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6

Most people will agree that market fundamentals, such as earnings, sales, management, competition, and interest rates, are basic factors that will eventually determine the value of a company, and therefore the price of the stock of the company. It is certainly possible to analyze each of the fundamentals that will impact prices. In fact, traders who characterize themselves as fundamentalists carefully analyze each factor before making a buying or selling decision.

The technical trader takes a somewhat different approach to the buying or selling decision. With the fact in mind that all fundamental factors are eventually reflected in the prices of all commodities or stock issues, the technical trader, rather than painstakingly analyzing every bit of news that is available concerning a particular stock or commodity, works only with the price of the contract or issue in question.

In effect, technical analysis can be a rather lazy way to analyze the markets. Let the other guys do the grunt work of mulling over the data and deciding what effect it all may have on the price of the stock. Its a lot easier simply to mathematically analyze the markets reaction to fundamental news and take your positions accordingly.

In a sense, a price chart is nothing more than a graphical representation of all the human activity that takes place concerning the price of the stock or commodity in question. Thus the analysis of price patterns and calculations based on price movements are actually the application of mathematically calculated probabilities of the repetitive nature of human behavior.

Most will agree with the axiom "History repeats itself." In a sense, this is the basis for technical analysis since we are calculating the actual probability of certain events repeating themselves at regular intervals, thus creating trading opportunities for the astute technical trader.

Since price patterns are simply the representations of human behavior, as discussed earlier, and since people are basically creatures of habit, it is possible to mathematically project the result of this repetitive human behavior using the modern forms of technical analysis that are available to every trader today.

Thus we have established the premises for the usefulness of the strange-looking dots, lines, and squiggles placed on price charts by

various mathematical processes loosely grouped together and referred to as technical trading tools. They are effective simply because they are predicting the eventual behavior of the selected population of individuals who actually determine the value of the issue at hand by trading the stock or commodity.

EACH ISSUE HAS ITS OWN PERSONALITY

Just as different individuals have their own separate personalities, each stock issue or commodity contract will also tend to exhibit its own character as it relates to specific price pattern behavior. After all, since the price behavior of a stock is determined by the finite group of people who trade the particular issue, the issue in question will take on the personality traits of the same group of traders.

As an example, lets examine one very simple market parameter, range expansion, and observe how several stock issues respond differently to the same market event.

One of the most basic, simple day trading techniques is trading the breakout of the early-morning range. In this system, one first determines the range in the early part of the day and then places a buy stop slightly above the high of the early range and also places a sell stop slightly below the low of the early range. When the market moves out of the early-morning range you are automatically in the market in the direction of the breakout as your stops are filled. Profits from such a strategy are usually taken at a specific target. The price objective at which the target is placed can be a specific dollar or point amount. Some traders also use a percentage of the previous days range as a target objective for this type of trade. Others may prefer to take a longer-term approach either by holding the position to the end of the day or possibly by keeping the trade overnight.

Think about our early-morning range as we have defined it. What is the probability that this range will also be the range at the end of the trading session? Most will agree that this is a rather remote possibility in most cases. With the possible exception of a stock that makes its big run up or down on market-moving news early in the day, most daily ranges are established in stages throughout the trading day as successive new daily highs or lows are made by normal market activity.

The theory here is that the probability is quite high that the

range developed very early in the trading day will not be the final range of the day for the stock or commodity we happen to be trading. Secondly, we are expecting, after the early range is established, that any range expansion will occur on only one side of the market. In this instance, the opposite side of the early-morning trading range will be in place for the remainder of the day. In other words, the system capitalizes on the fact that the high or low of the day is established early in the day and the breakout of this early range in one direction or the other will be consistently profitable.

The obvious trick here is to determine at what point in time the stock or commodity has established either the high or the low for the day. It is this "personality trait," the specific time at which we have the greatest chance of determining the final placement of the daily high or low, that we will examine in order to demonstrate the different behaviors of certain stock issues.

