CHAPTER 12

Strategy Diversification

The company that will be referred to only as CTNY was a relatively new proprietary trading firm in North America but it had expanded rapidly by offering extremely competitive deals to its branches through a franchised business model. In turn, its branches were able to offer some of the best terms and conditions available to proprietary traders who trade on the U.S. equity markets, including a large number of former senior traders from Swift Trade Securities. While it's a fairly commonly accepted principle among partners at many of New York's proprietary trading firms that poaching experienced and profitable traders from competing firms is overstepping a mutually understood boundary, CTNY had no problem aggressively poaching many of the top profitable traders straight out of established competitors' trading floors by offering deals that were nearly unheard of at the time.

Shortly before the branch of Swift Trade where I had been trained moved to a new building a few blocks from the core of Toronto's Bay Street financial district, it turned out that Jack had kicked the walls of the old trading floor one too many times. In spite of his impressive trading track record, the owner of the Swift Trade branch, Darrell, had been fed up with the noise pollution and the damages to the walls of the building. Sure, the profits that Jack brought in were more than enough to cover the cost of repairs, but Darrell had decided to put his foot down. After all, it was the latter period of the company's dark pool gaming era and there was no shortage of senior traders who performed on the same level with equally questionable strategies that required lower levels of maintenance and tolerance.

As it turned out, Jack had been one of the remote traders poached by CTNY in its first round of recruitment. Recruiting Jack to trade the company's capital from home might have been the ideal situation from the perspective of any firm, considering he would have to deal with any potential repairs himself depending on his living situation.

After a few days of consideration, CTNY's offer had admittedly become the most tempting one to accept simply because they had offered the most aggressive terms for experienced traders out of any of the companies willing to facilitate remote trading for experienced traders. Of course, there were additional hurdles. If I were to trade for the New York branch of CTNY, there would have been a number of bureaucratic hurdles to waste time with, including a Series 7 FINRA exam. I had completed the CSC exam long ago, which is generally considered the Canadian equivalent (though not actually required by regulators in the same manner) and contained very similar content at the time, so the FINRA Series 7 exam requirement would have been no problem from my end. CTNY, however, preferred to take an alternate route when recruiting traders who are not American citizens for a number of their own reasons. Since their offer allowed me to trade remotely for the company anyway, their arrangement with me as a non-American experienced trader was that I would officially trade for one of their Canadian branches, which legally existed as part of a completely separate corporate entity; regardless of my physical location, I would be logging in to an account under the Canadian entity to do so. Whether I continued to trade remotely for this Canadian branch from the apartment in Buffalo, or if I hypothetically decided to take up their offer to occasionally trade from one of their computer terminals located on their New York City based trading floor, I would nevertheless be logging in with a Canadian account and would officially be trading under the Canadian branch of the company in all cases.

This legal status, of course, remained intact even when they scheduled my visit to the New York City based branch of the firm for their two-week advanced training program. This CTNY trader training program, at the time, was optional and completely free of charge. I had learned later on that the company soon began to charge a fee for providing this training course to many beginner traders and some of its branches also required a risk deposit, like many of its peers in this segment of the industry, but the content reportedly stayed the same. After all, this was the epitome of capitalism in many ways. It seemed to be a decision based on the norms set by a number of its competitors within the industry. In the case of the former Swifties, however, the company seemed to offer a deal that was far more familiar to the business model of Swift Trade Securities with free a training program. If the fee was in fact charged to others, I was not entirely aware of it then. The company's aggressive recruitment of current and former Swifties at the time was to offer more competitive conditions than Swift itself did, so any differences from the offer given to beginners would not have been surprising. In either case, the training program was optional for experienced traders with verifiable track records who simply wanted to diversify trading strategies, to add to a trader's arsenal rather than trade solely using the high-volume scalping techniques we had been trained to begin with at Swift. Some of my peers had decided to skip the CTNY training program altogether and go straight to trading live at the new company. I, though, figured there would be no harm in learning a few new strategies at the new company. At the very worst, it would have been a waste of a couple of weeks of my time. At best, any additional strategies that I might learn at this company could at least provide new ideas to hedge myself against any possible future scenarios when the high-volume scalping techniques we learned at Swift might not be quite as effective as they were at the start of my proprietary trading career.

After much discussion and strategic negotiation with Anna, she agreed to go back to New York City with me for two weeks. At that point in time, I was well aware of Anna's ongoing conflicts with her family in Staten Island, including a recent incident that climaxed with her mother smashing the family's television set with a baseball bat (I wish I could say this was an exaggeration), so we had settled on a two-week stay at a nice little hotel in New Jersey near Edison (formerly Menlo Park). Of course, this training period would be unlikely to create any income, and we were essentially living on my savings from my first run at Swift Trade Securities by then. In any case, redundant as it may become, I can't stress enough how important it really is to save and spend wisely at every possible turn during all the peaks in a trader's career even when it appears as though the money rolling in might be endless.

