The Van Tharp Institute

October 04, 2006 — Issue #291

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In this Issue:

Workshops

$700 Discount Expires Next Week  on 17 Steps and Exchange Traded Funds Workshops 

Feature Article

Biases and Developing Your Trading System, Part Three, by Van Tharp

Trading Education

Peak Performance for Traders and Investors

Trading Tip

A Review of Market Models— Why Cash Flow is King II, by D. R. Barton, Jr.

Listening In...

Money Management

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Feature

Tharp’s Thoughts

Judgmental “Heuristics” Or 
Biases and Developing Your Trading System, Part Three of Three

So far in this series, we have looked at biases regarding randomness, which is the tendency people have to seek patterns where none exist and to invent the existence of unjustified causal relationships. Because people attempt to understand and make order out of the market, they assume that the longer a trend continues, the more likely it will suddenly turn around. This manifests into the "gamblers fallacy," which is a very common trap that traders fall in to and lose money when they do.  And, last week we examined data reliability as it relates to the degree to which information reflects what is really happening. We focused on the representation bias, availability bias, anchoring bias, and hindsight bias.

Today we continue with four common misuses of sampling variability in relation to system development, and finish with some tips to help overcome all of these biases.

Sampling Variability. Most people misuse the basic concepts of sampling theory in making predictions and designing trading systems. The first principle, which is highly abused, is that you can make more accurate estimates of the true population probability from larger samples than from smaller samples.  In other words, you can get a much more accurate estimate of the reliability of a trading signal from a large sample than from a small sample.  In our earlier example, Jack said that his pattern predicted a higher market price 35% of the time. The accuracy of his estimate would be much better if it were based on 100 measures of the pattern than if it were based on 20 measures. Unfortunately, most people follow a bias called the law of small numbers. Once they observe a phenomenon occurring a few times, they believe they understand it and know its likelihood.

People tend to form their opinions based on a few cases, and fail to revise their opinions upon the receipt of new data to the extent that they should, based on probability theory. Traders tend to stick to their old opinions rather than updating them as new information becomes available. 

We call this the conservatism bias. This points out the importance of doing a thorough, objective testing of your market observations on a set of data that is different from the data in which you made the observation.

Traders want consistent information from various sources, such as three oscillators based upon the same data (which of course are likely to show similar results). However, this consistent information will lead to increased confidence, but not to increased accuracy of prediction.  

We call this the consistency of information bias. What it means is that traders are likely to add more indicators in order to get more consistent information so they can feel confident about it. But adding more indicators is not likely to give one more accurate information. This points out the importance of developing a simple, robust trading system.

A fourth major misuse of sampling variability is that people fail to understand that the amount of variability in a sample is positively related to the degree of randomness in the sample. Once you have observed a relationship in a set of data, it is no longer random with respect to that relationship. The more relationships you observe with respect to various parameters in the data, the less random the data is with respect to those parameters. Unfortunately, system developers frequently make this mistake when they use a sample of data to optimize a system and then test the system on the same data. Once a set of data has been used to optimize a system’s parameters, then it is not random with respect to those parameters.  As a result, when you use the same sample of data to test the system, you can expect it to do well in the test, but this has nothing to do with how it will work as a system trading real money. Data must be tested on a sample that is independent from the sample used to observe the original relationship.

How to overcome judgmental biases

You probably cannot totally overcome the effect of the various judgmental biases. One reason is that one of the most prevalent biases is the ego bias in which people decide, “Yes, I understand all of this, but it applies to other people, not to me. I’m a very special person and it doesn’t apply in my case.  Nevertheless, if you are willing to assume you are human and that these biases do apply to you, then you can take steps to minimize their impact.

Remember, your job as a trader is to find an edge in the markets. You must capitalize on that edge, so you will make money in the long run, while doing everything possible to preserve your capital in the short run. As a result, I strongly recommend that you spend a lot of time writing down your objectives and designing something to meet those objectives

What is an objective?

Your objective is your goal, your target. It is the thing that you want to attain or accomplish.

