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Initial Stop: Solution or Problem?

Initial Stop: Solution or Problem? - раздел Литература, Beyond Technical Analysis Many Traders Have Raised Stop Placement To An Art Form Because It Is Not Clea...

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.

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Все темы данного раздела:

Developing New Trading Systems 73
Introduction 73 The Assumptions behind Trend-Following Systems 74 The 65sma-3cc Trend-Following System 75 Effect of Initial Money Management Stop 88 Adding Filter to the 65sma-3cc Syste

Selected Bibliography 253 Index 255 About the Disk 261
Preface This is a book about designing, testing, and implementing trading sys­tems for the futures and equities markets. The book begins by develop­ing trading systems and ends by def

Introduction
Хорошая система торговли удовлетворяет вашу индивидуальность. К счастью, самый быстрый способ находить каждый - через процесс испытания(суда) и ужаса(террора). Любое проверяющее система программное

РАЗВИТИЕ И ВНЕДРЕНИЕ ТОРГОВЫХ СИСТЕМ
На предмете. Привлекательная особенность - то большинство материала, первоначальное или новое. Эта книга разделена на две половины по четыре главы каждая. Первая часть посвящена проектированию торг

The Usual Disclaimer
Throughout the book, a number of trading systems are explored as ex­amples of the art of designing and testing trading systems. This is not a recommendation that you trade these systems. I do not c

What Is a Trading System?
A trading system is a set of rules that defines conditions required to in­itiate and exit a trade. Usually, most trading systems have many parts, such as entry, exit, risk control, and money manage

Comparison: Discretionary versus Mechanical System Trader
Table 1.1 compares two extremes in trading: a discretionary trader and a 100% mechanical system trader. Discretionary traders use all inputs that seem relevant to the trade: fundamental data, techn

Discretionary Trader 100% Mechanical System Trader
Subjective Objective Many rules Few rules Emotional Unemotional Varies

Why Should You Use a Trading System?
The most important reason to use a trading system is to gain a "statisti­cal edge." This often-used term simply means that you have tested the system, and the profit of the average trade—

Robust Trading Systems: TOPS COLA
A robust trading system is one that can withstand a variety of market conditions across many markets and time frames. A robust system is not overly sensitive to the actual values of the parameters

How Do You Implement a Trading System?
Begin with a trading system you trust. After sufficient testing, you can determine the risk control strategy necessary for that system. The risk control strategy specifies the number of contracts p

Who Wins? Who Loses?
Tewles, Harlow, and Stone (1974) report a study by Blair Stewart of the complete trading accounts of 8,922 customers in the 1930s. That may seem like a long time ago, but the human psychology of fe

Beyond Technical Analysis
The usual advice for technical traders is a collection of rules with many exceptions and exceptions to the exceptions. The trading rules are diffi­cult to test and the observations are hard to quan

Introduction
This chapter presents some basic principles of system design. "You should try to understand these issues and adapt them to your preferences. First, assess your trading beliefs—these b

What Are Your Trading Beliefs?
You can trade only what you believe; therefore, your beliefs about price action must be at the core of your trading system. This will allow the trading system to reflect your personality, and you a

Six Cardinal Rules
Once you identify your strongly held trading beliefs, you can switch to the task of building a trading system around those beliefs. The six rules listed below are important considerations in tradin

Rule 1: Positive Expectation
A trading system that has a positive expectation is likely to be profitable in the future. The expectation here refers to the dollar profit of the av­erage trade, including all available winning an

Rule 2: A Small Number of Rules
This book deals with deterministic trading systems using a small number of rules or variables. These trading systems are similar to systems people have developed for tasks such as controlling a che

Days since 08/01/95
Figure 2.2 SScP-500 closing data with regression using terms raised to the fifth power. (2.1) (2.2) Est Close = C0

More rules need more data
2 4 8 12 16 24 32 48 64 96 128 Number of rules

Rule 3: Robust Trading Rules
Robust trading rules can handle a variety of market conditions. The per­formance of such systems is not sensitive to small changes in parameter values. Usually, these rules are profitable over mult

Number of rules
Figure 2.5 Adding more rules delayed entries and exits, increasing maximum intraday drawdown. Note that the horizontal scale is not linear. today's high + 1 point on a buy

Number of rules
Figure 2.6 Increasing the number of rules decreased profits in the U.S. bond market from January 1, 1975 through June 30, 1995. Note that the horizontal scale is not linear.

