Beyond Technical Analysis

Beyond Technical Analysis

Beyond Technical Analysis:

How to Develop and Implement a Winning Trading System

Tushar S. Chande, PhD

John Wiley 61 Sons, Inc.New York • Chichester • Brisbane • Toronto • Singapore • Weinheim

This text is printed on acid-free paper. Copyright © 1997 by Tushar S. Chande. Published by John Wiley & Sons, Inc.

Data Scrambling is a trademark of Tushar S. Chande.

TradeStadon, System Writer Plus, and Power Editor are trademarks of

Omega Research, Inc.

Excel is a registered trademark of Microsoft Corporation.

Continuous Contractor is a trademark of TechTools, Inc.

Portfolio Analyzer is a trademark of Tom Berry.

All rights reserved. Printed simultaneously in Canada.

Reproduction or translation of any part of this work beyond that permitted by Section 107 or 108 of the 1976 United States Copyright Act without the permis­sion of the copyright holder is unlawful. Requests for permission or further infor­mation should be addressed to the Permissions Department of John Wiley & Sons.

This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold with the understanding that the publisher is not engaged in rendering legal, accounting, or other professional serv­ices. If legal advice or other expert assistance is required, the services of a compe­tent professional person should be sought.

Library of Congress Cataloging in Publicaton Data:

Chande, Tushar S., 1958-

Beyond technical analysis : how to develop & implement a winning trading system / Tushar S. Chande.

Includes index.

ISBN 0-471-16188-8 (cloth : alk. paper)

1. Investment analysis. I. Tide. II. Series. HG4529.C488 1997 332.6—dc20 96-34436

Printed in the United States of America 10 98765432

Contents

Preface xi

Acknowledgments xiii

Developing and Implementing

Trading Systems 1

Introduction 1

The Usual Disclaimer 3

What Is a Trading System? 3

Comparison: Discretionary versus Mechanical System Trader 4

Why Should You Use a Trading System? 5 Robust Trading Systems: TOPS COLA 6 How Do You Implement a Trading System? 7 Who Wins? Who Loses? 8 Beyond Technical Analysis 9

Principles of Trading System Design 11

Introduction 11

What Are Your Trading Beliefs? 12

Six Cardinal Rules 14

Rule 1: Positive Expectation 15

Rule 2: A Small Number of Rules 17

viii Contents

Rule 3: Robust Trading Rules 22 Rule 4: Trading Multiple Contracts 29

Rule 5: Risk Control, Money Management, and Portfolio Design 32

Rule 6: Fully Mechanical System 36 Summary 37

Foundations of System Design 39

Introduction 39

Diagnosing Market Trends 40

To Follow the Trend or Not? 44

To Optimize or Not to Optimize? 48

Initial Stop: Solution or Problem? 52

Does Your Design Control Risks? 60

Data! Handle with Care! 64

Choosing Orders for Entries and Exits 66

Understanding Summary of Test Results 67

What the Performance Summary Does Not Show 70

A Reality Check 71

Developing New Trading Systems 73

The 65sma-3cc Trend-Following System 75 Effect of Initial Money Management Stop 88 Adding Filter to the 65sma-3cc System 93 Adding Exit Rules to the… Channel Breakout-Pull Back Pattern 101 An ADX Burst Trend-Seeking System 111 A… Contentsix

Developing Trading System Variations 147

Introduction 147

Channel Breakout on Close with Trailing Stops 149

Channel Breakout on Close with Volatility Exit 152

Channel Breakout with 20-Tick Barrier 155

Channel Breakout System with Inside Volatility Barrier 159

Statistical Significance of Channel Breakout Variations 161

Two ADX Variations 165

The Pullback System 168

The Long Bomb — A Pattern-based System 173

Summary 177

Equity Curve Analysis 179

Introduction 179

Measuring the "Smoothness" of the Equity Curve 180

Effect of Exits and Portfolio Strategies on Equity Curves 186

Analysis of Monthly Equity Changes 194 Effect of Filtering on the Equity Curve 200 Summary 204

