The speculator’s chief enemies are always boring from within. It is inseparable from human nature to hope and to fear… Instead of hoping he must fear; instead of fearing he must hope. He must fear that his loss may develop into a much bigger loss, and hope that his profit may become a big profit."
— Edwin Lefèvre (1923)
When it comes to placing and executing stops, there are various factors to consider including psychological aspects, statistical probabilities, money management, market volatility and order placement. Experienced traders study all of these areas and use that knowledge to form an approach that integrates these domains into an actionable structured discipline. This is what separates skilled from unskilled traders.
The human mind is susceptible to perceptual distortion, inaccurate judgment and illogical interpretation. Such mental trickery impacts decision-making, and colloquialisms like "markets can remain irrational longer than you can remain solvent" are intended to address these concerns. Ironically, such "rules of thumb" are exactly the kind of readily accessible and loosely applicable problem solving strategies, known as heuristics, that lead to the issue of cognitive bias in the first place.
The phenomenon of human behavior to make judgment calls not identical to the rules of formal logic or statistical probabilities likely evolved as an adaptation for making decisions under uncertainty. In many circumstances, heuristics can enable a faster thought process as well as lead to effective actions in a given context. On the other hand, cognitive bias reflects the inability to reason properly in comparison to a set of independently verifiable facts. How a situation is framed is key to influencing our choices.
Let’s suppose you were given a choice between an 80% opportunity of winning $50,000 and a 20% risk of not winning anything, vs. a 100% assurance of receiving $35,000. Which option would you choose? Alternatively, given the choice between an 80% risk of losing $50,000 and a 20% opportunity of not losing anything, vs. a 100% assurance of losing $35,000, which option would you choose now?
In an experiment by Kahneman and Tversky (1979) who introduced the notion of cognitive bias, 80% of the participants chose $35,000 in the first scenario, even though the riskier choice had a higher expected value ($50,000 x 0.8 = $40,000); and 92% of the participants in the second scenario chose to gamble on a 20% opportunity of not losing anything. This framing occurs because people’s fear of loss induces them to take greater risks in a losing situation (e.g., holding onto losses), whereas in a winning situation people have a tendency to become risk averse and prematurely take profits (i.e., not let profits run).
This leads directly into a discussion on money management techniques evolved from betting systems. Most gambling, such as a coin toss, is based on pure random outcomes — if you toss a coin 10 times and each time it comes up heads, the odds that it will come up heads again on the eleventh try are still 50/50. Mathematical systems designed around trade sizing are an attempt to best utilize a limited bankroll to exploit favorable situations.
One example is the Martingale strategy where a trader doubles his/her trade after a loss. The strategy derives from the idea that by always doubling your trade after a loss, you eventually would win enough to cover all past losses plus one unit. In real life, however, minimum and maximum lot sizes imposed by either a casino or futures broker effectively place a stop on the simple mathematical system of doubling up.What should be apparent then is that such systems increase a player’s bankroll volatility, thereby increasing the risk of ruin. Not surprisingly, there are numerous variations on modified doubling-up systems, or strategies that act in reverse and increase trade sizes after a win. The D’Alembert strategy is one such system whereby a trader increases his next trade by one unit upon winning, and reduces his next trade size by one unit after a loss. In the final analysis, however, it is impossible to convert a game with negative expectations (less then 50/50 chance) into positive expectations (greater than 50/50 chance) through an optimized betting system alone.
The above dialogue provides us with sufficient background to discuss the central issue involving money management-related stop placements — that of acting boldly, taking on too much risk and going bust; or trading too conservatively, which severely limits a trader’s ability to receive a good return on capital.
Let’s assume your trading strategy tends to win 53% of the time and lose 47% of the time, and that you have a $100,000 account. Playing it safe and risking $100 on each trade would minimize your chances of losing your initial stake, but given that the expected gain is 6% of $100 per trade, the returns would be too low to overcome transaction costs and trading overhead. Alternatively, if you risk all of your account on each trade, the probability you will be ruined moves toward certainty with each trade.
One way to maximize returns over the long run with acceptable risk is through use of the Kelly Criterion. This approach involves trading the same percentage of an account on each trade. To obtain the Kelly percentage, subtract the win/loss ratio from win probability [Kelly % = W – ((1 – W) / R)]. To calculate win probability, divide the number of trades with positive returns by the total number of winning and losing trades during this time period. To calculate the win/loss ratio, divide the average gains on winning trades by the average losses on losing trades.