Objectives set the roadmap for the entire system development process. How would one know how to get someplace if they didn’t know where they were going first? It is easy enough to see that if one trader had an objective such as “I want a system that trades long-term stocks, that requires my attention only once each week and makes 20% per year” compared to a trader’s objective that was “I want to actively trade my mother’s retirement account for four hours each day, without holding overnight positions” then two completely different systems would be required. The objectives or goals are very different. There are endless configurations of objectives. The point is you need to specifically know what it is that you are trying to attain; and only then can you develop a trading system that will help you attain it. 

Observe the markets as an artist would. Be creative. Determine relationships in the market that occur over a wide variety of markets and market conditions. Remember, you are not trying to explain the markets, but just determine some market relationships you can capitalize upon. The more widespread the relationship—does it occur in different markets and different types of markets—the more likely you will be able to profit from it.

Be willing to be unique. Think about how you can best represent the price of the market. Notice relationships in the patterns of price movement that you can capitalize upon. Once you have observed some relationships, figure out how to measure them. If you can avoid common indicators, then you probably have a real edge.

Simple is probably better. Why? Because the more complex the relationship, the more likely it is to be unique to particular markets and the less likely it is to make you money.

Be sure you understand the edge the relationships you observe in your data give you. Do your observations make sense? How do they give you an edge? Also be sure that you can write down your observations in enough detail so you can recognize them as they occur and not just in hindsight.

Understand money management so you can capitalize on your observations. Trade according to a predetermined plan rather than your emotions.

Be sure to objectively test your observations on extensive market data that is different from the data you used to observe the relationships in the first place. Objective testing is very important because with subjective testing you will tend to see what you want to see. In other words, the market will confirm your expectations.

Many of the psychological issues described in this article are covered in my How to Develop a Winning Trading System that Fits You workshop and home study program.  These programs will help you clarify your objectives, and then show you how to design a trading system to meet those objectives. 

 

About Van Tharp: Trading coach, and author Dr. Van K. Tharp, is widely recognized for his best-selling book Trade Your Way to Financial Fre-edom and his outstanding Peak Performance Home Study program - a highly regarded classic that is suitable for all levels of traders and investors. You can learn more about Van Tharp at www.iitm.com.

Trading Education

 Van Tharp's How to Develop a Winning Trading System 
That Fits You Home Study Course

One of the biggest secrets of successful trading is trading a system that fits you.  In fact, Jack Schwager, after interviewing enough “market wizards” to write two books, concluded that the most important characteristic of all good traders was that they had found a system or methodology that was right for them.

When someone else develops a system for you, you don't know what biases they might have. Developing your own system allows for compatibility with your own beliefs, objectives, personality and edges. 

More Info About How You Can Develop Your Own Trading System...

 

Trading Tip 

A Review of Market Models:
Fundamental Analysis—
Why Cash Flow is King II

by

D.R. Barton

Last week we looked at the common reporting method of earning or earnings per share and contrasted that with my preferred tool of operating cash flow.

As a quick recap, earnings are more easily “tweaked” to show favorable quarter-to-quarter results.  Poor real performance can be hidden for a number of quarters and not show up in earnings because of the vagaries of accrual accounting.  With cash flow measures, such machinations are much more difficult.

Let’s look at three well known stocks and at the relationship between their earnings and cash flow from operations.

Let’s look for trends over the past four reported quarters and see if that has been reflected in the stock price:

 

Sep 2005

Dec 2005

Mar 2006

Jun 2006

XMSR Earnings

-134,018

-270,474

-151,370

-231,678

XMSR Cash Flow

-90,717

7,568

-161,134

-272,235

*All numbers in thousands.  Source: Yahoo Finance 

As you can see, XM Satellite Radio (XMSR) has had negative earnings that have bounced around a bit.  But cash flow from operations has gone from “bad” a year ago, to “worse” in the last reported quarter.  This huge cash hit and the continuing hemorrhaging of cash has really been reflected in the XMSR stock price, which has gone from $36 to below $10 (now trading $11.93).

Contrast the XMSR story with Google (GOOG).  Almost everyone still believes that GOOG is overvalued, yet it's share price will just not stay down despite repeated cautions by analysts and aggressive short selling.  Let's see why:

 

Sep 2005

Dec 2005

Mar 2006

Jun 2006

GOOG Earnings

381,182

372,208

592,291

721,077

GOOG Cash Flow

646,747

658,434

824,804

840,586

*All numbers in thousands.  Source: Yahoo Finance

Yes, Google’s earnings keep growing.  But GOOG just keeps consistently throwing off increasing amounts of cash.  And as long as they can do that, their stock price (current $414.73) will continue to support those high valuations.