At this point, of course, the hotel in New Jersey was the most cost-effective option for a two-week stay in the New York area as well as an opportunity to check out a few places over the weekend, including the Menlo Park mall that Bridget had mentioned to me a million times prior to that stay. Despite the cost per night being nearly nonexistent compared to that of the majority of hotels within New York City and its boroughs, this was a clean and well maintained hotel. Anna's standards were not incredibly high, but I had insisted on something nicer than one of the dingy motels near the Old Town neighborhood in Staten Island.

Every day during the two weeks of training at CTNY, I made use of eastern New Jersey in its stereotypical manner by making a daily commute into Manhattan via the NJ Rail train to Penn Station on 34th Street, right next to New York City's world famous Madison Square Garden arena. Of course, it wasn't my first time boarding a train that had been destined for Penn Station in Manhattan by any stretch. Since meeting Anna, I had taken regular trips on the VIA Rail-Amtrak line from Toronto to New York City, which actually entered the city using the same tracks, entering Manhattan through an underground tunnel and terminating on the lower level of Penn Station. It was, however, refreshing to arrive at the same location every day following such short travel time—that is, in comparison to the over 10-hour train ride I had become accustomed to on all those trips originating from Toronto's Union Station.

* * *

Day one of training at CTNY.

The training class took place at the far end of the trading floor. If any of the trainees hadn't been completely preoccupied by the material, there was also a decent view of the city if anyone bothered to look. The class was much larger than the one at my branch of Swift Trade Securities in Toronto. With well over 20 students, even a 25 percent survival rate—if that statistic even applied to firms outside of Swift Trade's style of talent discovery recruitment—should yield more than one full-time trader at CTNY, in theory. I had long heard that the way things were done at this company would be a different approach, a whole new experience for a former Swiftie. And in many ways, they were on the spot.

The head trainer of this class was the floor manager himself, Jared. He started his career as a high volume scalper but has since branched out to other styles of trading, including a style of statistical correlation trading unlike the methods found in mainstream material. For his overnight positions—something that was strictly forbidden at all branches of Swift Trade Securities due to the company's style of risk management and methods of capital allocation—he specialized in a more traditional form of the “stat arb” category with long-short pair trades.

To quickly capture the attention of the entire training class—which consisted of a mix of backgrounds, partly reflective of the city itself but with a mostly male configuration—would have likely been something of a challenge for many people in Jared's position. Of course, he handled it with as much of a relaxed delivery as he maintained when he watched the progression of an “only” 50,000-share-sized trade on a liquid stock.

“Who can name three types of trading strategies?” Jared posed his first question to the trainees like a kindergarten teacher fishing for the letters of the alphabet.

Hesitantly, a man who could only be described as a human boulder sitting at the right side of the training area raised his hand with surprisingly little confidence for his appearance. “Breakouts, counter trend, and scalping?”

“Okay.” Jared nodded. “Anyone else?”

For the next half hour, a wide variety of buzzwords typically thrown around in trading magazines, books, and Internet sites were offered by various members of the class of CTNY trainees. Eventually, the choices boiled down into relatively obscure but more specific forms of related strategies. As the class progressed, the atmosphere began to loosen up and the trainees became increasingly confident. Meanwhile, Jared had been jotting down what appeared to be notes on his clipboard. At one point, the thought crossed my mind that he might have actually been drawing a random doodle of an animal to give the impression that he had something more up his sleeve than he really had.

Suddenly, he looked up at the class and scanned with a stern expression. “You, you, and you.” He pointed at three trainees scattered around different parts of the training area. “And you, and you.” He pointed at two more of the trainees.

Without any clue as to whether the trainees singled out had been chosen for something positive or negative, the entire class fell silent and the tension in the atmosphere returned as abruptly as a trend change in the markets.

“Get out. You're done here.”

For about 10 seconds of silence that felt like a much longer period of time, Jared continued to scan the faces of all the trainees and wait patiently as the chosen students began to fumble through their bags, binders, and personal items in confusion and acceptance of their fate.

“Those of you already trying to leave: Listen closely.” He lowered his clipboard and scanned across the faces of the entire class of trainees. “I'm giving you a second chance.”

At the risk of paraphrasing the entire lecture, Jared went on to deliver a speech on the fact that he had, in the past minute, watched as the faces of the chosen trainees transitioned from a level of overconfidence that appeared complacent into a fear that the dullest of a hunters' senses would pick up.