Ideas for Money Management 207

Introduction 207

The Risk of Ruin 208

Interaction: System Design and Money Management 212

Projecting Drawdowns 218

Changing Bet Size after Winning or Losing 221

Summary 224

x Contents

Data Scrambling 227

Introduction 227

What You Really Want to Know about Your System 227

Past Is Prolog: Sampling with Replacement 229

Data Scrambling: All the Synthetic Data You'll Ever Need 231

Testing a Volatility System on Synthetic Data 236 Summary 239

A System for Trading 241

Introduction 241 The Problem with Testing 242 Paper Trading: Pros and Cons 242 Do You Believe in Your System? 243 Time Is Your Ally 244 No Exceptions 245 Full Traceability 245

"Guaranteed" Entry into Major Trends 246 Starting Up 247 Risk Control 248 Do You Have a Plan? 248 How Will You Monitor Compliance? 249 Get It Off Your Chest! 249 Focus on Your Trading 250 Trading with Your Head and Heart 250 Summary 252

Selected Bibliography 253 Index 255 About the Disk 261

This is a book about designing, testing, and implementing trading sys­tems for the futures and equities markets. The book begins by develop­ing… The book is broadly divided into two parts. The first half deals with… This book goes beyond technical analysis—it bridges the gap be­tween analysis and trading. It provides a comprehensive…

Introduction

Эта книга показывает Вам, как создавать, проверять, и осуществить системы, которые удовлетворяют вашу индивидуальность. Вы разовьете не только… Эти книжные центры исключительно на творческом проекте системы, полном…  

РАЗВИТИЕ И ВНЕДРЕНИЕ ТОРГОВЫХ СИСТЕМ

1. Принципы проектирования торговой системы, которая охватывает шесть кардинальных правил 2. Основы проекта системы, который представляет десять главных проблем… 3. Развитие новых систем торговли, который подробно описывает семь новых систем

The Usual Disclaimer

What Is a Trading System?

The rules of a trading system can be implicit or explicit, simple or complex. A system can be as simple as "buy sweaters in summer," or… In practice, every trader uses a system. For most traders, a system could… It should be clear by now that there is no single universal trading system. Every trader adapts a "system"…

Comparison: Discretionary versus Mechanical System Trader

Exceptional traders are discretionary traders, and they can prob­ably outperform all mechanical system traders. Their biggest advantage is that they… Discretionary traders can make better use of market information other than… The goals of a mechanical system trader are to pick a time frame (for example, hourly, daily, weekly), identify the…

Discretionary Trader 100% Mechanical System Trader

must be specific, and cover every aspect of trading. For example, the rules must specify how to calculate the number of contracts to trade and what… Mechanical system traders are objective, use relatively few rules, and must… You can create different flavors of trading systems that use a small or limited amount of discretion. You. could, for…

Why Should You Use a Trading System?

The statistical edge is relevant to another statistical quantity called the probability of ruin. The smaller this number, the more likely you are,… 6 Developing and Implementing Trading Systems My biggest source of concern about these statistical numbers is they assume you will trade the system exactly as you…

Robust Trading Systems: TOPS COLA

How Do You Implement a Trading System? 7 system, which cuts losses immediately and lets profits run. This philoso­phy,… Two examples of robust systems are a moving-average cross-over system and a price-range breakout system. Both systems…

How Do You Implement a Trading System?

The system must clarify portfolio issues such as the number and type of markets suitable for this account. The trading system must also specify when… 8 Developing and Implementing Trading Systems A trade plan is at the heart of system implementation. The trade plan specifies entry, exit, and risk control rules…

Who Wins? Who Loses?

Stewart reported three mistakes made by these customers. (1) Speculators showed a clear tendency to cut profits short, while let­ting their losses… I should contrast this experience with the TOPS COLA philoso­phy discussed… You will win in the trading business if you have a specific trade plan that contains all the necessary details. You…

Beyond Technical Analysis

Chapter Principles of Trading System Design

Introduction

First, assess your trading beliefs—these beliefs are fundamental to your success and should be at the core of your trading system. You may have… The six major rules of system design are covered in this chapter in… 12 Principles of Trading System Design tern design.

What Are Your Trading Beliefs?

The simplest way to understand your trading beliefs is to list them. Table 2.1 presents a brief checklist to help you get started. You can expand the items in Table 2.1 to include many other items. For… You must ensure that your beliefs are consistent. For example, if you like fast action, you probably will not use…

Six Cardinal Rules

1. The trading system must have a positive expectation, so that it is "likely to be profitable." 2. The trading system must use a small number of rules, perhaps ten rules or… 3. The trading system must have robust parameter values, usable ^ over many different time periods and markets.

