Many traders have raised stop placement to an art form because it is not clear if the initial stop is a solution or a problem. The answer depends on your experiences. Often, the stop acts as a magnet for prices. It seems the market hits the stop, only to reverse and resume the previous trend. Thus, initial stops can easily test your patience. Even so, initial stops should be an essential part of managing trading risk. This section discusses some general issues related to selecting an initial stop. Detailed examples appear in the following chapters.
If you use an initial stop at all, use stops that follow money-management rules but are derived from system design and market volatility. A good idea is to use a 2 percent of equity initial stop, and then use maximum adverse excursion (MAE), a distribution of the worst loss in winning trades, to select the dollar value of the stop for a particular system. Relate the MAE to some measure of market volatility before calculating the number of contracts. Thus, the initial stop meets three criteria:
money management, MAE, and volatility.
Another issue involves whether you should place your stop loss order with your broker. Many traders will have a well-defined exit price, but will not place an order in the market. They like to monitor the market in real time, and will place the exit order themselves if needed. This is termed the “discretionary initial stop.” If you have good discipline and judgment, the discretionary initial stop could work well for you. How-ever, if you cannot monitor the market continuously, it may be prudent to enter the exit order with your broker.
What values of the initial stop should you use during system testing? That depends on the type of data you have and the nature of the system design. The issue is whether to use a tight stop or a loose stop. A tight stop may have a dollar value less than $500 per contract. A loose stop could be as high as $5,000.
Let us assume you have only daily data. In this case, it is difficult to test a tight stop accurately because the exact track of prices during the day is unknown. Suppose you are trading the bond market, and the typical daily range is $1000. Now, say you want to test a $100 stop with daily data. Most system-testing software will stop you out on the day of entry because it does not know the exact track of prices. Of course, if you have intraday data, then you can more accurately test a $100 stop. Thus, if your stop is very tight, you need intraday data for accurate tests.
There are two broad types of systems, those that are self-correcting and those that are not self-correcting. Self-correcting systems have rules for long and short entries. Such systems will eventually generate a long signal for short trades and vice versa. Because these systems are self-correcting, the reverse signal will limit losses, even without an initial stop. Of course, the losses will depend on market volatility, and easily could be as large as -$10,000 per contract.
Systems that are not self-correcting include those that trade the long side or the short side only. Thus, you could get a false short signal and remain short through a long up trend. The losses in these systems can be unlimited, and hence must be protected by an initial stop. A onesided system with an exit strategy can become self-correcting. The exit strategy will limit losses in a one-sided system by closing out the trade at some preselected point. For example, a self-correcting, longside-only system has an exit stop at the most recent 14-day low.
You can get a better feel for the efficiency of entry rules if you test a self-correcting system without initial stops. However, if the system is not self-correcting, then you must test it with an initial stop. There is still the issue of how wide the stop should be. Relatively wide stops, defined as three times the 10-day average of the daily range, are a good choice. In this way the stop has a smaller influence on results than do the entry rules. If you like tight stops, then use intraday data, or use an amount larger than the recent daily trading range.
Your data set will strongly influence the results of your initial stop selection. If your data set has many trading range markets, then a tight stop will produce whipsaw losses. Even though each loss may be small, the sum of a series of losses can be large. A loose stop will prevent whip-saw losses in a trading range. If the market is trending, then the value of the initial stop is not critical. Thus, a trending market will rescue a system with tight stops, and you can get some astonishing results.
Relatively loose stops, between $1,500 and $5,000, work well. If the stops are relatively “loose” then there is little difference between nearby values. Conversely, if the stop is “tight,” then small changes in the stop can produce big swings in equity. Hence, the system tests in this book use daily data and stops ranging from $1,000 to $5,000.
Often, the point of discussion in this book does not depend on the amount of the stop. Sometimes the loose stop is a necessary design fea-ture. In such cases the reason for choosing the wider stop is stated. Ul-timately, if you do not like my stop, you can retest the system to suit your preferences.
Some actual calculations will clarify this discussion. Here we use the standard 20-day channel breakout on the close (CHBOC) trading system. This system buys on the close if today’s close is higher than the highest high of the last 20 days. The short sale condition is symmetrical.
The system sells short on the close if today’s close is lower than the lowest low of the past 20 days. We will test this system on the coffee market, which has seen much volatility as well as strong trends. We will vary the initial stop from $0 to $8,000 in $500 increments and allow $100 for slippage and commissions.
Consider for a moment what the $0 initial stop means. The system goes long or short on the close. Thus, the trade will remain open only if prices continue to move strongly beyond today’s close. This is the toughest stop you can impose because the only trades that survive are the ones that are profitable immediately.
