derived data – or

analytics – that flow off the back of all that raw data. The ranking of data categories reflects the amalgamation

of quantitative strategy needs (see Exhibit 7).

Exhibit 7: Rank of Data Source Types (n=27)

Source: TABB Group

These reactions are supported, in part, by additional findings from the survey. While there are still firms seeking more speed, the desire to slow things down is non-trivial. Nearly 20% of respondents claimed their

average turnover frequency (TOF) was slowing. With this fact in mind, we would then expect portfolio

construction to shift from more asymmetric – where positions are independent – to more symmetric – which

relies on portfolio construction, rebalancing and maintaining market neutralities – since asymmetric strategies

most often rely on speed. This is also evident in the findings, where symmetric strategies represented at least

29% of the responses (see Exhibit 8).

Exhibits 8: Quantitative Strategies: Changes in Turnover Frequency and Portfolio Construction

Changes in Turnover Frequency

Nature of Portfolio Construction

Source: TABB Group

We confess that there are some notable flaws in these findings, as well – which have more to do with survey

construction. For instance, “faster” – in the “Changes in TOF” chart above – could mean several things,

including slower strategies becoming faster, but not at the same scale as the micro-second crowd. Bottom line:

It seems odd to say, but if the latest generation of high-turnover strategies represented the equivalent of low-

hanging fruit, then the next generation of quant strategies will need to pick the fruit from much higher up in the

proverbial tree.

© 2009-2014 by The TABB Group, LLC and contributors | info@tabbgroup.com | +1-646-722-7800

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Propeller Head Ubiquity, Part 3: A Rare Glimpse into Prop Trading’s Strategies and Profitability

Paul Rowady, TABB Group

08 July 2014

It is extremely rare for the public to get a glimpse into the profitability, revenue segmentation, or strategy breakdown of a proprietary trading firm. But in the past two years, the public has been gifted unprecedented transparency into two of the world’s foremost quantitative prop trading powerhouses: GETCO and Virtu.

This is Part 3 of a 4-part series on the next generation of quantitative trading. View Parts 1 and 2 here.

It is an extremely rare event when the public gets a glimpse into the profitability, revenue segmentation, or

strategy breakdown of a proprietary trading firm. In recent memory, it is not since the attempted IPO of

Chicago proprietary options trading firm Peak 6 in October 2001 that we have had such a look.

However, in the past two years, the public has been gifted unprecedented transparency into two of the world’s

foremost quantitative prop trading powerhouses: GETCO and Virtu – the first as a result of GETCO’s merger

with Knight Capital, and the second as a result of Virtu’s ongoing IPO trajectory (which, as many know, has

since been delayed). Both events and the associated filings gave us a taste of all three of the above:

profitability, revenue segmentation, and high-level strategy breakdowns.

Both the words and the numbers in these filings tell a story that TABB Group has been following for years. In

the GETCO – now KCG – data (below), we can see how a high dependence on “Americas” trading (most

likely focused on US equities market making) in the 2009 (and earlier) period led to regional diversification,

mainly to Europe first and then Asia-Pacific (APAC), which in this case includes Singapore, Hong Kong,

Japan, and Australia (see Exhibit 1, below).

Exhibit 1. GETCO Form S-4 (12 Feb 2012): Trading Revenues (2007 – Sep 2012, $millions)

Source: KCG, TABB Group

TABB Group believes that it is further evident from this data that overall profitability was highly correlated to

volatility first (2009-2011) and competition second (2012). With aggressive globally coordinated central bank

interventionism strategies ramping up in the post-global-financial-crisis (GFC) period of late 2008 and early

2009, strategies that were dependent on (higher) volatility suffered as global markets became awash with

volatility-crushing “quantitative easing” (QE). Note the positive impact on revenues in 2011, which TABB

Group attributes to a correlation to the then-looming threat of a US default and the resulting spikes in volatility

in the third quarter of that year.