“Confidence is fine,” he continued. “But never become complacent with success or yourself. I don't care if you've made two grand a day for the past six months. You're never home free. The moment you think you've got the market right in the palm of your hand, it'll break free and bite your whole damn arm off. Got that?”

With the tone firmly set for the rest of the training session, Jared proceeded to lean back comfortably on a leather chair as he delivered the rest of the training class. He had grabbed the full attention of the class by the horns and was ready to begin with the core material.

One of the few female trainees in the class was an academic with some retail investing experience named Beth, who had the uncanny ability to make the smartest and most assertive statement sound like a shaky question stemming from utter confusion. When Jared began on the topic of basic statistical arbitrage strategies, he naturally asked the trainees, “Can anyone tell me what a standard deviation is?”

Among a wave of raised hands from about half the class, many of the other trainees watched in awe as Beth answered with the actual mathematical equation to find a standard deviation rather than the general concept.

While she was doubtlessly intelligent, or at least adept at navigating the academic world, Beth struggled to catch on to the practical side of the trading business.

One of the few other female trainees in the class, however, was the polar opposite of Beth: an experienced trader named Erin, who I later learned had been a former Swiftie who started her career among the dark pool gaming crowd. Unlike some of her peers during that era, she had also adjusted to the changes in the market—and the regulations imposed on it—over the years and continued to do well in the industry. Having long been accustomed to the inner workings of the male-dominated industry, she had joined this training class for the same reason many other experienced traders did: the knowledge that it could never hurt to learn a few new strategies, or even ideas, to add to your arsenal as a professional trader of any level.

While the male-dominated class of trainees consisted mostly of men who ranged from experienced athletes to mathematically inclined programmers, the dynamic between the few women in the female minority of the class was the story less told in this industry. Not only were their experience and backgrounds widely varied, but their interaction strategies with the rest of the class also varied in style and technique when dodging the obligatory advances from the testosterone-filled environment. And above all, it was interesting simply because it had long been said among traders that, despite the minority of female traders, the few women who actually become traders tend to achieve a much higher success rate than male traders. Despite being part of that male majority, I often found myself rooting for the female minority to succeed simply to witness that often-told story unfold.

Another trainee, who will be referred to only as the Red Rooster, however, had an entirely different view of the female population of the training class. Every day, at every opportunity that presented itself, the Red Rooster would hit on one of the female trainees in as clichéd a manner as possible. What he did most likely wasn't and isn't rare anywhere in this industry, but the fact that he did it so often, and so blatantly that it almost appeared as though his sole purpose was to become a caricature of a French stereotype, kept the rest of the training class amused with his antics.

During one lunch hour, I decided to strike up a conversation with Erin about our common experiences at different branches of Swift Trade Securities, partly to give her a break from the Red Rooster's routine. We had both experienced the gradual changes in the market during the early period of Reg NMS implementation, the changes in NYSE market dynamics caused by the hybrid market environment, and the progressive improvement of dark pool algorithms. Naturally, the Red Rooster would then occupy himself during our conversations by turning his charm on Beth, who would typically be far more preoccupied with her struggles to grasp basic concepts in real-world trading despite an apparently inhuman ability to recite memorized details from textbooks.

* * *

Day two of training at CTNY.

For the first time, the beginners in the training class were given access to a demo account on the company's trading platform. For the former Swifties, however, it was less about learning anything new than it was about learning the seemingly random differences between the platform used by CTNY and the old Prosper Pro software created in-house by a sister company of Swift Trade Securities itself. This experience for a former Swiftie was a lot like the experience of an American visiting Toronto for the first time and realizing the abundance of similarities that he or she hadn't expected: the discovery that most Torontonians who were raised around the city actually speak a close variation of the generic American dialect familiar to moviegoers, rather than the small-town derived exaggerations of the “Canadian raising” accent or any French influences that might have been expected; yet, ketchup flavored potato chips are common and “Sub sauce” is actually something that can be ordered at a Subway restaurant. Going from almost any major American city to Toronto, as with the transition from the in-house Prosper Pro platform at Swift Trade to the Sterling Trader Pro software at CTNY, which is a popular platform among today's proprietary trading firms and was developed by an independent broker-neutral company, will expose a laundry list of similarities that are immediately obvious, but eventually a few odd but noticeable and entirely arbitrary differences would take some getting used to.

The fresh meat in the class would express their obligatory confusion at the basics of double auction markets in spite of a degree in some theoretical area of the finance industry along with, in many cases, years of retail investment account experience. When told to assign hotkeys on their keyboards for Buy, Bid, Offer, and Sell, many would question the purpose and difference between these functions. When told to assign each of these for each of the major destinations, from NYSE floor routes to Direct Edge EDGA, further confusion would doubtlessly ensue among the majority of the trainees.

