Читать книгу Trading Psychology 2.0 - Steenbarger Brett N. - Страница 12

I mentioned in the foreword that the immediate catalyst for this book was a review of ten of the top traders and portfolio managers I had worked with in the last decade. In a sense, this was my own solution-focused therapy. Performance coaches working with participants in financial markets encounter so much talk of failure, frustration, and shortcoming that it's necessary to occasionally step back and reconnect with all that is possible.

Maxwell was one of the top ten traders I had identified. For years he had been very successful trading intraday patterns in the S&P 500 e-mini (ES) futures market. His frequent refrain was that other traders were “idiots.” They chased markets, put their stops at obvious levels, and otherwise replicated behaviors that provided Maxwell with a trading edge. I wouldn't describe Maxwell as particularly intellectual, but he was very intelligent – and unusually shrewd. He was an avid gambler and had an uncanny ability to figure out the other players at the poker table. He seemed to know when others were bluffing, when they were on tilt, and when they held the nuts. While he knew the probabilities attached to various hands, it was his keen perception of his opponents that enabled him to bluff, fold, or go all in.

Maxwell contended that the players in the ES futures were like rookies at the poker table. That's what made them idiots. One of Maxwell's key trading patterns was fading “pukes.” When he saw the market breaking key support and traders baling out of their positions, he knew that fear was driving the trade – and that there would soon be an opportunity to take the other side. “The market doesn't reward idiots,” Maxwell once explained. By fading the fearful herd, he knew he could make a good living.

When I had the opportunity to watch Maxwell trade live, I realized how he was so consistent in his performance. He sat and sat and sat for good amounts of time, waiting for the market to “set up.” During this period, he would observe the flow of volume at various price levels. Watching a depth-of-market screen, he could tell when buyers were coming in or exiting at a particular level. If buyers couldn't take out a prior high or sellers a previous low, he would quickly take the other side. To no small degree, his trading was predicated on figuring out when traders were wrong before they figured it out.

Maxwell loved busy markets: The greater the order flow, the greater the opportunity to find those occasions when bulls and bears were caught in bad positions. Most of his sitting occurred during slow market periods. “There's no one in there,” he would shrug. An important part of his edge was not trading when he perceived no advantage in the marketplace.

The bull market ground on, VIX moved steadily lower, and the average daily ranges shrunk. Maxwell found himself with fewer opportunities. To make matters worse, individual traders were becoming less dominant in the market, as daytrading lost its appeal to the public in the aftermath of 2000 and proprietary trading began its descent in the wake of automated market making. With fewer idiots trading, Maxwell's profitability began a slow, steady decline. Gradually he began to wonder if he was the idiot. With larger trading firms increasingly relying on execution algorithms to get best price, prices moved differently than in the past. More than once, he lamented that the old ways of gauging buy and sell levels no longer worked.

Maxwell's risk management was good, so he wasn't losing much money. He also wasn't making much, however.

Not many peaks.

Not many valleys.

The passion ebbing.

Just like Chris and Gina – committed to what worked in the past, unable to find a bridge to the future.

You don't just wake up one morning and discover your edge is gone. Rather, as with those Kuhnian paradigms, negative evidence accumulates gradually until it is no longer possible to ignore. The restaurant owner who sold to Emil did not suddenly come to work and find no customers. The erosion occurred over time, during which he did everything possible to boost traffic: Change menu items more frequently, lower prices, run specials, and so on. All of these were changes within the same paradigm, however: They were rearrangements of deck seating on a sinking ship. Incremental changes don't work when qualitative change is necessary. For the restaurant owner, qualitative change was a bridge too far and he sold to Emil.

How many years did Gina and Chris plod forward in a marriage losing its compass before the contradictions accumulated and it was no longer possible to ignore the absence of closeness in the close home they were committed to building? An object in motion, not acted on by any outside force, remains in motion – and people are no different. We are wired to conserve energy: Constant change would be disruptive, exhausting, and inefficient.

It makes sense from a purely evolutionary perspective that what has enabled us to survive would become our default mode, our status quo. Maxwell rationalized the decline in his profitability in many ways: as the result of stress, burnout, high-speed algorithms, and just pure bad luck. Each rationalization helped sustain the status quo. “Don't fix what isn't broken” is common advice. As long as we convince ourselves that we're not broken, we don't have to seek fixes.

Key Takeaway

Routine is necessary for efficiency; breaking routine is necessary for adaptation.

There is another reason, however, why traders don't quickly embrace change in the face of changing markets and opportunities. Even when we possess a distinct and consistent edge in markets, the paths of our profitability can be highly variable. Over the long haul – 100 or more trades – an edge tends to be apparent, particularly if one is not engaging in high hit rate/high blowup strategies, such as the naked selling of options. Over the course of any series of, say, 10 or 20 trades, there are random series of winning and losing bets that can play havoc with our psyches.