Furthermore, TABB believes that the nearly $300 million in revenue declines between the 9 months ending

September 2011 and September 2012 were due to something more: competition. But we need not necessarily

speculate on causes – and changes in tactics. Notable highlights from the GETCO/KCG filing deliver the

answers:

“Declines [in]…revenues were impacted by lower overall market volumes, reduced levels of

volatility, increased competition and a higher percentage of internalization in U.S. cash

equity markets;” and

“Headcount increases related to early investments in the Global Arbitrage, Mid-Frequency

and Options trading businesses.”

And, “Colocation and data line expenses … increased to $81.4 million in 2011 from $55.2

million in 2010. The increase in colocation expense was primarily due to the build out of new

colocations in Mahwah, New Jersey, Basildon, United Kingdom, and Tokyo, Japan, as well

as higher vendor rates for data and services.”

Bottom line:TABB Group believes that the market ecosystem was no longer supporting the same level of

theoretical capacity for all high-turnover participants, and the competition was becoming increasingly fierce.

Finally, although the reasons may have had more to do with operational retrenchment in the wake of the

GETCO-Knight merger in mid-2013 than the threat of competition, we note that the KCG annual report for

2013 shows non-US revenues declining dramatically, from 46.5% of total KCG revenues for 2011 (which is an

almost exact regional split of the GETCO-only numbers) to 18.9% of total revenues for 2013. Whether for

enhanced operational integrity or the threat of increasing competition or some combination of these and other

factors, we believe that there was a retrenchment to the core regional strategy in 2013.

But then, we turn to Virtu. The Virtu data, made public just this past March 2014, continues the narrative (see

Exhibit 2, below). This is an example of a firm with a more diversified portfolio of strategies – even if they are

all variants of high-turnover, latency-sensitive strategies.

Exhibit 2. Virtu S-1 (10 Mar 2014): Total Adjusted Net Trading Income (000’s, USD)

Source: Virtu, TABB Group

It is because of this diversification that revenues continued to increase for Virtu in the post-GFC period,

particularly in the past three years when many high-frequency players were suffering declines, changing

strategy mix, or exiting altogether. Interestingly, with declining rates of growth in its core Americas equities

strategies and flat-ish growth in its global commodities futures strategies, Virtu continued to more than make

up for lost ground due with success in areas such as FX, non-US equities, options and fixed income (see

Exhibit 3, below).

Exhibit 3. Virtu S-1 (10 Mar 2014): Total Adjusted Net Trading Income (000’s, USD)

Source: Virtu, TABB Group

With growing competition and strategy maturity in global equities and futures strategies, the target for further

high-turnover strategy growth will need to be in fixed income, including the ongoing Dodd-Frank led

transformation in the swaps market. (But will this be enough to overcome declines in other products, assets,

and regions?)

Also, bear in mind that this diversification is likely to be difficult in options strategies – which primarily means

single-stock options strategies. While Virtu may have discovered a unique and persistent speed advantage across products, regions, and asset classes (an incredible feat representing the pinnacle of what TABB Group

believes is its core value proposition), it will be met with formidable competition in options, with firms such as

Wolverine, Susquehanna, Ronin, IMC, Optiver and a few others.

As a result of all this, TABB Group believes that the timing of Virtu’s filing is indicative, if not prophetic, of

more persistent market shifts. Whether Virtu ever goes public (given the current delay), there is some rather

stark writing on the wall: Chances are that the expected gains in high-turnover fixed income strategies will not

make up for the stagnation or declines in just about everything else for the foreseeable future.

Virtu has taken diversification in high-turnover (market-making) quant strategies to new levels. According to

its recent S-1 filing, Virtu “makes markets … in more than 10,000 securities and other financial instruments on

more than 210 unique exchanges, markets and liquidity pools in 30 countries around the world” (see Exhibit 4,

below). Chances are that this is the most comprehensive list of venues – less the full list of specific dark pools

– where high-frequency trading is even possible on the face of the planet today.

Exhibit 4. Virtu S-1 (10 Mar 2014): Liquidity Venues

Source: Virtu, TABB Group (** estimates)

© 2009-2014 by The TABB Group, LLC and contributors | info@tabbgroup.com | +1-646-722-7800