Rule 1: Positive Expectation

The terms "average trade" and "expectation" represent the same object, so they are freely interchanged in the following… Expectation($) = Average Trade($), Expectation($) = Net profit($)/(Tbtal… Expectation($) = [(Pwin) x (Average win($))] - (1 - Pwin) x (Average loss($))].

Rule 2: A Small Number of Rules

Consider two well-known trend-following systems. The common dual moving-average system has just two rules. One says to buy the up­side crossover,… You can contrast this approach with an expert system-based trading system that… The statistical theory of design of experiments says that even com­plex processes are controllable using five to seven…

SPZ5 Dally Close with OLS Line

CLOSE LR1

40 60 80 Days since 08/01/95

Figure 2.1 SScP-500 closing data with simple linear regression straight line.

Rule 2: A Small Number of Rules19

SPZ5 dally close with 5th order regression

Days since 08/01/95

Est Close = C0 + (C1 x D) Est Close=C0+(C1*D)+(C2*D2)+(C3*D3)+(C4*D4)+C5*D5)  

More rules need more data

2 4 8 12 16 24 32 48 64 96 128 Number of rules Figure 2.3 Adding rules reduced the number of trades generated over 10 years… Figure 2.4 shows that the profit initially increased as we added more rules. This means that the extra rules first act…

Rule 3: Robust Trading Rules

An example of a system with delayed long entries illustrates the use of nonrobust parameters. The entry rule is as follows: if the crossover between… Rule 3: Robust Trading Rules 23

MIDD follows same pattern as profits

Number of rules

today's high + 1 point on a buy stop. A $1,500 initial stop was used and $100 was charged for slippage and commissions. The results above are for an IMM (International Monetary Mar­ket) Japanese yen… Next consider the effect of nonrobust, curve-fitted rules, illustrated by the August 1995 N.Y. light crude oil futures…

Number of rules

The following trading rules were derived simply by visual inspec­tion of the price chart in an attempt to develop a curve-fitted system that picked… Rule 1: Buy tomorrow at highest 50-day high + 5 points on a buy stop (breakout… Rule 2: Sell tomorrow at low -2 x (h-1) - 5 points on a sell stop (downside range-expansion rule).

Effect of delayed entry on profits: 3/12 SMAXO

Delay (» of days) after crossover

The first rule is a typical breakout system entry rule, albeit for a breakout over prior 50-bar trading range. The second rule is a… The results of the testing are summarized in Table 2.3, page 27. The first… 26 Principles of Trading System Design

Here must be a Figure.

profitable trades. As many as 87 percent of all trades (20 out of 23) were profitable. A second clue was in the 14 consecutive profitable trades. A… This curve-fitted system was tested by using a continuous contract of crude… Interestingly, this system has its merits. When tested over 12 other markets to check if these rules were robust…

Rule 4: Trading Multiple Contracts

Multiple contracts also allow you to add a nonlinear element to your system design. This means the results of trading, say, five contracts using… A simple example illustrates these ideas. Assume that your account is so large… Consider a simple moving average crossover system using 5-day and 50-day simple moving averages. The trade day is one…

Rule 5: Risk Control, Money Management, and Portfolio Design

Given performance expectations and finite size of the trading ac­count, it is essential to maintain good risk control, sensible money man­agement,… Table 2.7 illustrates the effects of not using an initial money man­agement… As expected, the largest losing trade can be horrifying, and most real-world accounts would probably close before…

Comparison of equity curves: DM and SF

-DM -SF

 

Date

Figure 2.9 Swiss franc and deutsche mark equity curves are highly correlated at 83 percent.

Rule 5: Risk Control, Money Management, and Portfolio Design 35

contract each of SF and DM, but your profits would have been $63,850 trading two contracts of DM and $57,388 trading two contracts of SF.

Note one important difference between the two cases. Since the two markets may have negative correlation from time to time, the draw­down for both SF and DM together may be in between trading two con­tracts of just DM or SF. For example, the drawdown for SF and DM in this case was -$10,186 versus -$22,375 for two DM contracts and -$9,950 for two SF contracts. Hence, the benefits of trading correlated markets are relatively small. Thus, it may be better to trade uncorrelated or weakly correlated markets in the same portfolio.