“What ECN is best?” Beth asked, as though a single perfect solution were available in a textbook format.

“We'll get to that,” Jared answered. “And we'll get to why that question is like asking someone what the best restaurant in the world is.”

“Nobu,” one of the other trainees interjected with a chuckle.

“Sure, but what if you're headed there with no reservation with a party of 10 and it's a big night for them—maybe there's a line all the way to Franklin station trying to get in. Take notes, you'll understand every word of this by the end of the day. When you've got 10 lots of Citi to dump onto the market and there are a few million shares in line looking for that big rebate on BATS, you're better off getting filled on EDGA. You pay a small fee, but you can try to take the full penny instead of standing at the back of a huge-ass line. You'll miss the train every time trying to do that.” As the class progressed, that analogy became increasingly clear to the beginners in the training class as Jared explained the dynamics of destination selection and ECN fees and rebates.

With the inverted maker-taker pricing model implemented at the time by more than one of the ECN systems, it theoretically created an environment where scalpers could jump on the train by removing liquidity after it's already become obvious which direction the train is headed in. In reality, of course, every other major participant in the micro-term time frame traded by scalpers would also be aware of the advantages of removing liquidity from such a venue, so it quickly became obvious to the trainees that names like EDGA, which at the time paid a rebate for removing liquidity from it, would typically disappear (meaning all the displayed orders have been consumed by liquidity removing orders) long before the Level 2 quotes and the Time & Sales prints indicated any high probability of a move in a particular direction. There were, of course, exceptions to this rule. And for traders intending to trade other types of strategies with entirely different time horizons, these venues become popular as a means for entry and exit. For instance, a pair trader looking to open a short position in one stock simultaneously with a long position in another stock that shows a good level of co-integration and correlation, would often enter at least one of the legs of such a trade by aggressively removing liquidity on an ECN system that pays a rebate to liquidity removers. The techniques used to leg into such trades, however, are still rooted in the same concepts that are integral to the skills needed for high volume scalping, as the trader must be intimately familiar with the monthly fees and rebates on the major ECN venues. Also, when such strategies involve less liquid stocks that are thinly traded, a whole different set of skills is required that leans toward the skill set needed for the old dark pool gaming strategies.

On the other end of the spectrum, Jared also taught the trainees a basic technique for testing strategies using a simple spreadsheet in Microsoft Excel. After all, he had noted, aside from a trading platform, Excel remains one of the most commonly used programs on traders' screens all around Wall Street. Whether this was based on any real statistic, I have no idea. His techniques, however, were a refreshing way to look at the markets from the perspective of a former Swiftie. To any of the quants on Wall Street, I have no doubt that the type of basic statistical research we were trained to do on Excel was nothing but child's play, but it resulted in at least three different profitable trading methods on the trading floor over the next six months. So call it what you will, these basic techniques may not have been the advanced systems used by the top HFT funds, but they were enough to help a group of real traders make money.

To foster this constructive environment, Jared also encouraged the trainees to design original trading strategies and then test them: initially, on a small amount of data to see if it's at all feasible, and then on a relatively larger sample depending on the nature of the idea. In some cases, depending on the risk profile of the original concept, Jared permitted trainees to test the strategy live using relatively small trade sizes to start. If it worked as expected, the trader would then gradually scale up, but the scalability of a strategy would often vary depending on the nature of the technique itself as well as the amount of volume in the markets that the strategy was designed to be traded in. Another point that Jared hammered into this aspect of the training program was never to assume that a profitable trading strategy must be universal. It's not about finding some magic combination that works on every market—that's equivalent to a record label attempting to market the same music to every demographic on the planet. It might work for a large percentage, but it's unlikely to be universal, and it doesn't need to be. Sometimes, there's no harm in focusing on a specific market and taking advantage of the nuances and structure of that specific market in order to extract a trader's paycheck.

As the class progressed through the training program, Jared would occasionally lighten the mood with a story from his past experience in the industry. At times, it became obvious that he enjoyed embellishing some admittedly entertaining details in his stories, and he often exaggerated the sheer number of contacts in various parts of the industry. His knowledge of the markets, on the other hand, was undeniable and many of the concepts he introduced in the course of the training at CTNY had become the basis of many of the strategies I have used or modified in the years since. Over time, I have grown to respect his ability to manage the audience reactions just as he managed the trading floor. He was, after all, a seasoned player on the management side of the game—a cutthroat game bred by the many-shades-of-gray culture that is undeniably commonplace throughout the securities industry.