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November 12, 2005

It's About You

Market & Sector Review
This Week's Economic Reports

It's About You

As children, parents and teachers tell us whether or not we are doing well. When we get older our significant others offer praise when we met their expectations and punish us when we break the rules by going our own way. Society tends to reinforce looking to others for the standards that we should achieve. The media bombards us with images of success: Buy a sleek, new sports car and impress the neighbors. Wear the latest designer fashions and watch heads turn as you walk by. As a result of our surroundings, it becomes natural to ask yourself, "How well am I doing?" which in turn leads to asking, "How well 'should' I be doing?" When "should" and "must" enter the picture, it can place a lot of unnecessary pressure on us to perform. When the pressure is on, it is very common and we often usually choke under the strain. There's a danger when you look outward. You start to judge yourself. You start to think that you are doing well or poorly based on how others may see you. Instead look inward, and follow your own personal standards for where you want to go next.

Comparing ourselves to others is useless, time consuming, and counterproductive. Look inward for your own personal standards instead of outward in an effort to beat out the next guy. Each trader brings his or her own knowledge, personality, trading method, and tools to the trading arena. Through a coordinated integration of these various components, the trader builds up a set of individualized trading skills that produce lasting success. This integration doesn't happen over night, but though hard work and persistence. Over time, you make trade after trade, gaining key experiences along the way, until it all comes together in the end. You need to find one's own personal talents, accentuating your strengths and working around your limitations. Every trader is on his or her own path. For some people, the path is full of many curves and is quite long. For others, the path is straight and short. Follow your own path and accept the amount of effort and time it will take to reach your goals.

Studies of successful and creative people have shown that such people tend to work by their own standards. Even in competitive situations, creative people don't compare themselves to others. They look inward and let their internal standards guide them. They know that through persistence and determination, they will achieve success. They don't force it. They know that if they allow themselves to follow their passion, success will come naturally. If you take a similar approach to trading, you'll achieve lasting success.

Market & Sector Review

You may have heard from time to time that a market technician is really a frustrated fundamentalist. Not being able to figure out or trade on the fundamentals they turn to charts. How often have you read newsletters or heard commentary by a technician to only hear him or her quote fundamentals to justify their technical position? Because of the economy, because of the Fed, because of China or whatever, quite often I would imagine. Personally I am part both the technical combined with the fundamental. On John Hussman's site there is a good explanation of what he follows to forecast a recession. Well worth the read: Hussman on recession indicators!

As we continue to improve our data and this site it was decided this week to substitute linear regression analysis on the relative strength data along with the slope of the linear regression line. I in concert with Waveslider and others think it presents a better picture of what is going on. At the moment this data is available for stocks when you look through stock groups. It will be added to the Relative Strength Tables of ETF's, Indices, and Groups probably over the weekend, certainly by Monday or Tuesday. You will also note an additional piece of data, not only the relative strength of stocks as measured by their industry group but also by their sector, or as you will see below their sub-sector. We will get into the why's in a moment. I as many of you utilize TC2005 as my data feed and hence the Media General groupings as that is supplied with the TC2005 data. Recently while doing some research both with the Dow Jones total market indices, and the New York Stock Exchange's Industry Classification Benchmark (ICB) something became apparent to me.

In addition to the above research I visited and researched a bit on Hemscott (owners of the Media General Groupings) and discovered that TC2005 has dropped one level from the Hemscott or Media General database (See chart below). Why is this important? Well it may or may not be depending upon the research you intend to do, but you need to be able to compare apples to apples and not apples to oranges. For now what we are calling sectors and when we compare stocks to sector averages we are really comparing stocks to sub-sectors and not broad sectors. There will be times when you really want to know how, for instance, your gold stock is trading in reference to all Basic Materials and not just the Metals and Mining sub-sector or the Gold Mining Metals Group that we are currently dealing with. For now our sector data will utilize the Metals and Mining sub-sector to compare all metals stocks to, in addition to their respective groups. We will be looking shortly at alternative data sources to see if they make more sense to us. What we have now will certainly be sufficient for the great majority of members.

This week I'd like to go over some of the changes in the data and what it means to you and perhaps how to interpret what you see and direct your attention to a particular area or stock. Last week we showed relative strength vs. the broad market and relative strength vs. the MG industry group. This week we will take a look at relative strength vs. sub-sector and vs. industry group. To keep everything together here is a link to last weeks letter 11/05 Newsletter to review those charts and the same charts this week with the different data. Let's see what we find, but first:

First let's tackle for those unfamiliar, what linear regression and linear regression slope is, so all can understand what we are doing here. A classic statistical problem is to try to determine the relationship between a random variable Y (Relative Strength Data - Scatter points), and an independent variable x (Time or in this case trading days). Linear regression attempts to explain this relationship with a straight line fit to the apparent scattered data. The slope quantifies the steepness of the line. It equals the change in Y (Relative Strength) for each unit change in X (Trading Days). It is expressed in the units of the Y-axis (Relative Strength) divided by the units of the X-axis (Trading Days). If the slope is positive, Y increases as X increases. If the slope is negative, Y decreases as X increases. The Y intercept is the Y value of the line when X equals zero. It defines the elevation of the line. If you need more about the math please visit: Graphpad.com -> Linear Regression it's really important stuff.

