I want to emphasize that perhaps the best strategy of all, for most people, is to simply apply the stock picking criteria in the past chapters, then buy and hold their selected stocks without ever selling them. Of course, you will need to select a substantial number of stocks to achieve an adequate level of diversification, but for results versus risk and time expended, it is hard to beat a buy-and-hold strategy. I recommend the simple buy-and-hold approach for the vast majority of people.

This chapter, and following chapters, are written only for those who are willing to take more risk of loss and expend more time in order to have a chance at winning big. However, keep in mind that you can always lose big whenever you employ any type of trading strategy!

In the previous chapter, we studied the worst of all trading strategies. It systematically snowballs your losses and jettisons your best stocks just as they start to become winners. Practiced consistently, the scale-trading approach is a surefire ticket to the soup line. The Reverse Scale Strategy, on the other hand, is developed by inverting the Scale Trading approach, and in the right market conditions may deliver large profits over time. Before we get into the details of the Reverse Scale Strategy, though, let's take a side trip to examine how all portfolios inevitably act over time.

The One Inevitable Characteristic of All Stock Portfolios
To begin with, let's think about a portfolio of ten stocks held over a period of time, say, five years. For now, let's not worry about which stocks are in the portfolio. The only thing we know about the portfolio is that it is composed of ten stocks. Now let me ask the question, "what can we predict about the portfolio five years from now?" In other words, what is certain to happen over the next five years?

First of all we can't predict what the total return on the portfolio will be, because that will depend on market conditions over the next five years, and also will depend on how well our ten companies individually perform over that period of time. Stocks have historically returned on average about 9% per year, but over any five-year period this can range from a negative number to a very positive number of 20% per year or more. It also varies considerably from company to company. So obviously we can't accurately predict what each individual stock in the portfolio will return, either.

It may be disheartening to you to realize how little we actually can foretell about the future performance of our portfolio. However there is only one thing that we can fairly confidently predict about any basket of stocks, and it is this:

At the end of the five year holding period, some stocks in the portfolio will have performed vastly better than others.

For the sake of reference, I will call this the Variability Concept.

This is not exactly a revelation. We could expect that one or two of the stocks will have tremendously outperformed the market averages, which might mean a move of two, four, or maybe even ten or more times our entry price, depending on market conditions. Some will have proved to be dogs, perhaps declining marginally, or in the extreme case, gone out of business in the meantime. A large portion of the stocks will have performed pretty much in line with the market. If you've chosen your stocks randomly, there's also a very good chance that your ten-stock portfolio will have returned something close to what the market averages returned over the five years. Since every portfolio of stocks contains future winners and future losers, we are left with this: The challenge of investing is to make sure that when you get to the end of your holding period, you find that most of your money was invested in the stocks which performed the best, and relatively little was invested in the stocks which did the worst.

To realize how this concept can be useful to us, we also have to add to it another fact we've already discussed in great length about the stock market:

Stocks make large moves in continuous trends which almost always take months or years to develop.

Let's call this the Trend Concept.

Large price movements are gradual incremental events, not all-at-once step functions. They are evolutionary, not revolutionary. Whether the move is up or down, a really big move does not normally happen overnight unless there is a merger announcement, bankruptcy filing, or something of that sort. Even then, the actual announcement has often been preceded by an uptrend (in the case of a pending buyout) or a downtrend (in the case of a pending bankruptcy filing). The reason for this is that there are always some folks who know about these pending announcements before they happen, even if they are not supposed to know. Their buying or selling leading up to the announcement moves the stock while the public is still clueless as to why it is moving.

Putting the Trend and Variability concepts together, it becomes apparent that there will most likely be a wide gap in the returns between the best-performing and worst-performing stock in your ten-stock portfolio. It is equally apparent that this condition will develop slowly, with the gap in total returns between the best and worst stock growing steadily as the holding period lengthens. The union of these two inevitable events should lead logically to this conclusion:

If only we could find a way to gradually allocate our investment dollars to the best-performing stocks in our portfolio as they are becoming the best-performing stocks, then we'd have a tremendous chance of greatly increasing our investment returns above and beyond what would be achieved by simply choosing those same ten stocks and holding them in equal dollar amounts.