Delay (» of days) after crossover
Figure 2.7 The effect on profits of changing the number of days of delay in accepting a crossover signal of a 3-day SMA by 12-day SMA system is highly de­pendent on the delay.

Here must be a Figure.
Figure 2.8 The August 1995 crude oil contract with curve-fitted system profitable trades. As many as 87 percent of all trades (20 out of 23) were profitable. A second clue

Rule 4: Trading Multiple Contracts
Multiple contracts allow you to make larger profits when you are right. However, the drawdowns are larger if you are wrong. You are betting that with good risk control, the overall profits w

Rule 5: Risk Control, Money Management, and Portfolio Design
All traders have accounts of finite size as well as written or unwritten guidelines for expected performance over the immediate future. These performance guidelines have a great influence over the

Equity Curve: 3SF vs SF+TY+CT
-3SF -SUM

Time (months)
Figure 2.11 This contrived jagged equity curve has a standard error of 2.25. The perfectly smooth equity curve has an SE of zero. The standard deviation of monthly returns is 33 pe

Rule 6: Fully Mechanical System
The simplest answer to why a system must be mechanical is that you cannot test a discretionary system over historical data. It is impossible to Summary37 for

Summary
This chapter developed a checklist for narrowing your trading beliefs. You should narrow your beliefs down to five or less to build effective trading systems around them. This chapter also

Introduction
This chapter examines many key system design issues. Now that you un­derstand some basic principles of system design, you can consider more complex issues. And as you understand these issues, you c

Diagnosing Market Trends
You can design a profitable trading strategy if you can correctly and con­sistently diagnose whether a market is trending. In simple terms, the market exists in two states: trending and ranging. A

ADX Rising, RAVI Rising, Market (1/1/89-6/30/95) ADX>20 RAVI > 3
Coffee 30.2 43.3 Copper, high-grade 27.0 35.3 Cotton 29.2

To Follow the Trend or Not?
If you are not a large hedger or an institutional trader, you can follow either of two basic strategies when you design a trading system. You can be a trend follower, or you can take antitre

Profits of age of Winner Loser tive Drawdown
($) Trades Winners ($) ($) Losers ($) Coffee 1,837 27,065 -11,215

To Optimize or Not to Optimize?
If you have a computer, you can easily set up a search to find the "opti­mum" values for a system over historical data. The results can be truly astonishing. Imagine your profits if you c

Length of Optimized 3 mo. 1990 6 mo. 1990 9 mo. 1990 12mo.1990 SMA Relative Relative Relative Relative Relative (days) Rank Rank Rank Rank Rank

Day CHBOC with varying initial stop
S

Changes In MIDD for 20-day CHBOC on Coffee
-20000 -22000 S -24000 -26000 -28000 -30000 -32000 -34000 -36000

Changes In percent profitable trades, 20-day CHBOC on Coffee
>o o 10 o irt o io o io t- r- cm cm co ro ^t -a- Initial stop ($)

Cumulative frequency distribution average 10-day daily range in coffee
250 750 1250 1750 2250 2750 3250 3750 4250 4750 5250 Range ($)

Does Your Design Control Risks?
As you design your trading system, remind yourself that one of your key goals is to control the downside risk. You will quickly discover that risk is a many-splendored thing. This section br

Data! Handle with Care!
You have many choices when you select data for your system testing. You should therefore exercise great care in choosing your test data because they have a big influence on test results. C

Profit MIDD of Wins Win/Loss Data Type ($) ($) Trades (%) Ratio
Actual with rollovers 17,963 -21,663 111 40 1.80 Continuous type 38/13 18,450 -24,813 79 31 2.74 Continuous type 49/25 20,413 -22,137 77 31 2.89 Continuous type 55/25 20,

Choosing Orders for Entries and Exits
You have three basic choices for orders that you use to initiate or exit your trades: market, stop, or limit orders. There are three philosophies at work here. One says to get your price, implying

Understanding Summary of Test Results
This discussion of the detailed summary of test results found in technical analysis programs uses in part the report from Omega Research's TradeStation™ software. The purpose of the summary is to s

British Pound 38/13-dally 02/13/75 - 7/10/95 Performance Summary: All Trades
  Total net profit ($) 155,675.00 Gross profit ($) 266,918.75 Total number of trades 71 Number of winning trades 32 Largest winning trade