The benefits of adding usually unrelated markets to a portfolio can be illustrated by an example of trading the Swiss franc (SF), cotton (CT) and 10-year Treasury note (TY) in a single account, using the same dual moving average system as above. The paper profits from trading three SF contracts add up to $86,801 versus $85,683 for SF plus TY and CT. The equity curve for the two combinations is shown in Figure 2.10. The smoothness of the two curves can be compared by using linear regres­sion analysis to calculate the standard error (SE) of the daily equity

Equity Curve: 3SF vs SF+TY+CT

Days (5/89-6/95) Figure 2.10 Adding 10-year T-note (TY) and cotton to the portfolio trading… 36 Principles of Trading System Design

Simulated "Jagged" equity curve

Time (months)

curve. The SE for trading three SF contracts in $6238, and the SE for SF and TY plus CT is just $4,902, a reduction of 21 percent. Thus, add­ing TY… The relevance of the standard error is illustrated in Figure 2.11, which shows… Diversification can be more than just adding markets. You can also trade multiple trading systems and multiple time…

Rule 6: Fully Mechanical System

Summary37 forecast what market conditions you will face in future and how you will react… If you can define how you make discretionary decisions, then these rules could be formalized and tested. The process…

Summary

This chapter also reviewed six major rules of the system design. A trading system with a positive expectation is likely to be profitable in the…    

Introduction

We will begin by asking the question: Do markets trend? The an­swer to the next big question, whether you should trade with the trend or against the… The chapter begins the discussion on risk control issues by address­ing… 40 Foundations of System Design

Diagnosing Market Trends

Longer-term strategies are likely to succeed in trending markets, and shorter-term strategies in ranging markets. As always, the market may not make… There are many different ways to determine if a market is trending. Clearly,… Diagnosing Market Trends 41

Percentage of Days Percentage of Days

ADX Rising, RAVI Rising, Market (1/1/89-6/30/95) ADX>20 RAVI > 3

gies are worth considering for system design. The next section examines whether you should use trend-following strategies over the long run.

To Follow the Trend or Not?

Table 3.2 shows test results for a stochastic-oscillator-based an­titrend trading system provided with System Writer Plus™ software from Omega… To Follow the Trend or Not?45 Table 3.2 Stochastic-oscillator antitrend…

Max­ imum Maximum

Paper Number Percent- Largest Biggest Consecu- Intraday

Profits of age of Winner Loser tive Drawdown

  end of the range, then oscillator values are below 20. We assume that the next… The system tested uses a 10-day period to calculate the so-called fast-K and fast-D moving averages. When the fast-K…

To Optimize or Not to Optimize?

The term "optimization" is used rather loosely here to include all the activities affecting selection of parameter values in a trading… The problem with system optimization is that past price patterns do not repeat… You must also resolve other conflicts. For example, you must choose the period you will use to optimize your trading…

20 31,238 -2,200 -1,538 1,863 650 25 28,275 -2,475 -3,112 -488 -2,300 30 24,175 338 -300 2,325 2,113 35 18,088 338 63 2,175 1,963 40 15,475 338 -525 2,625 4,000 45 7,950 338 -4,363 2,038 3,600 50 7,013 338 -4,363 -1,800 -238

50 Foundations of System Design

Table 3.7 Data showing that relative rankings from the past do not predict future relative ranks

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

We next test the hypothesis that if the optimization period were closer to the actual trading period, the predictions would be more reli­able.… Let us carry our argument one step forward. Because we do not capture any… Table 3.8 Data showing that bringing the optimization period closer to the trading period (11 /88-11 /89) does not…

Initial Stop: Solution or Problem?

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… money management, MAE, and volatility. Another issue involves whether you should place your stop loss or­der with your broker. Many traders will have a…

Day CHBOC with varying initial stop

Initial stop ($) Figure 3.3 Profit increases steadily and then levels off as the initial stop… Initial Stop: Solution or Problem? 55

Changes In MIDD for 20-day CHBOC on Coffee

Initial stop ($) Figure 3.4 As we loosen the initial stop, MIDD first increases and then stops… 56 Foundations of System Design

Number of trades for 20-day CHBOC on Coffee

Initial stop ($)

Figure 3.5 The number of trades drops and levels off as we loosen the initial stop.