Last year I wrote a blog post based on the P/L Forecaster that Henry Carstens posted to his Vertical Solutions site. In researching that post, I explored three profitability curves: one with no edge whatsoever (50 percent win rate; average win size equal to average loss size); one with a negative edge (50 percent win rate; average win size 90 percent of average loss size); and one with a positive edge (50 percent win rate; average win size 110 percent of average loss size). Over the course of 100 trades, we could see the edge – or lack of edge – play out. Along the way, however, were surprising ups and downs that were purely random. By running Henry's Forecaster many times, we can see how many ways it's possible to have a constant edge and end up at a relatively constant end point, but with extremely different paths along the way.

Traders very often overinterpret these random ups and downs in the P/L curve. When they have strings of winning trades, they convince themselves that they are seeing markets well and increase their risk taking. When they encounter a series of losing trades, they become concerned about slumps and reduce their risk taking. Those adjustments ultimately cost the trader money. Imagine a baseball player who gauged his performance every 20 or so at-bats. When he gets a large number of hits, he considers himself to have a hot hand and swings even harder at pitches. When he strikes out a number of times, he talks himself into changing his swing to get out of his slump. Both adjustments take the batter out of his game. Ignoring short-term outcomes and focusing on the consistency of the swing is a far more promising approach to batting performance.

So it is for traders. Someone like Maxwell is wise to not overinterpret daily, weekly, or monthly P/L. Rather, he should assess the elements of his trading process, from his generation of trade ideas to his trade execution, and seek to make incremental improvements. When the paradigm is working, the most constructive course of action is to steadily refine the paradigm.

The problem is that, once in a while, 20 trades turn to 40 turn to 60, 80, and 100, and evidence accumulates that the trading paradigm is no longer viable. Even a small edge is apparent after enough instances: That's why it makes sense to keep betting in Vegas when the odds are with you. If you go all in on any single bet, you court risk of ruin: That randomness of the path can take you out of the game. But if you bet moderately with a constant edge, more bets allow the edge to overcome randomness. When randomness overwhelms an edge not just over a dozen or so trades, but over a great number of them, then we have evidence that something has changed. Still, a trader like Maxwell can convince himself that this, too, shall pass.

Tracking your edge is relatively easy when you place several trades per day. What about less active investors and portfolio managers who might limit themselves to several trades per week or month? If trade frequency is low, an entire year of diminished performance could go by and represent nothing more than random bad luck in performance. Imagine, then, the trading firm that allocates more capital to the portfolio manager who has a good year and not to the one who underperforms. Those adjustments, no less than the hot hand/slump-inspired adjustments of individual traders, can drain performance over time.

It's a genuine challenge to track edge and randomness over small sample sizes of trades. If a strategy can be backtested objectively without overfitting historical data, it is possible to generate a reasonable set of performance expectations in the absence of recent, real-time trading. For a purely discretionary strategy, however, the sobering truth is that, over the course of a limited number of trades, we cannot really know whether performance is due to luck or skill. Michael Mauboussin writes convincingly about this challenge in his book, The Success Equation (2012), pointing out that our failure to recognize luck makes it difficult to objectively evaluate performance. An overemphasis on recent performance leads traders to place too much significance on recent runs of winning and losing trades, not recognizing the important role that luck plays in those runs. Whenever Maxwell had gotten to the point of trying to make meaningful changes in his approach to markets, he would hit a winning series of trades and convince himself that “the market is coming back.” Only after hope was raised and dashed many times did he get to the point of seeking help. By that time, however, like our couple, Maxwell had gotten to the point of questioning whether he could, indeed, go forward.

Maxwell was not broken, just as Gina and Chris weren't broken. Like them, he kept doing what worked and stayed confident in his course even after it ceased to take him where he wanted to go. But also like the couple, Maxwell was doing many things well. In avoiding consensus and the herd behavior of traders, he was able to sustain a high level of intellectual and behavioral independence. His ability to detect ebbs and flows in volume helped keep him out of trades going the wrong way, even if it was now far more difficult to anticipate the market's inflection points. In the old days, Maxwell used to be able to point to a chart level and anticipate how the market would behave once it touched that level. Those days, he realized, were long gone. There just weren't enough idiots left in the market to overreact to those chart levels!

