Donald R. Wilson Jr’s Book: Hiding in Plain Sight

“To create something exceptional, your mindset must be relentlessly focused on the smallest detail.” – Giorgio Armani

Taken out of context, one might legitimately jump to the conclusion that today’s installment on the Feed is about 11-time kickboxing champion, Don “The Dragon” Wilson. Or, better yet, that the initials “DRW” represent the greatest hockey team of all time, the Detroit Red Wings…

However, unfortunately for Mr. Dragon and my Wings – and given the context of the mythological trading landscape we have been exploring lately – this post can only be referring to Chicago’s very own Don Wilson and his eponymous proprietary trading firm, DRW Holdings, LLC (DRW).

Here’s some personal perspective to get us started:

In the history of legendary Chicago trading firms, one could draw a line with options trading prop shop O’Connor & Associates (and the O’Connor brothers, Billy and Eddie) and the CBOE on one side, and rival futures trading prop shop CRT (Chicago Research & Trading – and founder Joe Ritchie), and the CME on the other. Both of these firms were derivatives trading pioneers that came to prominence in the 80’s and early 90’s before being acquired by Swiss Bank Corp. and NationsBank, respectively. I had the good fortune to work with both of these teams…

In the current era, one could argue that Don Wilson and his DRW group are to the CRT / CME / futures lineage what Ken Griffin and his Citadel group are to the O’Connor / CBOE / options lineage – at least as the major Chicago players go. And, as a result, this is why these firms have been among the first for us to model in the context of the 13F datasets.

Now, of course, we could also argue that this kind of attribution is a gross oversimplification that not only leaves out the considerable strategy diversification of these two powerhouses, but also leaves out mention of some of the other legendary firms (and their founders) that have played legendary roles in the evolution of the high-performance trading world.

Not to worry. We will eventually get to the modeling and profiling of all of these firms – and many others beyond this small circle. For now, I want to continue to build the foundation we have been focused on of late by returning to the initial post on Paul Gurinas’ and Bill Disomma’s futures prop shop Jump Trading. If you missed that, see Jump (Experiments In) Trading, LLC.

Here’s the setup:

If you have been paying close enough attention to our “Hiding in Plain Sight” series, then you would know by now that a key working hypothesis of Alphacution’s research is that overperformance – or, alpha – is limited, and this boundary has critical impacts on the behavior of players in the ecosystem.  Moreover, we have been building the case that highly-automated trading firms are well-positioned – if not, optimally positioned – to capture a disproportionate share of scarce and finite sources of alpha.

From there, the next component of our near-term research strategy is to focus on those trading firms “closest” to the sources of liquidity because these players are 1) uniquely positioned to showcase the capacity of the alphas on the faster end of the temporal spectrum, and 2) are simulataneously in a position to foreshadow the impacts of technology and workflow automation on those other players who are focused on the slower end of the temporal alpha spectrum.

The first grouping is composed mainly of market makers and proprietary trading firms. The latter group is composed mainly of hedge funds and traditional asset managers. Those firms that can embody the benefits of both groups through a metastrategy of nested alphas are the one’s likely to enjoy the greatest success. (Don’t hurt yourself on this one. We’ll come back to this concept in significant depth later because it is a hallmark of the most advanced players. For extra points, search Andy Sterge or CooperNeff on the Feed.)

For trading strategies that are based on listed products like cash equities, options and other equity-linked products like ETFs, those firms whose books have become big enough (>$100 million) to require a 13F filing are of particular interest because of the underlying strategy transparency these reports provide. What has become an order of magnitude more interesting is those trading firms that are closest to the sources of liquidity and need to fulfill certain broker-dealer (BD) requirements. In these cases, BDs need to file an annual X-17A-5 report, which includes balance sheet information (and occasionally other juicy tidbits, as will be demonstrated shortly).

So, when we find trading firms who have a combination of 13F and X-17A-5 reporting requirements, then we have discovered a research treasure trove.  In short, all consequential market makers and most consequential prop shops are required to file both of the aforementioned reports.

Alphacution’s foray into this combined dataset modeling and analysis started with the initial post on Jump and the recent one on Two Sigma and its late 2017 acquisition of market maker Timber Hill from Interactive Brokers. Here, we extend that thread with some examples of our recent modeling of DRW Securities, LLC (DRWS).

In the chart below, Alphacution presents the major product class breakdown based on the percentage of gross exposure values reported by DRWS from 2010 through 2017. (Note: gross exposure is the sum of long and short sides of the balance sheet which are approximated in most cases by the sum of securities owned and securities sold but not yet purchased.)

The main point to be made here for now is that balance sheet exposures are not necessarily correlated to magnitude of revenue. By reputation and anecdote, we would expect a significant share of DRW’s revenue to come from fixed income, currency and commodity (FICC) futures, options and swaps trading along with some cash fixed income arbitrage strategies. And yet, the balance sheet of DRWS betrays this expectation with significant exposures to equity and equity-linked products.

Here’s what’s happening: Trading in all asset classes and products are speeding by at the native turnover frequency of the underlying strategy relative to the liquidity of the relevant markets (which influences strategy capacity). Traders much prefer to capture their alpha and be flat (or fully hedged) at the end of the day. This is just as true for a local pit trader in 1985 as it is for a global electronic trading powerhouse in early 2019. But, given the need to grow and scale, some strategies begin to accumulate deltas – and, deltas have a funny habit of showing up on balance sheets.

Now, once in a blue moon, a legendary prop shop will make a mistake and disclose something that they would otherwise prefer to keep private. Those of us who believe that some of the greatest opportunities are hidden deep in the details tend to be the ones who notice when these mistakes occur.

The chart below represents what Alphacution believes is one such mistake – and reveals the point about where firms like Jump Trading – among those most similar in our limited sample to the core trading strategy of DRW – derive their revenue:

The point here is that while a significant portion of balance sheet exposure may be attributed to equity and equity-linked strategies at DRW, the lion’s share of the revenue is still likely coming from FICC-related trading. Using Jump as a reference point, that would be a lot of balance sheet to commit to generate something in the neighborhood of single-digit % of annual gains (as Jump did in 2011 at 1.5%). Of course, on the other hand, a lot has changed since 2011, which we can demonstrate later.

Nevertheless, the fact that the equity trading exists at all at a FICC powerhouse is indicative of the reality that the best trading firms will inevitably outgrow the capacity of their core strategy, and therefore, need to hunt for new alphas elsewhere.

The moral of today’s story?

Building an exceptional trading (or asset management) business is ultimately about much more than discovering a source of alpha or two. Great trading businesses are built on a foundation of processing no matter what the source of alpha may be. Another key takeaway here from the data is that both DRW and Jump are eagerly looking for new sources of performance so as not to rest on the laurels of the original sources of success…

Anyway, Alphacution has a ton more comparative analysis on DRW, Jump and others loaded in the chamber for future lessons, so let’s bookmark, digest and conclude with this:

We have made a point to showcase the growing usage of and dependence on ETFs in recent research, particularly with regards to Bridgewater Associates. So, with these examples in mind, please ponder the reason(s) for the episodes of resemblance in the ETF penetrations for the respective DRW and Jump equity books, below:

We will return with our own thoughts soon…

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By | 2019-09-25T15:48:16-04:00 January 30th, 2019|Alphacution Feed|

About the Author:

Paul Rowady is the Director of Research for Alphacution Research Conservatory, a research and strategic advisory platform uniquely focused on modeling and benchmarking the impacts of technology on global financial markets and the businesses of trading, asset management and banking. He is a 30-year veteran of the proprietary, quantitative and derivatives trading arenas. Contact:; Follow: @alphacution.