Reversing the Scale Trading Example
What we need, then, is to develop a system that will accomplish this allocation of capital to our strongest and best-performing stocks. As it turns out, we can do this by simply reversing the scale trading approach learned about in the last chapter. So in other words, we add equal dollar amounts to our stock positions as they move up in price, instead of when they move down in price. This is what I call the Reverse Scale Strategy. In the rest of this chapter, you will see how the mathematics of this approach work greatly in our favor.

Since one picture is worth a thousand words, take a look at the following chart. It is a price chart of Wireless Telecom, a stock which I began buying in early 1994, and still own as of this writing. I purchased the stock after it had already more than doubled in value, at slightly above $2/share (marked by the arrow). I added an equal dollar position (not an equal number of shares) with every 50% increase in price from the previous purchase level, represented by the horizontal lines in the chart below. That is, each successive purchase was for less shares than the previous purchase.

Pursuing the Reverse Scale Strategy I purchased positions at approximately $2.07 (all prices are adjusted for stock splits which occurred during the stock's rise), $3.10, $4.65, $6.97, $10.44, and $15.64. The price has not yet reached $23.44 or I would have purchased an equal dollar amount there, too. For the sake of an example, let's say I put $2,000 into the stock at each of those price levels, and every time I did make a new purchase, I moved my stop-loss order (if you are not familiar with stop-loss orders, they are explained in Chapter 8) up to the price of the previous purchase. Hence, my sell point was constantly rising during this time, most recently at a price of $10.44. Obviously, I owned other stocks in mid-1994 when I first bought a position in Wireless Telecom, but at that time I had no idea this particular stock would increase as much as it did in value versus the other stocks. I didn't need to know, because my strategy guaranteed that if it made an exceptional move, I would have a disproportionate amount of money invested in it. As I said earlier in the book, it is best to avoid prediction altogether, and rather rely on a strategy which can guarantee a good allocation of your dollars.



If you followed the Scale Trading example as presented in the last chapter, you saw how no matter what happened, the scale-trader's poor strategy allocated most of his capital to the worst-performing stocks gradually, with a large loss being the inevitable result. Like a snowball rolling downhill, the tendency for a declining stock to keep on declining, in combination with the scale trader's foolish trading rules required the poor trader to buy more and more while his position became worth less and less. Once you have really grasped how foolish the scale trading strategy is, it becomes much easier to see how wise it is to follow the Reverse Scale Strategy. To give you a flavor for the advantages of adding to a position as it moves up in price, following is a brief contrast of Scale Trading versus the Reverse Scale Strategy:


Scale Trading

Reverse Scale Strategy

Positions added only if stock declines.

Positions added only if stock increases.

Your average cost per share is always above the current market price after second purchase.

Your average cost per share is always below the current market price after second purchase.

Sacrifices large long-term gains for small short-term gains.

Sacrifices small short-term gains in order to realize large long-term gains.

Unlimited potential for loss.

Unlimited potential for gain.

Makes no attempt to cut losses. Adds to losing positions.

Cuts losses. Does not add to losing positions.

In a portfolio, automatically allocates majority of capital to worst-performing issues.

In a portfolio, automatically allocates majority of capital to best-performing issues.


The Snowball Effect

To help you envision the principle of the Reverse Scale Strategy, I'd like to offer the following illustration. Imagine you are standing at the top of a large hill. You have made five snowballs, all equal in size, and you give each of them a equal push to start them rolling downhill. One of the snowballs starts out OK but doesn't get very far, as it hits a rock that was hiding below the surface of the snow, exploding the snowball into smithereens. Two others make it about halfway down the hill, but then stall out because they became large and happened to be on a part of the hill that was not as steep as some other areas. Still another makes it a bit further than those two, but then hits a wet area and gets bogged down. One of the snowballs, however, happens to have just the right type of snow and a nice steep incline, and its quick start, momentum, and after a while, sheer size make it unstoppable. It goes several times the distance of any of the other snowballs.