What the Performance Summary Does Not Show
The test summary leaves out some important information, highlighted below. You may wish to examine these factors in greater detail. One simple ratio is the recovery factor (RF). RF is abso

A Reality Check
This section sounds a note of warning before you proceed: Test results are not what they seem. You should recognize that trading systems are designed with the benefit of hindsight. This is true bec

Introduction
A trading system is only as good as your market intuition. You can for­mulate and test virtually any trading system you can imagine with today's software. The previous chapters studied the b

The Assumptions behind Trend-Following Systems
The basic assumptions behind a simple trend-following system are as follows: 1. Markets trend smoothly up and down, and trends last a long time. 2. A close beyond a moving average

The 65sma-3cc Trend-Following System
This section discusses how to formulate and test a simple, nonoptimized, trend-following system that makes as few assumptions as possible about price action. It arbitrarily uses a 65-day simple mov

Distribution of Trade P&L for 65sma-3cc: 2400 trades
tOU                    

Comparing frequency distribution of 65sma-3cc trades to standard normal distribution
  | 0.2

Frequency distribution of 65sma-3cc trades compared to a modified normal distribution
^-•-•^-T-OOOOOOOOOOOOOT-'- Z (standard deviations)

Maximum favorable excursion of 1,565 losing trades of 65sma-3cc system
800 700 600 500 400 300 200 100 0 s Maximum profit ($) Figure 4.9 A histogram of maximum profit in 1,565 losing trades over 20 ye

Cumulative Frequency of winning trades, 65sma-3cc system
2000 3000 Maximum pro

Effect of Initial Money Management Stop
Since the initial test of the 65sma-3cc model was encouraging, we can now do more testing. The first item of business is to insert an initial money management stop into this model. Our detailed ana

Number of trades Increases and levels off.
•US Bond -DM 750 1000 125

Volatility-based initial money management stop
Figure 4.13 The profits (upper line) increase as the initial money management stop is loosened. Eventually, the stop is too wide and profits begin to level off. The lower line is t

Profit and MIDD for LH as a function of initial MMS

Volatility-based initial MMS
Figure 4.14 The profits (upper line) increase as the initial money management stop is loosened. The lower line is the maximum intraday drawdown. Data are for the live hogs market.

Adding Filter to the 65sma-3cc System
So far, we have let the trading system generate pure signals without try­ing to filter the signals in any way. As we have seen, this system will gen­erate many short-lived or "false" sign

Largest losing trade increases as MMS Increases
-1000 -2000 -3000 <s.

Volatility based initial MMS for Sugar
Figure 4.15 Largest losing trade for sugar using the 65sma-3cc trading system increases as the volatility-based initial money management stop increases. also the short exi

Adding Exit Rules to the 65sma-3cc System
Selecting general and powerful exit rules is a difficult challenge in sys­tem design because the markets exhibit many different price patterns. One form of exit that is particularly easy to impleme

Channel Breakout-Pull Back Pattern
This section discusses a trading system based on a pattern observed in mature markets, that is, markets with a large volume of institutional ac­tivity. In these markets, the big players have a tend

An ADX Burst Trend-Seeking System
We have assumed that the market was about to trend in both the 65sma-3cc and the CB-PB systems, although we did not actually verify that the market was trending because it is difficult to measure t

A Trend-Antitrend Trading System
In this section we explore the trend-antitrend (T-AT) system, designed to switch automatically between an antitrend mode and a trend-follow­ing mode. You will like this system if you aggressively l

Gold-Bond Intermarket System
This section develops intermarket trading systems for trading negatively or positively correlated markets. We begin with a quick review of the difficulties of formulating intermarket models. The go

A Pattern for Bottom-Fishing
Market-specific systems work best on a particular market because they capture some unusual feature of that market. It is difficult to speculate why certain markets show signature patterns. We shoul

Time: 4/82-7/95
Figure 4.39 Equity curve for bottom-fishing pattern (9/82-7/95) with X = 1 and /= 0 (aggressive trades) for SScP-500 data with rollovers. Initial money man­agement stop was $2,000.

Identifying Extraordinary Opportunities
Once or twice a year, the futures markets provide extraordinary oppor­tunities for exceptional profits, and if you can take advantage of these opportunities, your account performance will improve s

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