One of my favorite solution-focused exercises in such situations is to institute a review of winning trades. Much of the role of a trading coach consists of comforting the afflicted and afflicting the comfortable. When someone is afflicted like Chris and Gina or Maxwell, some comfort in the search for exceptions to problem patterns can be empowering. When traders are in denial, doing ever more of what hasn't worked, some affliction of comfort becomes useful. A review of best trades reminds discouraged traders that they are not wholly dysfunctional. Talents, skills, and experience remain – they just need to be redeployed.

During Maxwell's trade review, we found an unusual number of winning trades held for a short time. He referred to these as scalp trades. “I see what's happening in the market and I jump on it,” Maxwell explained. It was when he tried to identify longer-term significant price levels and hold positions for hours or days that he was no longer able to make money. From the review, Maxwell and I could clearly see he had retained his reflexes – and his capacity for quickly sizing up markets. It was his thinking about markets and not his instinctive pattern recognition that was off. In scalping mode, he was all instinct – and he made money surprisingly consistently.

Shortly after the review, Maxwell joked with me about an email he had gotten from a guru seeking to charge big bucks for sharing his wave-based trading secrets. He reminded me of my earlier blog post making fun of the “idiot wave” and shook his head at the foolishness of traders who believed such obvious sales hypes. I quickly saw my opening.

“So, Max, if you don't use wave theory, how are you going to figure out where the market will be trading at 3:00 p.m. tomorrow?”

Max laughed and joked that he already had too many crushed crystal balls and was not about to dine on more broken glass.

“But aren't you doing the same thing with your levels that the Elliott guys are doing with their waves?” I challenged. “They're predicting the future and so are you.”

Maxwell looked puzzled; he wasn't sure where I was going with this. “Besides,” I continued, “you don't need to predict markets to be successful. What the review of your trades told us is that you're plenty good at identifying what the market is doing at the time it's doing it. Why predict levels for price movement when you can identify what people are doing in real time?”

You could see the wheels in Maxwell's head turn. Predicting an uncertain future was what idiots do. His job was to identify buying and selling pressure, not anticipate it.

Pattern recognition was his bridge to the future.

Kahneman, in an excellent research summary, identifies two basic modes of thinking. One is fast; the other is slow. In Thinking, Fast and Slow (2011), he explains that fast thinking enables us to respond to challenges in the immediate present. If a car suddenly drifts into our lane, we quickly swerve to avoid an accident. That rapid processing enables us to respond to crisis. If we had to think through every aspect of what was happening on the road, we'd hardly be able to adjust to the flow of traffic – or avoid oncoming vehicles!

The problem with fast thinking is that it is surface thinking. We perceive something, rapidly assess its relevance to us, and quickly respond. In the case of the oncoming car, that's a good thing. In the case where we see an African American man walking toward us on the sidewalk and we quickly cross the street, that same rapid processing allows bias to drive our actions. Indeed, many of the well-known cognitive biases, such as recency bias and the availability heuristic, are the result of fast processing taking control of our decisions and actions.

Slow thinking, on the other hand, is deep thinking. When we think in slow mode, we observe, catalog our observations, analyze what we've observed, and draw conclusions. Such a process is less likely to be swayed by superficial bias, but it consumes a great deal of our cognitive resources. We can drive the car and carry on a conversation while in fast mode. It's unlikely that we could solve a complex mental math problem while remaining fully attentive to road conditions. That's one reason texting and driving so often leads to disaster.

For efficiency's sake, we tend to rely on the efficient fast system except in situations that call for deep reflection. As a result, many of our decisions and actions end up reflecting first impressions, not carefully reasoned conclusions. How many times do we analyze a market, plan a trade, and then do something different in the heat of market action? The problem is not a lack of discipline per se. Rather, our fast thinking brain has hijacked our slow, reasoning mind. Quite literally, Kahneman points out, a different part of the brain controls our fast and slow processing, sometimes taking control at the least opportune occasions.

If we think of two brains – two relatively independent information processing systems – then it isn't a far reach to identify at least two intelligences. We can be smart fast thinkers, smart deep thinkers, sometimes neither, and sometimes both. Think of very talented salespeople or highly experienced air traffic controllers. As a rule, they are not the most intellectual people – not necessarily deep thinkers – but they process information very well, very quickly, and very flexibly. The salesperson reads customers very well and subtly adjusts his or her tone of voice and message to the immediate situation. The air traffic controller doesn't think about each plane, where it's going, who operates it, and so on, but instead quickly processes the many planes coming in and out of a busy airport. This ability to quickly process rapidly changing information enables the controller to make split-second decisions that keep the system functioning efficiently and relatively accident-free.

Key Takeaway

How we think anchors how we trade.

Conversely, we've all known very bright, intellectual people who seem to lack practical sense. They can solve math problems and analyze situations, but then are clueless when it comes to reading the social cues of a dating situation. The engineer could tell you all about the construction and operation of a car engine, but it's the racecar driver who has the smarts to power the vehicle to victory at Indy.

