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
Initial Stop: Solution or Problem? 53
judgment, the discretionary initial stop could work well for you. However, 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,
Foundations of System Design
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 feature. In such cases the reason for choosing the wider stop is stated. Ultimately, 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.