The analogy between snowball-rolling and a portfolio of stocks is a good one. Obviously, the snowball that rolls the farthest gets the biggest and picks up more snow gradually as it goes. The size of the snowball can represent either losses or gains, depending on whether you are using the Scale Trading approach (snowballing losses) or the Reverse Scale Strategy (snowballing gains). Really, both the Scale Trading approach and the Reverse Scale Strategy cause a snowballing effect. You have to choose which strategy you would prefer: One which snowballs losses or profits. Tough choice, huh?

With snowballs, as in the stock market, there are things you can control and things you cannot control about the stocks you are investing in. You can control how big you make each snowball initially, and you can control how much of a shove you give each. From then on, many of the factors are out of your control or unpredictable. Even though we can't predict which snowball will roll the farthest, the hill still gives more snow to the one that eventually does go the furthest, because it adds snow to it gradually as it progresses. Hence, the beauty of the Reverse Scale Strategy is that just as the hill and gravity make sure the snowball that goes the furthest gets the most snow, our strategy will make sure that the stock which advances the furthest gets most of our capital.

Trading Rules for the Reverse Scale Strategy - An Example.
To learn how to implement the Reverse Scale Strategy, let's run through an example for one single stock. Although we will be using the Reverse Scale Strategy in a portfolio of several or more stocks, it is much easier to illustrate the concept using just one stock.

First, we construct a chart similar to what the scale trader in the last chapter constructed, only our chart begins at the initial purchase price and goes up, each succeeding decision point being 50% higher than the previous one, (instead of 50% lower, as with scale trading). The trading rule is:

Invest an Additional Designated Number of Dollars at Each Price Level as That Level is Reached - and Only If It Is Reached.
As you can see, we will be adding an equal dollar amount at each price level. This dollar amount is the same as our initial position in dollars, but a reduced number of shares due to the higher price paid for each successive purchase. For a stock where our initial purchase was at $20 per share, our decision chart would look as follows (the initial entry position is highlighted):

Reverse Scale Strategy, 50% purchase increments (Chart No.1)

--

Decision Point
Price Level


Amount Invested
this Purchase *


Shares bought

Cumulative $ Invested

Cumulative Shares Owned

Current Value of Shares

Cumulative Cost per Share

Total $ Profit/(Loss)

Loss-cutting point

13 1/4

N/A

N/A

N/A

N/A

N/A

N/A

N/A

Initial entry point

20

$1,000

50

$1,000

50

$1,000

$20.00

$0

Decision point 1

30

$990

33

$1,990

83

$2,490

$23.98

$500

Decision point 2

45

$990

22

$2,980

105

$4,725

$28.38

$1,745

Decision point 3

67 1/2

$1,013

15

$3,993

120

$8,100

$33.27

$4,108

Decision point 4

101 1/4

$1,013

10

$5,005

130

$13,163

$38.50

$8,158

* Since shares can only be bought in increments of one, this number does not always equal $1,000 for each purchase, but the cost of the closest increment of one share that can be purchased with $1,000.

Again, each successive Decision Point is arrived at by multiplying the previous one by 1.5. So the first decision point is calculated by multiplying the $20 initial entry price by 1.5, which yields $30; $30 times 1.5 results in $45, and so on for as far as you need to go.

Our other trading rule is:

Whenever our stock increases to reach a decision point and then retreats all the way back to a previous decision point, we will sell out our entire position in the stock.

Why do we have this trading rule? Simply because if a stock retreats enough to make it all the way back to a previous decision point, then it's a good bet it's lost enough momentum that it will have a hard time becoming a market leader once again. In other words, its uptrend may be ending or about to go dormant for a long, long time. So, it's best to trade it in and start over with another more promising issue. As we have discussed in earlier chapters, we need to give a market-leading stock plenty of room for normal retreats off its highs in order to be able to ride the long trends when they develop. However, we have to draw the line at some point. Given that our decision points are 50% apart, the prospect of "whipsaw" losses or prematurely bailing out of a stock are limited with this approach.