Initial Stop: Solution or Problem? 57

Changes In percent profitable trades, 20-day CHBOC on Coffee

Figure 3.6 The proportion of profitable trades increases and levels off as we loosen the initial stop. tion (Figure 3.8, page 59) shows that a stop of $3,000 exceeds 98.3 per­cent… You can now use the cumulative frequency distribution to select a stop based on market volatility. An arbitrary stop…

Variation In biggest losing trade: 20-day CHBOC on Coffee

CM CM CO CO "tf T 1^ 10 <D tO f*- h-.

-1000

-2000

-7000

-8000

-9000

Initial stop ($)

Figure 3.7 The worst losing trade increases as we loosen the stop.

try to take the long-term view when you set your stops. If you use a con­stant stop based on system design, then use loose stops. If you set the stop differently for each trade, then you have probably mastered the fine art of placing stops.

The risk of being stopped out is highest near trade inception, as shown by the calculations in Table 3.11, page 60. This table shows the effect on the length of the average losing trade of using no stop, a $1,500 stop, and a variable stop. A simple 20-day CHBOC model, with no exits other than an initial money management stop, is used, allowing $100 for slippage and commissions. The tests were over a 6-year period commencing May 26, 1989, using continuous contracts.

The data in Table 3.11 show that inserting an initial money man­agement stop of $1,500 reduced the length of the average losing trade by approximately 40 percent to 17 days from 28 days. These calculations confirm that the risk of being stopped out is highest near trade incep­tion. The average winning trade was typically 2 to 3 times longer than the average losing trade.

Initial Stop: Solution or Problem? 59

Cumulative frequency distribution average 10-day daily range in coffee

250 750 1250 1750 2250 2750 3250 3750 4250 4750 5250 Range ($) Figure 3.8 The cumulative frequency distribution of the 10-day average daily… If you look more closely at Table 3.11, you will see that for some markets, such as gold, sugar, and soybeans, the…

Does Your Design Control Risks?

Does Your Design Control Risks? 61 A trailing stop is a popular method to control portfolio volatility and… An important type of risk arises from correlation among markets. You know that correlated markets move roughly…

Data! Handle with Care!

Choose your data vendor with care, since data vendors differ in accuracy, depth of coverage, and reporting conventions. For example, there can be… If you are testing futures contracts, use a continuous contract or the actual… Data! Handle with Care! 65

Number

Profit MIDD of Wins Win/Loss Data Type ($) ($) Trades (%) Ratio

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 20,350 -21,115 86 34 2.42

Choosing Orders for Entries and Exits

Timed-market orders on the open or the close are a good way to both exit and enter positions. Many traders recommend entering on the open, and… Remember that there can be divergences between what the testing software… Understanding Summary of Test Results 67

Understanding Summary of Test Results

The summary shown in Table 3.13 is for the British pound con­tinuous contract for the 65-day simple moving average, three consecu­tive closes… The summary is broken down into five blocks. The top-most block describes… The total net profit is the difference between the gross profit and gross loss. The gross profit is the sum of the…

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

What the Performance Summary Does Not Show

One simple ratio is the recovery factor (RF). RF is absolute value of the ratio of net profit to maximum intraday drawdown, and it measures how far… Another useful value is the adjusted gross profit, in which the larg­est… The summary also does not give a histogram of your trades. You may wish to export your data to a spreadsheet to look…

A Reality Check

72 Foundations of System Design curve-fitting. However, it is worth recognizing that the influence of… It is also important to recognize that past price patterns may not repeat in precisely the same way. Hence, because…

Introduction

1. A simple trend following system—the 65sma-3cc system. 2. A pattern-based system for long trades only—the CB-PB sys­tem. 3. A trend-seeking, strength-of-trend system—the ADX burst sys­tem.

The Assumptions behind Trend-Following Systems

1. Markets trend smoothly up and down, and trends last a long time. 2. A close beyond a moving average signals a trend change. 3. Markets do not have large countertrend price swings.