The data in the LR direction field or Slope (See Below) is not an angle per se like 50 degrees, but rather the rate of rise or decline expressed as a rate of change in the raw relative strength data on that trading day. Let me use slope in terms of price per bar of the stock for clarity. The raw slope essentially gives us the change in price per bar of the regression (best fit) line. If the slope is 1, then the regression line is rising at a rate of $1 per bar. Similarly, a slope of -0.25 would indicator that the line that best fits the last N bars of data is falling at the rate of $0.25 per bar. For now suffice it to say that if the number is positive (above zero) then the linear regression line is rising and if the number is negative (less than zero) then the linear regression line is declining. It may be easier to express this field as a simple + or - to indicate direction, we will play a little more. The data period used is 21-days or approximately 1 month's worth of trading data. I hope everyone is still with me, if not please visit the link above on Linear Regression and then come back.

First let us look at the New Relative Strength report, looking at the group discussed last week - Accident and Health Insurance or MG432, and as you will notice, at the same time the sub-sector Insurance or MG430.

The picture above is from the data as of Wednesday evening 11/9. Notice: two different relative strength figures, one against the stocks group in this case MG432 Accident and Health Insurance ->columns color coded green for ease of viewing, as well as against it's sub-sector in this case Insurance (MG430), color coded orange, as well as the individual stocks relative strength percentile ranking, color coded blue. Let's look at a chart of AFLAC (below) to see what this data is telling us and how we may use it to narrow our stock search. The data is expressed in the same manner as before except in reference to a linear regression line instead of a moving average. In essence 105 means that the relative strength figure is 5% above the linear regression line and a positive number in the Direction field indicates the linear regression line of relative strength is rising, Conversely 95 means the relative strength number is 5% below it's linear regression line and a negative number in the direction field indicates the linear regression line is declining.

Please remember this data is not there to confuse, or to make decisions for you, it is there to help you quickly and at a glance find the strong stocks in strong sectors and strong groups or the reverse if you are looking for shorts. Then you must go to the charts and/or fundamental data to make final decisions. The point we are trying to make, to help you cut down your research time, is to research first sectors, then groups, and finally stocks. It is usually a good idea, although there are always exceptions, to buy strong stocks in strong sectors and strong groups, not in weak sectors or weak groups. Currently there are 6,800 stocks in our database, but only 31 sectors, and 209 Industry groups. Instead of trying to search through 6,800, search through 31 instead, you'll find in time you'll greatly reduce the time you spend and you will also make better decisions.

Notice a few things on the above chart of Aflac (AFL). When comparing the relative strength to the moving average vs. relative strength to the linear regression line: Notice when compared to Accident and Health the linear regression line is already pointing lower, while the moving average appears just ready to turn down. In both cases as of this date the relative strength is under the moving average and the linear regression line, this will not always be the case. The next thing to notice is that AFL's relative strenght is rising when measured against the sub-sector Insurance and at the same time the relative strength is declining when measured against its group Accident and Health Insurance. If you wanted to be long in this sub-sector or even this group there are probably better choices at this point in time. Now let's look at the same picture but as of 5-trading days ago, in this case November 2, 2005.

Now notice that at that time AFL's relative strength was above both the moving average and the linear regression line, this time however the linear regression line is pointing higher against both the sub-sector Insurance and the group Accident and Health Care. The slope of the linear regression line is greater against the sub-sector than it is against the group. Notice also that against the sub-sector Insurance AFL's relative strength made a new high over the July high while against its group it is diverging negatively. So as of this date we can see that if you are looking at a trade in Accident and Health Insurance as above there are probably better, stronger choices. I do not want to take anything away from AFLAC here, it's a great company (love their commercials), but the objective of this exercise is to find the strongest stocks, at a point in time, within sub-sectors and groups.

Finally we look at the same chart only 21-trading days ago, in this case 10/11. Now notice that in the three month basing period, trading between 43 and 46 while the linear regression line against the sub-sector Insurance was flat, AFLAC began to outperform it's group Accident and Health Insurance, as shown by the linear regression line beginning to rise from falling and before the moving average turned higher. Previous to this point the linear regression line against both had been pointing lower, a great indication if you were interested in this sub-sector to buy AFLAC for a trade at this point in time.

I hope this helps explain the reasons for the shift to linear regression and linear regression slope and how one can use this data to find great trades. If the explanations are not to your understanding please let me know and we'll try again. If you spend some time practicing the use of this data, I promise that in a relatively short period of time you will become proficeint in quickly reviewing the data, pointing you to great stocks that will make you some great money. But it will take some practice -> Do it! We continue to research new ways to help traders and investors and will present them when we determine there to be value, such as linear regression analysis on relative strength.

Next Week Waveslider has graciously agreed to present (step by step) his top down approach to finding and timing great stocks utilizing the data we provide. I have already received it, now we have to decide on some charts to show for visual reference. It's an excellent piece don't miss it-> it's really great stuff!

This Week's Economic Reports

Have A Great Week!

Bill

Disclaimer: Trading in securities, of any type, may not be suitable for all individuals. The contents of this newsletter are not a solicitation to buy or sell securities. The opinions expressed are solely that of the author. You must do your own research, contact your own financial advisor for suitability of any investments. Data gathered is from sources believed to be reliable, but NO guarantee as to their accuracy is made.