We often refer to trading as if it's a single activity. Trading, however, is like medicine: a broad set of activities and specialties. A psychiatrist is a physician; so is a surgeon, and so is a radiologist. The skills required for each are very different. So it is in financial markets. Market making is very different from global macro portfolio management – and both are quite different from the trading of options volatility.

One of the things that make trading interesting is that it blends fast and slow thinking in myriad ways. At one extreme, we have the daytrader, who performs relatively little deep analysis, but who can excel at real-time pattern recognition. At the other extreme, we have the long-term equity investor who studies companies in depth and constructs complex portfolios that hedge various sources of factor risk in order to profit from the price movements of strong versus weak companies. In between these two are hedge fund managers that combine the deep dives of macroeconomic analysis with the quick processing of market trends and reversals.

My experience is that successful market participants rarely excel in both slow and fast thinking, but they almost always excel in one or the other. If you look at what makes them successful, what you find is that they discover ways to engage markets that leverage either their fast processing or deep thinking skills. In a purely cognitive sense, they play to their strengths. This was certainly true of Maxwell: His scalp trades were the result of considerable fast thinking skill.

Slumps follow when traders respond to market setbacks by switching cognitive modes. The fast thinker begins to overanalyze markets and loses further touch with markets. The deep thinker becomes fearful of loss and acts on short-term price movement. Anxiety and performance pressure take traders out of their cognitive zones – and away from their strengths. So it was for Maxwell. His setbacks began in low-volatility markets that were increasingly dominated by market-making algorithms. He convinced himself that he needed to adapt to these changes by widening his holding periods and trading more strategically than tactically. Instead of following the market tick by tick and gauging order flow, he looked to longer term support and resistance levels on charts and ideas coming from earnings reports, data releases, and recent news. All of these took Maxwell out of his zone: He was trying to adapt to change, but doing so by becoming less of who he was at his best. Fortunately, his scalp trades kept his fast thinking skills alive – and his trading account treading water – during this wrenching period of adjustment. Over time, however, his results were becoming more average because he was increasingly relying on his relatively average deeper, analytical skills.

What turned Maxwell around psychologically, however, was that he redefined his emotional commitment to trading. Recall Chris and Gina. What was their prime motive? They wanted to be great parents and provide their children with the kind of upbringing they never had. They could not change their marriage until they reached the recognition that they couldn't be good parents to their maturing children unless they modeled a good marriage. Now their motives were aligned. They practically leaped into enhancing their marriage because they were doing it now for a good cause.

Maxwell's psychological raison d'être was that he was the smart guy who profited from the idiocy of others. Making money for him was an emotional affirmation that he was clever, unique, and distinctive. When he stopped making money – and especially when he saw market makers profiting at his expense – he began feeling like an idiot. So what did he do? He tried to make himself into a deep thinker, someone who would be smarter than others in a different way. Ironically, he was seeking affirmation by running from his strengths.

What the solution-focused exercise demonstrated was that Maxwell was successful in a number of his trades, but that he was successful by being more tactical, not by becoming a grand strategist. As with Gina and Chris, Maxwell embraced his strengths in spades once he realized that they were the path to his emotional success. A kid from the proverbial wrong side of the tracks, Maxwell had a bit of a chip on his shoulder. He was out to prove himself to be worthy. That emotional priority wasn't going to change. We just needed to align that priority with his best trading. That became much easier when Maxwell was able to see that, in trying to predict markets, he was being one of the idiots he routinely ridiculed. He was no more willing to be an idiot than Gina and Chris were willing to be bad parents.

I won't pretend that the work with Maxwell was easy. The turnaround did not occur overnight. A great deal of work remained to distinguish why some of his tactical trading based on pattern recognition worked some of the times and not at others. It turned out that further investigations of his trading were needed. What I found in breaking down his trades was that he was losing more on the short side than the long side – and this was in markets that had been in longer-term uptrends. Subtly, Maxwell was trying to prove himself by making himself into a contrarian. When he saw that this also was acting like an idiot by swimming against the tide, he became much more open to using simple gauges to stay on the proper side of the market. For example, he defined strong, neutral, and weak markets based on early readings of how the market traded relative to its volume-weighted average price (VWAP), preventing him from fading the very strong and weak markets. By expanding the useful patterns he looked at, he was able to leverage his pattern recognition strengths.

He came to me with problems, but it was his good trading that generated the solutions. Once Maxwell found a way to bridge his fast trading skills with the emotional driver of his trading, meaningful change could occur.

That is the takeaway: We cannot change if we fail to tap into those emotional drivers.