To illustrate, let's assume we took our initial position at $20/share as indicated in Chart No.1. Over the next year, the stock increases in value gradually to $105/share, as graphically illustrated in Chart No.2. We would have picked up shares at $30, $45, $67 1/2, and $101 1/4, for a total of 130 shares owned, referring once again to Chart No.1. Because the stock reached the Decision Point No.4 at 101 1/4, our sell point would have ratcheted up to 67 1/2.

Chart No.2:



Let's say then that the stock retreats back to the $67 range. Since the stock has at that point violated our sell Decision Point No.3 by falling below $67 1/2, we unhesitatingly enter a market order to sell the entire 130 shares. For the sake of simplicity, let's assume we were able to sell our shares at exactly $67 1/2. We could then compute our profit from the trade as follows:

Summary of Purchases and Sale (Chart No.3):

Purchase No.

Shares Purchased

Price per Share

Total Cost

Commission

Net Cost

Purchase No.1

50

$20

$1000

$25

$1025

Purchase No.2

33

$30

$990

$25

$1015

Purchase No.3

22

$45

$990

$25

$1015

Purchase No.4

15

$67 1/2

$1013

$25

$1038

Purchase No.5

10

$101 1/4

$1013

$25

$1038

Total cost of all the purchases: $5,131.

Total shares purchased: 130

Proceeds from 130 shares sold at $67 1/2 = $8,775. Minus $ 25 commission = $8,750.

Net Profit = $8,750 minus $5,131 or $3,619.

Just to illustrate the previously made point about the Reverse Scale Strategy making it hard to get shaken out of a stock prematurely, please note what our sell decision point would have been had the price topped out at only $100 instead of at 101 1/4 or higher. In that case, the price would have had to retreat from $100 all the way down to $45/share in order to trigger a sellout of the position, since it never reached the $101 1/4 level and therefore $67 1/2 never became our sellout point. Now, I know emotionally it might seem disheartening to you to have to sit idly by while a stock sinks from a peak of $100 down to $45. But believe me, there are plenty of times where this discipline of being able to ride out the occasional temporary steep correction will be the very thing that allows you to sometimes go on to make a huge gain of 1,000% or more. Keep in mind that gains of 1,000% happen much more often than you'd think if you are using the stock-picking criteria presented in Chapter 4. It is also much easier to ride a stock down temporarily if it is only one of many stocks you own, so make sure you diversify!



For the sake of covering all the bases in the last example, what would have happened if our stock had turned out to be a loser instead of a winner? If after we took our initial position at $20 per share, the stock declined to 13 1/4 or lower ($20 divided by 1.5), we would have sold the initial position and started looking for a new stock to start over with. We would have incurred a loss of $337.50 plus two $25.00 commissions, for a total loss of $387.50. We then would go prospecting for a new stock to trade. Remember, we do not want to keep gunning for the same stock once we've been bumped out of it by our system.

Risk and Reward
While you might or might not be impressed with a profit of $3,619, keep in mind that we never exposed ourselves to a loss of more than $400 or so in this trade. So, the potential for profit here is unlimited (limited only by the performance of the stock being traded), while the potential for loss is quite limited.

The real power of the Reverse Scale Strategy lies in using it to harness the power of margin borrowing. So in the Chapter 8 we will explore how the Reverse Scale Strategy can go hand in glove with the controlled use of borrowing to enhance the return on your portfolio. Chapters 9 and 10 will cover implementation details and trading rules. When we are done we will have the perfect blend of limited loss, limited personal cash investment, and unlimited profit potential. However, keep in mind that anytime you use margin borrowing to buy stocks, you are taking a larger risk of loss than if you didn't. There is still no free lunch. (To learn more, see Margin Trading.)

Five Minute Investing is Copyright © 1995 by Braden Glett,
who has given written consent to distribute on Investopedia.com. Check out Braden Glett's new book - Stock Market Stratagem: Loss Control and Portfolio

Next: Five Minute Investing: Margin Power »


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