рефераты конспекты курсовые дипломные лекции шпоры

Реферат Курсовая Конспект

Data! Handle with Care!

Data! Handle with Care! - раздел Литература, Beyond Technical Analysis You Have Many Choices When You Select Data For Your System Testing. You Shoul...

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.

Choose your data vendor with care, since data vendors differ in accuracy, depth of coverage, and reporting conventions. For example, there can be differences in the opening price of a contract between data vendors. Another policy difference is how errors are detected and cor­rected. You want a vendor with "clean" data all around.

If you are testing futures contracts, use a continuous contract or the actual contracts with rollovers. Unlike a cash market index, futures data are not continuous: contracts are dormant, become active, and ex­pire. Hence, to produce a continuous, albeit "synthetic," data stream, different contracts must be combined in some consistent manner. You have two choices when you combine futures contracts. You can preserve the prices or price levels, at the cost of correctly preserving the ampli­tude of price movements, or, alternately, you can preserve the amplitude of price movements at the cost of adjusting prices. Continuous contracts that preserve amplitudes are preferred for testing. Each type of continu­ous contract will give slightly different numerical results.


Data! Handle with Care! 65

A good choice is using actual data with rollovers if the software al­lows it. Results from continuous contracts come closest to data with roll­overs, but they tend to underestimate the number of trades and hence the losses due to slippage and commissions. They also underestimate the difficulty with placing stops on rollover trades. For example, after roll­overs, you can get stopped out on a real trade, while the system trading the continuous contract continues to hold its position.

Other than type of data, you must also choose the amount of data. In general, the more data you can use, the better, because you can then test a model over a wide variety of market conditions. There is also a sta­tistical requirement, usually quoted as sufficient data to produce 30 or more trades over the test period. The idea here is simply that the more trades you have in a given sample, the better your estimate of the aver­age properties for the entire universe. Hence, you can use the average properties (such as average trade) to estimate how the system will do in the future.

Although 30 trades may not seem like a large number, you may have difficulty obtaining 30 trades with weekly data using certain trend-following models. Thirty trades is probably too small a number to fully eliminate any effects of the data used for the tests. Hence, more than 100 tests is preferable, if possible, and you can obtain sufficient numbers by combining tests over multiple markets and multiple time frames. Later in the book you will learn how to generate synthetic data to gen­erate a large sample of trades.

The point of this discussion is that different input data will give you different results. Besides, you cannot be certain that your trading will ever achieve those results because you do not actually trade the syn­thetic data. We now look at the results of testing a dual-moving average crossover system using 5-day and 50-day simple moving averages, an in­itial money management stop of $1,500, and $100 for slippage and com­missions.

Table 3.12 was created by Continuous Contractor™ software from Tech Tools, Inc. to show different types of continuous contracts for the Swiss franc. Over the same period, model performance was calculated using actual contracts with automatic rollover on the twenty-first day of the month prior to expiration. The cautionary tale here is that test re­sults vary widely with the type of data used.

Focus on the number of trades for the same entry and exit rules. There are 111 trades with the actual data, almost 37 percent more than the average number of trades created using continuous contracts. The extra trades result primarily from rolling over existing positions into the next active contract.


66 Foundations of System Design

Table 3.12 Comparison of test results with different types of continuous contracts

– Конец работы –

Эта тема принадлежит разделу:

Beyond Technical Analysis

На сайте allrefs.net читайте: "Beyond Technical Analysis"

Если Вам нужно дополнительный материал на эту тему, или Вы не нашли то, что искали, рекомендуем воспользоваться поиском по нашей базе работ: Data! Handle with Care!

Что будем делать с полученным материалом:

Если этот материал оказался полезным ля Вас, Вы можете сохранить его на свою страничку в социальных сетях:

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

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

Хотите получать на электронную почту самые свежие новости?
Education Insider Sample
Подпишитесь на Нашу рассылку
Наша политика приватности обеспечивает 100% безопасность и анонимность Ваших E-Mail
Реклама
Соответствующий теме материал
  • Похожее
  • Популярное
  • Облако тегов
  • Здесь
  • Временно
  • Пусто
Теги