Great Trading!

D. R. Barton, Jr. is the Chief Operating Officer and Risk Manager for the Directional Research and Trading hedge fund group. D. R. has been actively involved in trading, researching, and teaching in the markets since 1986.  D. R. has taught extensively in many investment areas including intra-day trading, swing trading, and cutting edge risk management techniques. 

His writing credits include co-authoring Safe Strategies for Fin-ancial Fre-edom and co-creator and contributing author on Fin-ancial Fre-edom Through  Electronic Day Trading.

D.R. presents the IITM Swing Trading Workshop and Professional Tactics for Day Traders Workshop. Each workshop is only held once each year. 

Listening in...  

From the MasterMind Trading Forum...

Special Report on Money Management 
Author: JJH


I have been studying Dr. Tharp's Special Report on Money Management and there is still one item in the "Percent Risk" model that I still don't fully understand. Maybe someone here could enlighten me a little bit. It states "If you traded this system with $1,000,000 and used a 1% risk, your bet sizes would be equivalent to trading the $100,000 account with 10% risk. Thus, Table 4 suggests that you probably should not trade this system unless you had at least $100,000....." I just don't see the connection. Unless you know the "R multiple" distribution of the trading system, I don't see how you could determine the account size necessary to trade the system with the data given in Table 4. I am trading a very small account right now, but my commissions, slippage, and R multiple distribution is such that I can weather the expected drawdowns and not be too concerned about wiping out my account. Maybe somebody can shed some light on this comment.


Reply To This Message 

Re: Special Report on Money Management 
Author: PMK 

I believe the key factors are the number of rejected trades and the number of margin calls. If you look at Table 4 you have to risk at least 2.5% (of the $1,000,000) per position to get zero rejected trades and less than 10% to get no margin calls.

If you need to risk at least 2.5% of a million dollar account then you are risking $25,000 per position (at the start) and the maximum drawdown of 29.1% approximates to 12 losers (which is approximately $300,000).

Therefore, my analysis of Table 4 would indicate that to trade this system properly would require $1,000,000 at 2.5% risk, with your maximum drawdown tolerance of about 30%. Not sure what the comparison to the $100,000 account refers to, or the $100,000 account minimum - maybe someone else knows?

Obviously if you are trading something that can scale down to zero (like FX trading) rather than the futures contracts examples where you have a minimum risk per contract based on your stop and you can only buy a minimum of 1 contract (i.e. fractional contracts aren't allowed), then there is no minimum account requirement for any system that uses a percentage risk model.

Remember however that as position-sizes scale down but some implementation costs do not, you can end up with a proportionally higher implementation cost per trade with smaller accounts. This can sometimes be a significant negative factor on the viability of trading a system with small size.

Paul King
Reply To This Message 


Re: Special Report on Money Management 
Author: Level7


I will take a wild guess at one meaning without looking at Table 4 or the article for system traders. The actual size of the two bets RISK the exact dollar amount. (10000) Assuming the same sequence of winners and losers, your psychology would likely get in the way though the actual outcome would be the same (except for the paragraph below). Could you still take the trade after 9 losses betting the remaining 10000?

PMK highlighted the more practical system trader aspects of the maximum probable expected number of losers and the drawdown characteristics. The minimum size account is related to that however, since the stock market distribution has fat tails and you test the past and not the future, there is always the risk that a fully tested and quantified system will still lose significant money in real life.

As a discretionary trader, I use testing under live conditions, much smaller bets, and continuous feedback to adjust my trading style. I stepped out of the market for 7 weeks when I didn't like the "feel" for example. Lately as I have gotten a very hot hand, I have increased my risk doing what is working and in the latest 3 weeks have nearly doubled my returns for this year. So by missing the down and changing styles at the right time, I can make significant gains when the time is right. 

Hope that helps.

Join in the discussions:

www.smarttraderblog.com

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Tharp Concepts 
Explained...

Psychology of Trading 

System Development 

Risk and R-Multiples 

Money Management / Position Sizing 

Expectancy 

Business Planning 

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