The 65sma-3cc Trend-Following System

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… There are many ways to make the decision that the trend has turned up. The… 76 Developing New Trading Systems

Frequency distribution of 65sma-3cc trades

 

0 0 0 0 0 0 Q Q Q 0 Q 0 Q 0 Q 0

in o m q in o i" q u) o u> o w> o in o

h- 5 cm in f^- o cm in cj p h- i/> cm Q f^ "3

<y <a- co cm ••- ••- ' ••- cQ cm co ^t in m <o

Bin width = $250

Figure 4.5 Histogram of all 2,400 trades for the 65sma-3cc trading system.

The 65sma-3cc Trend-Following System 83

65sma-3cc trades. A histogram of all 2,400 trades shows the distribution of trade profits and losses (see Figures 4.5 and 4.6). There are more large winners than large losers, and many small losers. Remember that these results were calculated without using an initial money manage­ment stop. Most of the trades are bunched between -$3,000 and $2,000, with the highest frequency near zero. There are few losing trades worse than -$5,000, balanced by even more trades with profits greater than $5,000. An initial money management stop will clean up the negative part of this histogram.

Thus, it should be obvious that most of the profits come from a relatively small number of trades. In Figure 4.6, 12.5 percent of the trades are seen to have closed-out profit greater than $3,000. Be aware that if you get out too soon, you are likely to miss one of 100 or so (4 percent) of the mega-trades that make trend-following worth the aggra­vation.

Many measurements follow what is called a standard normal distri­bution. For example, if you measured the diameter of ball bearings, the

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

1000 2000 -3000 -2000 -1000 Figure 4.6 A histogram of the 65sma-3cc system over a narrower range of prof­its and losses. Notice that only a small…

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

£ ^asssKS^sisgs's^fepssi" ^-T-T-T-OOOOOOOOOOOOO-'--'-

Frequency distribution of 65sma-3cc trades compared to a modified normal distribution

^-•-•^-T-OOOOOOOOOOOOOT-'- Z (standard deviations) Figure 4.8 A fitted normal distribution shows that the 65sma-3cc trade distri­bution has "fat" tails, and…

Maximum favorable excursion of 1,565 losing trades of 65sma-3cc system

s Maximum profit ($) Figure 4.9 A histogram of maximum profit in 1,565 losing trades over 20 years and 23 markets from the 65sma-3cc…

Maximum adverse excursion for 777 winning trades of 65sma-3cc system

500 -

n n n

§o o 10 0 r-- in CM CM

10 0 10 0 10

I-- 10 CM 0 1^

Maximum loss ($)

Figure 4.10 Analysis of 777 winning trades: maximum loss in trades that were closed out at a profit. This is also known as the maximum adverse excursion plot.

About 500 (64 percent) of the trades were immediately profitable, with a loss during the trade of less than -$250. Another 100 trades showed drawdowns of less than -$500.

Thus, almost 77 percent of the trades showed a loss of -$500 or less during their evolution. There were very few trades that showed losses greater than -$1,750 and then closed out at a profit. This suggests that we could set an initial stop at $1,000 and capture almost 88 percent of the winning trades. This is a realistic way to pick the point at which a mechanical initial money management stop could be placed.

The same information can be viewed as a cumulative frequency chart to see how many trades achieved a certain profit target (see Figure 4.11). This type of chart shows what proportion of trades had a maxi­mum favorable excursion of, say, $500. It shows, for example, that 50 percent of trades had reached a $1,000 profit target, and so on.

In summary, the 65sma-3cc system test over 20 years of data and 23 markets showed it is a robust and profitable system that makes money in trending periods. Since we tested the system without any initial

88 Developing New Trading Systems

Cumulative Frequency of winning trades, 65sma-3cc system

Figure 4.11 Cumulative frequency of maximum favorable excursion of 65sma-3cc system. Note that horizontal scale is not linear. money management stop, there were several trades with losses greater than…

Effect of Initial Money Management Stop

The 65sma-3cc Trend-Following System 89 However, we should insert another condition into the formulation of the model… Inserting an initial condition should have two effects. (1) It should reduce the maximum intraday drawdown, since some…

Number of trades Increases and levels off.

