The 65sma-3cc Trend-Following System - раздел Литература, Beyond Technical Analysis This Section Discusses How To Formulate And Test A Simple, Nonoptimized, Tren...
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 moving average of the daily close to measure the trend. Sixty-five days is simply the daily equivalent of a 13-week SMA (13x5= 65), representing one-quarter of the year. This is an intermediate length moving average that will consistently follow a market's major trend.
As shown in Figure 4.1, when the market is trending up, prices are above the 65-day SMA, and vice versa. In sideways markets, this SMA flattens out and prices fluctuate on either side. Clearly, the trading system picks up and sticks with the prevailing trend (see Figure 4.2).
There are many ways to make the decision that the trend has turned up. The usual way is to use a shorter moving average of, say, 10 days, and decide that the trend has changed when the shorter average crosses over or under the longer moving average. If you decide to use a short moving average, its "length" will be crucial to your results. Another weakness is that often prices will move faster than the shorter moving average, so that the entries can seem rather slow.
76 Developing New Trading Systems
Figure 4.1 September 1995 Japanese yen contract showing the 65-day SMA and the signals generated by the system.
Figure 4.2 The 65sma-3cc system stayed long throughout this major uptrend in the S&P-500 index in 1995.
The 65sma-3cc Trend-Following System 77
Hence, the 65sma-3cc system will require three consecutive closes (3cc) above or below the 65-day SMA (65sma) to determine that the trend has changed. For example, the trend will be said to have turned up after three consecutive closes above the 65-day SMA. Similarly, the trend will have turned down after three consecutive closes below the 65sma. Once again, the requirement of three consecutive closes is arbitrary. It could be ten consecutive closes or any other number. Clearly, the results will vary with the number of confirming closes.
If you are afraid of false signals (see Figure 4.3), then the number of closes you use will act like a filter in reducing the number of trades. In a fast-moving market, requiring a large number of consecutive closes will give delayed entries (see Figure 4.4). Conversely, if a market is moving sluggishly, a small number of consecutive closes will give false signals. Thus, there is a trade-off here that determines how quickly you recognize a change in trend.
Once you recognize a change in trend, you still have to decide how to enter the trade. You should enter the trade on the next day's open, to guarantee that you can execute the signal and get a fill. For example, if the three consecutive closes criterion is satisfied as of this evening's close, you should buy at the market on the open of the next trading day. You will get a fill somewhere in the opening range the next day. It is likely that you will be filled near the top of the opening range for buy orders, and near the bottom of the opening range for sell orders. This
Figure 4.3 The choppy sideways action in December 1995 British Pound generated a string of whipsaw losses for the 65sma-3cc system.
78 Developing New Trading Systems
Figure 4.4 These swing moves in December 1995 crude oil produced many trades but small profits because the 65sma-3cc system does not have a specific exit strategy.
slippage should be ignored, and just lumped into your $100 allowance for slippage and commissions. The main effect of this entry mechanism is that you are not filtering out any entry signals, and ensuring that you will put on this position the first time the entry conditions are satisfied.
There are a number of choices on how to actually enter the trade. For example, you could enter the trade on the close of the third consecutive close above or below the 65-sma. A second choice would be to enter the next day on a stop order beyond the previous, or a nearby, high or low. In effect, you would also filter out some entry signals, because you would not get a fill on every signal. This may be useful in situations where prices briefly spike beyond the 65-sma during prolonged trends.
A third entry choice would be to delay entry for x days after the signal, and then enter beyond a nearby n-day high or low. This is another way to filter down the entry signals in order to find more profitable ones. Note that if you use a limit order for your entries, occasionally you may not be filled at all, missing the entry by just a few ticks. Hence, you should enter on the next day's open to assure an entry into the new trend.
Before we proceed, let us put this entry signal through a critical test to check if the 65sma-3cc entries are better than random. Following the approach of Le Beau and Lucas (see bibliography for details), let us
The 65sma-3cc Trend-Following System 79
test the entry signal with exit on the close of the ra-th day, without any stops, and no deductions for slippage and commissions. For simplicity, only the effect of long entries are shown. The proportion of trades that are winners should consistently be more than 55 percent. The test includes the long entry over 21 markets, stretching from January 1, 1975, through July 10, 1995, using a continuous contract. Because not all markets were trading back in 1975, all available data are used.
Table 4.1 shows that, on average, 55 percent of the long entries were profitable, suggesting that the 65sma-3cc model probably does better than random. The result for short trades is similar, and you can be reasonably confident that this model provides robust entry signals. Your task is now to combine this model with risk control and exit methods that match your trading mentality.
Table 4.1 Testing 65sma-3cc long entry for randomness over 21 markets
using all available data between 1 /1 /75 and 7/10/95. Exit on the close of the n-th day.
Market
5 days
10 days
15 days
20 days
30 days
50 days
British pound
Coffee
Copper
Corn
Cotton
Crude oil
Deutsche mark
Eurodollar
Gold
Heating oil
Japanese yen
Live hogs
Orange juice
Silver
Soybeans
S&P-500
Sugar
Swiss franc
10-year T-note
U.S. bond
Wheat
Average
54.62
55.95
55.86
55.71
54.52
80 Developing New Trading Systems
To summarize this nonopdmized system, the actual trade entry is at the market on the open of the next trading day after the close of the day the signal is received. You will notice that there are no specific exit signals at this point, which means that the short entry signal is also the long exit signal, and vice versa. In practice this means that if you are long one contract, you will sell two contracts to go net short one contract, and vice versa.