The outcome of applying the Kelly formula is known among investment professionals as the "optimal geometric growth portfolio" because it promotes efficient diversification. In effect, as winnings accrue trade sizes increase, and as losses accrue, trade sizes decrease. As a result, the chance of ruin is small, although a run of bad luck on a series of trades could make it increasingly difficult to break even (see "Problem with percentages").
Of course the application of any system, including the Kelly Criterion, requires common sense. For example, if the Kelly percentage is 4% and you apply this parameter as a money management stop across 25 trades simultaneously, essentially your Value at Risk (VaR) is 100%. In practice, because over-trading is worse than under-trading, venturing a fraction of the amount recommended by the Kelly formula is suggested. This helps protect against errors in "edge" calculations, and helps reduce portfolio volatility.
Another consideration is trade frequency vs. magnitude of winnings. Said otherwise, the frequency of correctness does not matter, it is the magnitude of correctness that matters. In Nassim Taleb’s book, Fooled by Randomness, he provides a table, which highlights the difference between probability and expectations.
Outcomes are asymmetric. Even though there is a higher probability that the market will go up, the expectation is negative because if the market goes down, the magnitude will be greater. Using horse racing as an analogy, a horse with a high likelihood of winning can be a good or a bad bet — the difference being the odds. In other words, a 10-1 shot may be a better bet.
This exposition hints at one of the most important principles in successful trading — planning your exit before you enter a trade. Knowing beforehand if the risk outweighs the reward is key to determining positive expectancy and stacking the odds in your favor. However, finding where to place technical stops —as opposed to money management stops — is a balancing act. You should place technical stops closer to the market than a money management stop (your maximum allowable risk), as this establishes two layers of protection. Also try to avoid placing these stops at obvious levels to reduce the risk of getting hit and experiencing slippage.
For example, it is common to hear advice on placing stops below the latest low when long, or above the latest high when short. Because this method is so frequently used, these support-resistance levels become congestion areas that often result in false breakouts. Not surprisingly, pros "gun" for such levels trying to trigger stops with false breakouts. Then after these stops are "cleaned out," the market has a tendency to reverse, but not always — all it takes is a real breakout to wipe out an undisciplined trader without stops (see "High traffic area?").
You may want to place technical stops a bit closer with the understanding that losses may be more frequent, yet at the same time smaller. Or you could place your stop farther away from the most obvious chart areas in order to reduce the chance of getting hit. The key is to try and not place stops at levels that are obvious, and instead place technical stops where the market is not expected to go.
Aside from determining technical stops based on chart patterns, another common strategy is adjusting your stop based on market action. The term "trailing stop" refers to an exit level that adjusts upward when the price of a futures contract makes a new high if long; or adjusts downward when the price makes a new low if short. Should the futures price trigger the trailing stop, this is taken as a signal to close out the position. This method is used by many traders to "keep" profits as they accrue.
Astute traders are knowledgeable about the psychological pitfalls that influence decision-making and behavioral biases. Traders should learn to think and act like casinos, not gamblers, with respect to statistical probabilities and positive/negative expectancies. As the saying goes, "plan your trade and trade your plan" and do not get emotional about cutting losses — it is just the cost of doing business as a trader.
Key to successful stop placement is calculating a tolerable risk level per trade and implementing a position-sizing strategy that optimizes portfolio growth. As "Measuring risk/reward" (below) shows, this calculation is an interdependent process in which account size, contract multiple/granularity, money management, position sizing, trade frequency and market volatility all play a role in normalizing allowable risk per trade.
As to the placement of technical stops, there are probably as many methods for determining when/where to exit trades as there are systems for entering trades. Professionals invest much of their time and energy planning exits. What is important is that you do not place your technical stop outside your money management stop. If your system logic does this, it is a sign to rethink the entry.
Last to consider are the type of instructions provided to your broker. Stops become market orders once your designated price is touched and only should be used when your priority is certainty of execution rather than price. Alternatively, you can use stop limit orders that limit the amount of allowable slippage, but can leave you exposed. Many traders use a mental stop, entering the market on a limit once their level is reached to avoid the potential cascading effect of stops. While avoiding slippage is key, a trader should account for a certain amount of slippage on stops.
Michael "Mack" Frankfurter is managing director, operations of Cervino Capital Management LLC.