750 1000 1250 Initial money management stop ($) Figure 4.12 Effect of initial money mangement stop on number of profitable… We can get around this problem by using a volatility-based initial money management stop. For our calculations, we can…

Variation In profits and drawdown with volatility-based stop for US Bond market

S o -20000 -40000 -60000

-Profits •MIDD

 

Volatility-based initial money management stop

same period as Table 4.1. Other calculations (not shown) show that the largest winning trade is affected only a little by the initial stop, since… You should note some limits on how the initial money-manage­ment stop can be… The 65sma-3cc Trend-Following System 93

Profit and MIDD for LH as a function of initial MMS

Volatility-based initial MMS

In summary, adding an initial money-management stop is useful from a risk-control point of view because it reduces the largest losing trade and the…

Adding Filter to the 65sma-3cc System

94 Developing New Trading Systems

Largest losing trade increases as MMS Increases

Volatility based initial MMS for Sugar

also the short exit, and vice versa. At this stage, the goal of the filter is only to reduce some of the signals in a congestion area. You can design many types of filters. Here we use a momentum-based filter… You can also use Wilder's ADX (average directional index) as a fil­ter for trending or nontrending markets.…

Adding Exit Rules to the 65sma-3cc System

In the 65sma-3cc system, the approach of using entry rules as exit rules does catch long trends, but at the cost of wide swings in account equity.… As an alternative to the entry-triggers-exits approach, you can con­sider many… 100 Developing New Trading Systems

Channel Breakout-Pull Back Pattern

We begin with a few examples of how the CB-PB system works, and show the actual code used for the tests. Next, we test the basic CB-PB entry… The channel breakout-pull back pattern is for long trades only. The… 1. The market will begin an uptrend after the consolidation ends, because it has recently made a new 20-day high.

An ADX Burst Trend-Seeking System

Figure 4.23 shows the March 1993 U.S. T-bond contract trending upward nicely from December 1992 through March 1993. The indica­tor under the daily… ADX is closely related to double-smoothed absolute momentum, and hence will… During a strong trend, as markets make big daily moves in the di­rection of the trend, the daily ADX momentum can…

A Trend-Antitrend Trading System

The challenge in this type of system is to find a consistent basis to define when to trade with the trend and when to fade it. Markets will often… For this system, we will use the 18-day ADX to measure market trendiness, and… We must also decide how to enter the trade. For simplicity, we will enter on the open of the next trading day. We can…

Frequency Distribution of 1311 T-AT Trades

§OOOOOOOOOOOOQOQQQOQQ !BQinQ(Boii5esiBe!BeC>Qu5eiBQpS eiBi~-ScM!Si'»ScMin<Mol~-B5cMQr-.iotMo ^.tpin^-^-coN^T^ ' »- cMCMco'»S5m<oi-<o

Bin Size = $250

Figure 431 Frequency distribution of T-AT trades showing a spike at the $5,000 initial stop and at trades with profit greater than $8,000.

button for the 65sma-3cc system (see Figure 4.5). It also shows a spike near the $5,000 initial stop. Like the 65sma-3cc distribution, it also shows a spike for trades with big profits. Figure 4.32 shows this distribu­tion normalized and compared to a fitted normal distribution. It is im­mediately clear that the T-AT trade distribution has "fat" tails compared to the normal distribution. Thus, the probability of a trade far from the center is much greater than the corresponding normal distribution. The tail on the profits side is fatter than on the losing side, suggesting that the entries are working well. Observe how the initial stop cuts off losing trades. However, there is no such cutoff on the profit side, as seen by the spike at the right edge of the distribution. This is the TOPS COLA principle introduced in chapter 1 applied to a trading system in practice.

In summary, the T-AT system illustrates how to develop a system that automatically adjusts to market conditions. It differs from the 65sma-3cc system in that its initial stance is to take an antitrend posi­tion; the 65sma-3cc system always takes a position with the trend. A reversal condition switches the T-AT system from antitrend to a trend-

Gold-Bond Intermarket System123

T-AT Closed trades Frequency Distribution (N = 1311)

0.06

0.05

0.04

0.03

0.02

0.01

0.07

t^t-ooooooooo

Z score (standard deviations)

Figure 4.32 T-AT frequency distribution normalized and compared to a fitted normal distribution.

following mode. The objective reversal condition assures entry in the di­rection of a major trend, thus allowing you to take advantage of all mar­ket conditions.

