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A Pattern for Bottom-Fishing

A Pattern for Bottom-Fishing - раздел Литература, Beyond Technical Analysis Market-Specific Systems Work Best On A Particular Market Because They Capture...

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 should take extra care when developing such systems because the market mechanics driving such patterns could change abruptly.


A Pattern for Bottom-Fishing133

The S&P-500 futures contract can be used to illustrate a pattern-based approach. For instance, we consider a continuous contract from April 21, 1982, through July 10, 1995, and test the standard simple mov­ing average crossover system with 10-day and 11-day simple moving av­erages. We use a relatively loose $2,000 initial stop, which will absorb random price fluctuations, and allow $100 for slippage and commissions.

The 10- and 11-day dual crossover system lost $181,005 on paper, with 530 trades. Only 34 percent or 178 trades, were profitable, with a maximum intraday drawdown of $189,370. One interesting feature was that virtually all the loss ($185,545) was on short trades. This makes sense if we recognize that the market has been generally moving up since 1982. However, it is striking that this simple trend-following sys­tem fared poorly in spite of the prolonged uptrend. So the S&P-500 fu­tures market is not a trend-follower's delight.

Because all of the losses were on the short side in the previous test, it makes sense to try the simple moving crossover system in the an-titrend mode. The antitrend rules are as follows:

1. Buy if the 10-day SMA crosses below the 11-day SMA on the close.

2. Sell if the 10-day SMA crosses above the 11-day SMA on the close.

Using the same test period, initial stop, and allowance for slippage and commissions as the previous test, the turnaround in profits with the antitrend rules was remarkable. This antitrend 10- and 11-dayJystem netted $55,920 for a swing of $240,925 on 531 trades. Fully 48 percent, or 254 trades, were profitable, with a maximum intraday drawdown of $32,735.

The results of the antitrend approach are not spectacular. However, they do highlight the unusual nature of the S&P-500 market. They sug­gest that you could find market-specific systems that would test poorly on other markets. For example, the 10/11 antitrend strategy lost $56,775 when tested on the Swiss franc continuous contract over the same period, but the 10/11 trend-following strategy lost just $13,088 over the same period.

The following is a glaring example of how "hindsight" influences system design. There were many "V" bottoms on the daily bar-charts of the S&P-500 market, so a bottom-fishing strategy that tries to pick bot­toms was attempted. Theoretically, it should test well since this is an


134 Developing New Trading Systems

andtrend approach. The rules for the S&P-500 "bottom fishing" pattern are as follows:

1. A 20-day low has formed within the last 5 days.

2. Today's high-low range > X; X = 4 for conservative trades; X = 1 for aggressive trades (each point is not one tick, but one full S&P index point = $500)

3. Today's closing-opening range > Y ; Y = 3 for conservative trades; Y = 0 for aggressive trades.

4. If rules 1,2, and 3 are true, then buy tomorrow on the close.

5. Exit on the close of the twentieth day in the trade.

6. Initial money management stop = $2,000 per contract.

Note that we can fully automate the bottom-fishing pattern. We have no difficulty getting entries, because if we get a signal today, we can buy on tomorrow's close. So it is easy to implement using a mechanical system. For example, the analysis can be done after market hours, and the order entered before trading begins.

This system has a conservative entry combination and an aggres­sive entry combination. The conservative approach generates fewer trades. You can modify this pattern in many ways. The most obvious change is the exit strategy. For example, you could set an exit target at the most recent 20-day high.

The system was tested using System Writer Plus™ and actual S&P-500 contracts. The rollover date was the twentieth day of the month be­fore expiration. The results are in two blocks in Table 4.20 because Sys­tem Writer can process only 30 contracts at a time. You can treat either the conservative or the aggressive set of X and Y values as an unop-timized set. Both combinations were profitable on both blocks of data.

The equity curves for both options are shown in Figures 4.38 and 4.39. The equity curve for the conservative option is smoother than the aggressive option. Also, the aggressive option can produce larger draw­downs than the conservative values.

Data using the March, 1995 S&P-500 contract yield Figure 4.40, page 136, for X = 4 and Y = 3, and Figure 4.41 is for X = 1 and Y = 0. This system picked off the bottoms very accurately. Entry and reduced slippage are assured by entering and exiting on the close. Thus, a pat­tern-based, antitrend, bottom-fishing approach works nicely on the S&P-500 market.


A Pattern for Bottom-Fishing135

Table 4.20 Performance of bottom-fishing system with $2,000 initial stop and exit on the close of the twentieth day in the trade using actual S&P-500 data with rollover

                Number                
                of Trades; Ratio:     Maximum    
        Test Period Net Profit (S) Percen­tage of Wins Average Win/ Loss Average Trade (S) Intraday Drawdown ($) Profit Factor
Pattern
X=4, y=3 9/82-2/88 40,900 18; 44 3.80 2,272 -6,300 3.04
X=4, /=3 2/88-7/95 60,650 46; 39 3.25 1,319 -13,675 2.09
X=1, y=o 9/82-2/88 58,625 57; 45 2.45 1,029 -11,425 2.06
X=1, y=o 2/88-7/95 70,600 93; 35 2.81 -27,125 1.54

 

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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

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

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

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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