A chess player analyzing the board for the next move; fighter pilots maneuvering their planes to get a lock on enemy aircraft; a baseball player tracking the release of the ball from the pitcher?s arm; ballet dancers executing their leaps; an oncologist diagnosing a rare form of cancer; a bodybuilder sculpting a small muscle group to achieve symmetry: all of these are examples of performance activities. They are also examples of fields that have been widely researched in the past two decades, uncovering important clues as to the factors that create successful performance.
This research raises fascinating questions: What makes expert performers different from less successful ones? Is expert performance a function of inherited personality traits and skills, or can it be cultivated in the proper environments? Which techniques has research found to dramatically improve performance? Will the performance-enhancing techniques that benefit chess grandmasters and Olympic athletes also assist traders? The book I am currently writing will tackle all these questions and more. This article has a more modest aim: It will draw upon research studies with chess experts to identify the one most important thing traders can do to accelerate their development.
Trading as a Performance Activity
Not all trading is a performance activity, of course. A computer can be programmed to enter, manage, and exit positions, but the computer does not perform in the same way as the athlete, dancer, or fighter pilot. Performance, in the psychological sense, begins with the human element in competition. Humans choose when to take action and when to refrain; they can select various courses of action on different occasions and can invent new strategies when needed. The trading computer does not have good days and bad days?only profitable ones and unprofitable ones. Human traders can perform poorly even if they make money, and they can have good days even when they?re in the red. That is because performance is a function of the chosen actions of performers, the correctness of those choices, and the skill with which the actions are carried out. Once an element of discretion enters into trading, it becomes a performance activity: one in which outcomes are dependent upon the choices of the performer.
There are several common features of performance activities:
- They can be executed well or poorly. Activities that are performed well on a consistent basis require a high degree of skill. A lucky outcome, such as winning a lottery, is not a skilled performance.
- There are individuals who can be identified as expert performers. With very rare exception, expert performers are ones who have developed their talents over time. Most expert performers undergo specialized training to cultivate their talents.
- They require a specialized knowledge base. The knowledge may be the ?how-to? knowledge of a gymnast or the research knowledge of a scientific researcher. To perform well in a field, a person must master the information and skills specific to that field.
Trading, as a performance activity, has much in common with chess. It is competitive, requiring a high degree of concentration and strategy. It also features a limited number of actions that, in combination, create a large array of possible strategies and actions. This makes both activities easy to learn, but difficult to master. Chess can be played in lightning fashion, with very little time between moves, or it can allow players many minutes to plan moves?or even days (postal chess). Trading can also be conducted on a very short-term basis or can be planned and executed over hours or days. These similarities make chess an excellent starting point for examining the performance dynamics of trading, especially since chess is one of the performance fields most studied by researchers.
The Performance Ingredients of Chess
A well-replicated finding in chess research is that the memory processes of experts are different from those of non-experts. One intriguing set of studies took chessboard arrangements from a past tournament games and briefly showed them to expert players and novices. Afterward, the expert chess players were able to recall the positions of many more pieces than the novices. When the two groups were shown chessboards with randomly arranged pieces, however, their recall of the positions of the pieces was quite limited. The researchers? conclusion was that experts do not have better memories than non-experts; rather, they have better memories for meaningful relationships among chess pieces. Instead of remembering where each individual piece was on the board, the experts viewed the board as clusters of pieces and remembered these. When the board was randomly arranged, there were no meaningful clusters of pieces and the experts had no effective means for encoding their information.
How do expert chess players gain this ability to perceive meaningful patterns among pieces? Because chess players are given ratings based upon their tournament play, it is relatively easy to compare experts (masters and grandmasters) with less accomplished players. When a variety of factors are incorporated into multiple regression equations to predict chess ratings, two stand out as highly significant:
- The number of books owned ? Research conducted by Neil Charness and colleagues finds that the correlation between books owned by chess players and their current performance ratings was .53.
- The cumulative number of hours spent in practice ? Those same researchers found that the correlation between the amount of time spent in practice and current performance ratings was .60.
To appreciate these findings, it is necessary to understand what chess books are and how they are used. These texts typically break the game down into components (opening, endgame, defenses, etc.) and present historical games from tournaments, along with annotation from an expert author. Readers do not merely skim over these games; they learn specific opening or defensive sequences and then see how these were utilized in actual games. They recreate those games on their own boards and carefully play through the positions, so that they can see what the expert players saw. They also play through alternate sequences to observe where these might lead.