Gold-Bond Intermarket System

124 Developing New Trading Systems and-effect relationships. Hence, they are often a good addition to your… Many analysts have recognized intermarket relationships, which imply some form of weak cause-and-effect relationship.…

A Pattern for Bottom-Fishing

A Pattern for Bottom-Fishing133 The S&P-500 futures contract can be used to illustrate a pattern-based… The 10- and 11-day dual crossover system lost $181,005 on paper, with 530 trades. Only 34 percent or 178 trades, were…

Equity Curve for SP#1: VarA = 4, VarB = 3, MMS = $2,000, Exit = 20th close

80000 5 60000 a- S

Time 1982-95

Figure4.38 Equity curve for bottom-fishing pattern (9/82-7/95) with X = 4 and Y = 3 (conservative trades) for SScP-500 data with rollovers. Initial money man­agement stop was $2,000 per contract.

136 Developing New Trading Systems

Equity Curve: SP#1, VarA = 1, VarB = 0, MMS = $2,000, Exit on 20th day close

120000 100000 80000 S .•5' 60000 it 40000 -

-20000

Time: 4/82-7/95

Figure 4.40 The bottom-fishing pattern with X = 4 and / = 3 picked off the… A Pattern for Bottom-Fishing137     •475.00 -470.00 ] ^ ^ …

Equity Curve: SP#1 A=4 B=3 MMS=$2000 Case! =exit on 20th close Case2 = $1000 profit + 5day trailing stop

-10000

Figure 4.42 Equity curve for case 1 and case 2.

The generalized bottom-fishing pattern was profitable on 11 of 17 markets, including deutsche mark, Eurodollar, gold, Japanese yen, coffee, orange juice, Swiss franc, S&P-500, silver, 10-year T-notes, and the U.S. bond market. Thus the pattern also seems to work on mar­kets that trend well or have good swing moves. The results are given in Table 4.21.

These data suggest that the bottom-fishing approach captures a ba­sic trading pattern in the markets. The long test period and the profits on a variety of markets indicate that the idea is robust. The difference in performance between markets seems to be the amplitude of the move­ment after forming the pattern.

An extension of the test of the bottom-fishing pattern to stocks ex­plores its performance over different time periods. Figures 4.43 (weekly) and 4.44 (monthly) illustrate how the generic bottom-fishing pattern works. Figure 4.43 has weekly data for Union Carbide showing how the pattern picked the bottoms in 1990 and 1991. The pattern also stayed long throughout the major uptrend. The pattern tests well with weekly data on stocks. Figure 4.44, page 140, has monthly data for Caterpillar

A Pattern for Bottom-Fishing139

Table 4.21 Results of testing the generic bottom-fishing pattern on other markets

Market	Profit (S)	Number of Trades	Percentage of Wins	Maximum Intraday Drawdown ($)	Profit Factor
British pound	-17,694			-6,403	0.92
Coffee	86,740			-62,251	1.36
Crude oil	-35,660			-38,000	1.43
Eurodollar	20,650			-5,825	1.71
Gold	7,510			-40,000	1.06
Heating oil	-19,687			-50,124	0.88
Japanese yen	98,513			-15,188	1.95
Live hogs	-17,853			-22,1 76	0.83
Orange juice	12,653			-11,978	1.16
Silver	121,970			-54,550	1.81
Soybeans	-1 7,869			-35,719	0.86
S&P-500	127,925			^3,065	1.64
Sugar	-23,660			-34,166	0.75
Swiss franc	64,450			-28,387	1.48

 

91 92 93 94 95 Figure 4.43 Example of generic bottom-fishing pattern on weekly stock data.

140 Developing New Trading Systems

9 90 91 92 93 94 95

Figure 4.44 Example of generic bottom-fishing pattern on monthly stock data.

Tractor. The bottom-fishing pattern responded to the 1992 bottom and stayed with the stock throughout the rally.

In summary, the bottom-fishing pattern-based system is a good ex­ample of a market-specific system. You can use it as a model to develop other pattern-based systems on the S&P-500 market. The pattern can be generalized successfully to other markets, including stocks. The bot­tom-fishing pattern also works across time periods such as daily, weekly, or monthly. Thus, the bottom-fishing pattern captures a fundamental pattern of price evolution.

Identifying Extraordinary Opportunities

Figure 4.45 of the September 1995, Japanese yen contract illus­trates such an extraordinary opportunity. If you had tripled your expo- Identifying Extraordinary Opportunities141 sure to the Japanese yen during these two awesome moves, you would have made an extra $40,000 with only moderate extra…