I have programmed a simple system based on early range expansion that I use at seminars and on my web site to demonstrate the operation of several self-adaptive programming techniques. I have used this system to analyze several stock issues to find the optimal time at which the high or low is to be determined to achieve the most profitable results for this simple theory. Those results are listed in Table 3.1. The number after each stock symbol represents a time at which the issue in question will have the highest probability of having established either the high or low for the day. Simply add this time, in minutes, to the time of the opening of the market. For example, the table suggests that only 15 minutes into the market day one could be reasonably confident that either the high or the low of the day for AFFX, AMAT, and AMGN has been established. At the other extreme, this table suggests that the same range determination for NOK should not be calculated until 90 minutes have elapsed since the opening of the market.

Note the wide variation in response times to our simple demonstration system in the table. This is a rather typical response that is found when the behavior of a group of issues is measured against a set market parameter. Analysis of the same group of stocks using many of the same routines we will examine later in this book will also return the same wide variation of results. Although we have measured only one "personality trait" of a selected group of issues, the data here is sufficient to demonstrate adequately the existence of a wide variety of "personalities" across a group of stocks.

Table 3.1 Time after the Open for Probable Daily High or Low for Each Issue

 AFFX DCLK HGSI AMAT AD 1 NTAP AMGN QLGC DISH SEBL YHOO QCOM IMNX SUNW CMVT COST WCOM EXDS MLNM BGEN VIGN TERN VRSN CHKP ADBE PMCS VTSS rrwo BRCM BRCD LVLT s MEDI PSIX INKT EBAY INTC RMBS ALTR NXTL JDSU CTXS

Although the tables data is included specifically to demonstrate the existence of wide variations in response to a single market factor, the implications of the presence of this phenomenon in the market have much wider ramifications to the systematic day trader.

Later in this book, in the Data Appendix, you will encounter a number of statistical tables that detail the times at which various stock issues actually break out of their respective early ranges. These tables also contain data referring to the number of times such breakouts are on the high or low side of the market and how far the average move is on each side of the breakout. Also, the tables will reveal the percentage of days from each issue during which there is no breakout of the early range and the percentage of days that break out on both sides of the early range. A program designed to screen a database and search for various tendencies created the material in the tables found in the Data Appendix. Please do not conflict the numbers in these later tables with the ones in Table 3.1. The table in this chapter reflects the time at which the issue in question will have the highest probability of having established either the high or the low for the day, not the eventual breakout that may or may not occur. The table in this chapter is an output of an automated day trading program utilizing self-adaptive parallel functions that looks at the market a bit differently than the

scanning program mentioned. The table here is presented simply as a demonstration of how various issues will respond quite differently when measured against an identical standard. These numbers are not meant to be used to create a day trading system. The information in later chapters and the numbers found in the Data Appendix are included to aid readers in the development of a highly accurate day trading system designed around each traders specific trading style.

All system traders should be aware of the fact that not all issues will respond to their day trading strategies in the same fashion, as demonstrated. Most system traders will develop their individual trading styles based on observation of the price behavior of a relatively small number of issues or commodity contracts. The temptation is certainly present, after the strategy is developed and tested, to trade a larger portfolio with the same system. With this table of results in mind, it would certainly be advisable to test your system thoroughly against all issues on which you wish to trade. The traders graveyard is littered with the remains of those who blindly assumed that their strategies could be applied with equal validity across a large portfolio after being tested on only a few selected issues.

Lets briefly examine some of the reasons that these demonstrated personality differences exist among most stock issues and commodity contracts.

An exchange-listed stock derives its personality from the specialist on the floor who directs the order flow for any specific issue. These issues therefore will be more consistent in their market behavior since one person has considerable influence on the trading of the stock.

On the other hand, stocks that are primarily traded through electronic means such as ECNs (electronic communication networks) may have multiple market makers dominating the trading of a particular issue at different times throughout the trading session. It naturally follows that these issues will have greater fluctuations in their trading patterns and thus display a more dynamic personality with respect to their chart patterns that are displayed.

PROBABILITIES

Recall those advanced math courses in high school where we all had to calculate those boring probability equations? Remember how we

could predict the likelihood of rolling a pair of sixes with a pair of dice? What is the probability of dealing three aces in a row from a standard deck of cards? Youll recall that it is mathematically possible to make these predictions on a consistent basis. In all actuality, technical analysis of market activity is nothing more than the calculation of the probability of a defined series of events repeating itself time and again.

Exhaustion points that regularly occur at cycle tops and bottoms are good examples of these probability-type calculations.