Interestingly, chess experts do not have significantly more chess-playing experience than non-experts. Rather, a higher percentage of the experience of experts is spent in the systematic practice of various facets of the game. Non-experts tend to spend a higher proportion of their time in games against similarly-skilled opponents. This experience neither exposes the learner to the moves of experts, nor does it provide time for a careful review of moves, exploration of alternate lines, etc. In the Charness work, the correlation between solitary practice and chess ratings is almost twice as high as the correlation between practice with others and ratings. This is because solitary practice with chess books allows learners to obtain chess knowledge in context. Instead of focusing on the moves of an opponent, learners encounter?again and again?those meaningful configurations of pieces that appear in the games of experts.
Enhancing Trading Performance
Students of trading are at a huge disadvantage relative to students of chess. Chess books document the performance of centuries of experts in actual tournament situations. Because of this, chess students can create and play through almost any challenging situation imaginable, drawing upon the accumulated wisdom of experts. Trading possesses no such database. Trading books, unlike chess texts, are not annotated compilations of the trading decisions of objectively rated experts. One cannot use trading books to recreate trading sessions or to systematically explore trading decisions and their alternatives. Chess books lend themselves to independent deliberative practice; trading books present ideas outside the context of actual trading.
As a result, traders tend to spend little time in the systematic practice that is the single greatest predictor of chess expertise?not to mention expertise in music, athletics, and dance. This violates a principle from the performance research that is so striking that it might even be called a law:
In every performance field, the development and maintenance of expertise requires a high ratio of time spent in practice relative to time spent in actual performance.
Athletes spend far more time working out, practicing, and scrimmaging than actually playing in competitive events. The same is true for chess masters, professional dancers, fighter pilots, and racecar drivers. Our analysis of chess expertise helps to explain this law. Only significant time spent in absorbing winning and losing chess enables players to internalize the patterns of play that distinguish experts from non-experts. The trader who spends more time trading than practicing trading is like the golfer who spends more time playing rounds with buddies than on the driving range, putting green, and in lessons. We all know golfers like that, and they are not the ones who make their living on the PGA tour.
This then leads us to the single most important step you can take to become an expert trader:
The expert trader needs to be able to review and re-experience markets and systematically rehearse facets of trading performance: entering, managing, and exiting positions.
Note that what I am suggesting is NOT paper trading. Paper trading is usually a following of the market in real time, accompanied by simulated trading decisions. Such paper trading does not allow traders to replay market action, review their decisions, test out alternatives, etc. It is this re-experiencing that cements learning, and it requires a database of market days similar to the database of tournament games utilized by chess books.
Think of each trading session as a chess game, and each game as a contest between two expert players named ?Bull? and ?Bear?. Every short-term swing in the market is a move by Bull or Bear that ultimately leads either to a victory for one of them or a draw. In tracking the moves of Bull and Bear, we can pause the match at any point and observe how each player exploits the weak moves of the other. With the aid of an electronic database that collates similar trading sessions, we can even explore how alternate moves by each side produce different outcomes. Moreover, we can play and replay the ?games? (and their similar variants), seeing if our simulated trading decisions accurately reflect our reading of the strengths and weaknesses of the players? positions.
How could we create such a database? Two methods stand out at present, and my hope is that software vendors will create even more:
- Replay. Some programs, such as Ensign and e-Signal, allow users to replay market data at varying rates of speed. This permits repetition of a market day, so that paper trading can be accompanied by review and fresh practice. Programs that allow users to save and replay tick data are especially valuable, as this creates a library of trading sessions akin to the collections of chess games found in books.
- Taping. Videotaping of one?s trading screens allows for unlimited review of market action and one?s trading decisions. It is not too far-fetched to imagine video-taping of simulated trading from video-taped data, creating feedback loops for learning. Over time, collections of these tapes form a library for study that would allow traders to practice trading almost any kind of market imaginable.
If this analysis has merit, then most of the services offered to traders in the popular media have limited value. Self-help techniques, exhortations regarding discipline, didactic presentations of patterns, and general rules and advice do not turn chess novices into experts, and there is no reason to believe they will advance the performance curve for traders. Knowledge and practice?and especially the direct experience of knowledge-in-practice?are the keys to the acquisition of expertise.
We commonly hear the statistic that 90% of all traders ultimately fail. If this is so, it is not because they lack the right personality traits, indicator patterns, or software programs. Rather, they have failed to structure their learning to facilitate expertise. This is one of the most important lessons we can learn from the decades of research and hundreds of studies on the topic of performance. The path to our greatness lies not only in performing, but in the systematic work we put into performance. The next great advance in trading technology, I believe, will be the creation of dynamic learning environments that serve as the electronic equivalent of chess books. The learning platforms we rig for ourselves today will pale in comparison to tomorrow?s technology, but that matters little to those pursuing self-development. The single most important step you can take, Ayn Rand realized, is to fight for tomorrow, so that you might live in it today.