Observe that profits increase steadily as we loosen the initial stop (see Figure 3.3). There was a surprising profit of $158,103 with a $0 initial stop on just 20 (of 434) trades. This confirms a common piece of market wisdom that the best trades are profitable immediately. It also confirms that only 5 percent or so of the trades are the “big ones.” So you should work hard not to miss them.
Figure 3.4 shows that a tight stop can produce a drawdown greater than using no stop at all. More and more trades recover their losses and close at a profit as the stop widens. Eventually the stops are so large that they have little effect, and so MIDD stabilizes.
The initial stop cuts off fewer trades as we loosen it (see Figure 3.5), and hence the total number of trades produced by CHBOC de-creases. Once the stop is “too loose” (more than $3,000 or so), it has little effect, and the number of trades stops declining.
Only 5 percent of the trades are profitable with a $0 stop. The per-centage of winners increases quickly as we loosen the initial stop until the stop has little effect (see Figure 3.6). As we loosen the stop, more of the winning trades can survive the vagaries of market action.
As you may expect, the worst losing trade increases as we loosen the stop (see Figure 3.7, page 58). This occurs because the worst case with a $0 stop reflects slippage due to a weak opening. However, as we loosen the stop, the losing trade from a false signal can survive longer.
The highest average 10-day trading range in the coffee market over the last 20 years was approximately $5,025. The average value was $1,015 and the standard deviation was $641. The cumulative distribution (Figure 3.8, page 59) shows that a stop of $3,000 exceeds 98.3 percent of all the 10-day average trading range values seen in coffee over the last 20 years. Hence, $3,000 should be a loose stop. Figures 3.3 through 3.7 show that the changes in performance begin to level off beyond $3,000. Thus, you can view stops greater than $3,000 as “very loose” stops. A $500 stop that covers less than 20 percent of all observed values of the 10-day average daily range qualifies as a “tight” stop.
You can now use the cumulative frequency distribution to select a stop based on market volatility. An arbitrary stop may be too tight or too loose. This analysis assumes that you use the same dollar stop on every trade. If you vary the initial stop on every trade then this analysis will be of little use to you. We already know that stops are hit more frequently during trading range markets. Hence, you could use some measure of trendiness to vary your initial stop.
Variation In biggest losing trade: 20-day CHBOC on Coffee
Many traders feel an aversion to taking a big loss, even though they have no problem taking many small ones. The maximum drawdown usually decreases as the stop increases (see Figure 3.4). Thus, you should try to take the long-term view when you set your stops. If you use a constant stop based on system design, then use loose stops. If you set the stop differently for each trade, then you have probably mastered the fine art of placing stops.
The risk of being stopped out is highest near trade inception, as shown by the calculations in Table 3.11, page 60. This table shows the effect on the length of the average losing trade of using no stop, a $1,500 stop, and a variable stop. A simple 20-day CHBOC model, with no exits other than an initial money management stop, is used, allowing $100 for slippage and commissions. The tests were over a 6-year period commencing May 26, 1989, using continuous contracts.
The data in Table 3.11 show that inserting an initial money management stop of $1,500 reduced the length of the average losing trade by approximately 40 percent to 17 days from 28 days. These calculations confirm that the risk of being stopped out is highest near trade inception. The average winning trade was typically 2 to 3 times longer than the average losing trade.
If you look more closely at Table 3.11, you will see that for some markets, such as gold, sugar, and soybeans, the length of the average losing trade did not decrease much even after adding a stop. This means that the volatility in these markets is not as large as, say, the currency or bond market. An approximate initial stop that will produce an average losing trade length of 10 or 11 days is also shown in Table 3.11. The S&P-500 index futures contract and coffee were the two most volatile markets, followed by cotton, Swiss franc, and the U.S. bond markets. Conversely, gold, sugar, and crude oil were relatively less volatile. Hence, you may find it useful to consider overall market volatility when placing your initial stop.
In summary, you can get a better feel for system performance if you use loose stops with a self-correcting system. If a stop is “tight,” then a small change in the stop can affect long-term performance. If a stop is “very loose,” then changing the stop will have little effect. As you loosen your initial stop, the profits increase and then change more slowly. This means that once you pass some volatility threshold, increasing the initial stop adds little value.
Another reason to use loose stops is that you cannot properly test stops that are smaller than the daily price range. Ideally, you should base your initial stop on money management guidelines, the maximum adverse excursion of the system, and on market volatility. There are many ways to select an initial stop; once you pick a method, you should use it consistently.