Note that for the tests below we will add a condition to prevent back-to-back entries of the same type. This will allow an apples-to-apples comparison when studying the effect of adding stops or exits. yovl do not need this condition for actual trading.
To summarize what is not defined at this point: There are no specific risk-control rules in terms of an initial money management stop, nor any money-management rules to determine the number of contracts to trade. We will just trade one contract for simplicity without any risk-control stop. This is not a recommendation to trade without a risk control stop; the calculations are done without any stops here to illustrate a point. Later, we will examine how to add risk control and study the effect of money management.
The 65sma-3cc system should make all its profits during strong trends. It should lose money in sideways or nontrending markets. And it should have between 20 and 50 percent profitable trades. We tested this model over 23 markets using 20 years of continuous contract data. If a contract was not traded for 20 years, then we used all available data from the starting date. The usual allowance of $100 per trade for slippage and commissions was made. Thus, this is a rigorous test for a nonoptimized system over a long test period, and across a large number of markets. The results are summarized in Table 4.2.
The results for this simple, nonoptimized trend-following system are encouraging. You could have made a paper profit of $1,386,747 by trading just one contract for each market, and been profitable on 19 of 23 widely diverging markets. The test sample generated 2,400 trades, so this is a highly significant test. Approximately 34 percent of all trades were profitable, a number typical of trend-following systems.
The ratio of average winning to average losing trades was excellent, at 3.3 averaged over the 2,400 trades. This number is useful for calculating the risk of ruin; a number above 2.0 is desirable, and anything over 3 is welcome news. The average trade made a profit of $558, an attractive amount, considering transaction and slippage costs. It is customary to seek a number over $250 for the average trade. The average profit per market was $60,293, approximately 2.74 times the average maximum in-
The 65sma-3cc Trend-Following System 81
Table 4.2 Test results for 65sma-3cc trend-following system
Market
Years
Paper Profit ($)
Total Trades
Winning Trades (%)
Average Win/Loss
Average Trade (S)
Maximum Intraday Drawdown (S)
British pound
7/75-7/95
125,344
3.72
1,193
-25,431
Canadian
6/77-7/95
-12,750
2.32
-102
-21,030
dollar
Cocoa
5/80-7/95
-15,370
1.80
-153
-2,219
Coffee
5/75-7/95
239,096
5.83
1,993
-36,956
Copper,
12/88-7/95
-7,890
1.48
-161
-17,355
high-grade
Corn
5/75-7/95
26,081
2.98
-4,331
Cotton
5/75-7/95
112,490
4.26
1,023
-8,730
Crude oil
8/83-7/95
17,570
2.58
-11,690
Deutsche
7/75-7/95
68,575
2.90
-1 3,250
mark
Eurodollar
6/82-7/95
34,175
3.16
-7,150
Gold, Comex
5/75-7/95
53,770
3.44
-28,440
Heating oil
7/79-7/95
56,198
3.89
-18,021
Japanese
12/76-7/95
143,425
3.80
1,649
-12,963
yen
Live hogs
5/75-7/95
31,971
2.49
-5,863
Orange juice
5/75-7/95
13,018
3.05
-27,950
Silver
5/75-7/95
197,305
6.87
1,370
-51,040
Soybeans
5/75-7/95
62,406
2.86
-21,768
S&P-500
9/82-7/95
-7,260
3.13
-72
-97,470
Sugar
5/75-7/95
49,493
3.75
-10,806
Swiss franc
7/75-7/95
108,475
3.28
1,086
-11,638
10-year
9/82-7/95
34,219
3.66
-1 3,743
T-note
U.S. bond
1/78-7/95
50,143
2.62
-38,819
Wheat
5/75-7/95
6,263
2.78
-19,663
Total
1,386,747
2,400
Average
60,293.3
3.3
-22,014
Standard
66,698.1
1.17
20,342
Deviation
traday drawdown, of-$22,014. This is a healthy recovery factor, or coverage of the worst losing streak of the system.
In summary, a simple trend-following approach worked on many markets over a long time period with few assumptions and no optimization.
Developing New Trading Systems
The results also point out some weaknesses of this system. The average profit per market is 90 percent of the standard deviation of the average profit. This means that profitability varied widely from market to market. The maximum intraday drawdown was 108 percent of its standard deviation, implying that the drawdowns also varied considerably among markets. The standard deviation of the average trade also implies that results can vary substantially over time or across markets. A further weakness is the relatively small number of profitable trades. Thus, we can summarize the principal weakness as a large variability in the results over time and across markets.
Combining the strengths and weaknesses, you would say that this is a sound trend-following system with good chance of being profitable over many markets over a long time period. But because of the large variability in results, you would have to trade this system relatively conservatively. You should allow a large equity cushion to absorb drawdowns.
A look under the hood of this trading system, so to speak, and a closer examination of the results of the analysis reveal further details of
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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
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
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
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
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
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
Initial Stop: Solution or Problem?
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 magn
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
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
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
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
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
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
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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