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Profits of age of Winner Loser tive Drawdown

Profits of age of Winner Loser tive Drawdown - раздел Литература, Beyond Technical Analysis ($) Trades Winners ($) ($) Losers ($) ...

($) Trades Winners ($) ($) Losers ($)

Coffee 1,837 27,065 -11,215 ^4,931
Cotton -98,725 4,955 -2,800 -102,205
Crude oil, -61,940 5,210 -7,850 -63,180
light                            
Gold, -29,830 2,630 -2,920 -31,150
Comex                            
Japanese -47,713 8,633 -2,762 -60,81 3
yen                            
Swiss franc -55,350 9,175 -3,225 -63,51 3
U.S. Bond -49,313 4,400 -1,694 -61,469

 

end of the range, then oscillator values are below 20. We assume that the next move will take prices toward the top of the range. The "range" be­tween the .r-day high and low changes continuously. Hence, this oscilla­tor cannot predict the amplitude of the next move.

The system tested uses a 10-day period to calculate the so-called fast-K and fast-D moving averages. When the fast-K is above the fast-D line, the system buys on the open and vice versa. The System Writer Plus™ software guide gives the exact method for the calculations.

This example uses continuous contracts for seven unrelated mar­kets, allows $100 for slippage and commissions, and uses a $1,500 initial money management stop. The test period was from May 26, 1989, through June 30, 1995. This simple system was a net loser over these markets. It also had substantial drawdowns, largely due to the many suc­cessive losing trades. Note the large number of trades and the relatively low proportion of winners.

The main implication of these calculations is that although markets may trend for short periods only, the profits during trending periods can far exceed the profits during trading ranges. The reason for this is that the amplitude of price moves during trends is many times the amplitude during trading ranges.

This example assumes that you pay the "discounted" trading com­missions offered on the street. If your trading commissions are very low or negligible, then the antitrend strategy, with its high trading fre­quency, takes on a different dimension.


46 Foundations of System Design

Table 3.3 Impact of trading costs on profitability of antitrend trading strategies (dollars)

Market Paper Profit $100SScC Paper Profit noS&C
Coffee 1,837 29,438
Cotton -98,725 -69,125
Crude oil, light -61,940 -31,840
Gold, Comex -29,830 -A,230
Japanese yen ^7,713 -16,813
Swiss franc -55,350 -26,850
U.S. bond -t9,313 -18,313

 

Table 3.3 compares paper profits with and without slippage and commissions (S&C). The difference in profitability is striking. The sto­chastic oscillator system performance improved significantly with low commissions. This result indicates that an antitrend strategy would not be attractive if you had to pay high commissions.

There are a number of "antitrend" strategies. Table 3.4 presents another set of calculations using a different trading strategy to illustrate this point. The moving average crossover (MAXO) system is the sim­plest trend-following strategy, but it can also be used as an antitrend strategy. For example, if the shorter moving average crosses over the longer moving average, you can go short in an antitrend strategy. Of course, this "upside" crossover would be a signal to buy long in a trend-following strategy.

Table 3.4 Comparison of trading systems using 5-day and 20-day simple MAXO tests, 5/89-6/95 (dollars)

Antitrend Trading MAXO Trend-Following MAXO
    Paper Profit, $100SStC Maximum Intraday Drawdown Paper Profit, $100 S&C Maximum Intraday Drawdown
Coffee ^2,719 -59,344 59,241 -17,216
Cotton -14,670 -36,895 -6,845 -18,010
Crude oil, light 2,580 -21,500 -30,730 -35,460
Gold, Comex -12,740 -21,780 -8,560 -12,950
Japanese yen -34,650 -58,540 -9,025 -22,738
Swiss franc -7,812 -45,688 -23,500 -40,175
U.S. bond -28,119 -33,019 -9,643 -23,568
Average -19,733 -39,538 -4,152 -24,302

 


To Follow the Trend or Not?47

Here we have arbitrarily picked 5-day and 20-day moving averages as examples of short- to intermediate-term averages. The test period was from May 26, 1989, through June 30, 1995, with $100 for slippage and commissions and a $1,500 initial stop. The antitrend strategy was a net loser on average, with significant potential for intraday drawdowns. The trend-following strategy cut the average loss by 79 percent and draw­down is lower by 39 percent—a better situation on both counts.

Table 3.5 presents another combination: the moving average an­titrend and trend-following strategies with 7-day and 50-day simple moving averages. This combination is good for no-nonsense trend fol­lowing. The assumptions are the same as before: $100 for slippage and commissions and a $1,500 initial stop with the calculations performed from May 26, 1989, through June 30, 1995.

Under antitrend trading, the 7/50-day SMA combination was also a net loser. On the other hand, it was a net winner with trend following, with profitability across all seven markets. The trend-following strategy had approximately one-fifth the drawdowns of the antitrend approach. Thus, the trend-following approach was the better choice on both counts.

These calculations show that a trend-following strategy is probably the better choice for the average position trader. However, the antitrend strategy may be attractive if you have low commission costs and little slippage.

The example tests in this chapter used arbitrary combinations of moving averages. However, you can test your system over historical data

Table 3.5 Comparison of performance for 7-day and 50-day simple MAXO tests, 5/89-6/95 (dollars)

Antitrend Trading MAXO Trend-Following MAXO
    Paper Profit $100 S&C Maximum Intraday Drawdown Paper Profit $100 SScC Maximum Intraday Drawdown
Coffee -22,716 -68,534 38,689 -27,615
Cotton -44,375 -52,275 23,155 -9,795
Crude oil, light ^t3,440 -47,570 20,430 -5,020
Gold, Comex -14,540 -20,980 4,560 -5,730
Japanese yen -39,663 -71,225 23,662 -23,075
Swiss franc -49,325 -70,800 32,988 -13,163
U.S. bond -34,606 -36,756 18,131 -14,619
Average -37,658 -49,934 20,488 -11,900

 


48 Foundations of System Design

to find other combinations with better performance. Optimization is the process of finding the "best" performing variable set on historical data. The next section examines whether optimization is a good design strategy.

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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

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

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

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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