Millard on Channel Analysis. Brian Millard
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Figure 2.1, the price has not yet returned to its levels at the beginning of the chart period.
It is interesting to see what a randomly created share price looks like when plotted. This is done by taking a starting value, such as 200p, and then randomly setting a value for the change over the following week. The change is added or subtracted from the previous day’s calculated closing price. Such a chart is shown in Figure 2.5. The price is random in the sense that it can move upwards or downwards from the previous value, but we have put a 10% limit on the movement in either direction. This is done to come as close as possible to real life, since we know by experience that prices do not move in huge jumps from day to day. The purists might argue that in doing this we have moved away from a completely random model, but this is not a significant restriction in terms of what we are trying to achieve.
Figure 2.5 A reconstructed chart of Guinness shares made by randomly calculating the change from the previous week. The starting value is 200p
There are many similarities between the random movement in Figure 2.5 and the movement of the Guinness share price in Figure 2.4 in the sense that underlying trends can be observed with random variations superimposed upon them. It could be argued that the only thing that really distinguishes the two types of chart is the much stronger upward trend observed in the Guinness share price, but that in general the chart could be that of any share. Chartists could draw trend lines and the like on this random chart just as on any other chart of a share price. While the similarities to share charts would lead to the conclusion that share price movement is totally random, simply looking at the chart in Figure 2.5 is not a rigorous mathematical test of random behaviour.
Fortunately for us, the model of share price movement that we put forward earlier in this chapter is a better reflection of how share prices move than is a model in which we take all price movement to be totally random. Even so, our model is not perfect, being only partly true. It is true that share prices contain random day-to-day and week-to-week movement, but what is not true is the statement that the start and end of a price trend is itself a random event. Share prices are essentially driven by these trends, but the beginning and end of a trend is not a totally random event. It is this fact that makes the methods used in this book workable, since if day-to-day price movement is random and the start and end of the trends are random, then the share price is totally unpredictable.
Without getting into the realms of probability theory, it is possible to demonstrate that while individual daily or weekly price changes can be accepted as having a great deal of random content, trends are much less random. For this purpose we can define a trend as being a succession of upward movements or downward movements on a daily or weekly basis.
The procedure is to take the Guinness share weekly price movements since 1983 and note all of the weekly changes. These are put into a pool. The same starting price of 54.5p on 7th January 1983, is used. The change over the following week is determined by randomly selecting from all of the changes which have now been put into the pool. From this change the following week’s price can of course be determined. The following week another change is taken from the pool. The procedure is repeated until a reconstructed price has been obtained for Guinness over the same period as the real price change occurred. Thus we have used the actual price changes which occurred in Guinness, but randomly changed the order in which they occurred. The result of this is shown in the chart in Figure 2.6. As with the previous random chart, there is nothing unusual about it, and it could be the chart of a real share price.
Since the chart has been reconstructed by randomly selecting price changes from the pool, then by using a computer, this process can be repeated as many times as required, with the result being different in each case.
Figure 2.6 The reconstructed weekly price movement in Guinness shares since 1983. From the same starting value of 54.5p, the order of weekly price changes has been randomly changed
The usefulness of this experiment lies not in the appearance of the charts themselves, but in a calculation of the number of times the price changes direction over the timescale used. In virtually every case, there are considerably more changes of direction in the reconstructed prices than in the real ones. Since there are fewer changes of direction in real prices, the sequences of upward or downward price movements must last longer. Thus there are more upward or downward trends in real prices, i.e. trends are more persistent in the real prices. Since the reconstructed prices have been generated by a totally random selection from the pool, this means that trends are subject to less random behaviour in share prices than would be predicted on the basis that the daily or weekly changes which go to make up the trends have a high random content. It is this increased persistence of trends that will enable us to make profits out of investment in shares.
Because of this increased persistence in the trends, and because of the fact that daily and weekly price movements, although having a high random content, do not have a 100% random content, then probably 70% of share price movement is not random, and is therefore predictable if the correct techniques are applied. The analysis of cycles in share price data, discussed in Chapter 6, also confirms this as a ball-park figure for nonrandom behaviour.
The technique of channel analysis, especially when used in conjunction with moving averages of various types, is able to extract most of this predictable movement from the share price data, thus giving the investor the most powerful prediction technique currently available.
We can predict the start and end of these price trends with a fair measure of success by adopting a realistic approach of developing “prediction boxes”. This means we do not say “the price will be 285p on 17th November 1997”. We do say “the price will enter the prediction area at the beginning of November where the downward trend will have an increasing probability of reversing direction, with the lowest price being in the range of 280p to 290p”. The difference between these two statements is the fact that in the first case we would be totally positive about a situation that it is impossible to be positive about, whereas in the second case we are taking into account the partially random nature of trends. Another important point is that the further into the future we try to predict, the greater will be the error involved in this prediction. The fact of the matter is that we do not need to know approximate price movements more than about three months ahead. This will be perfectly adequate for making substantial profits, as was discussed in the last chapter.
It is interesting to see how seriously some sections of the press take the idea of long-term prediction of share prices by some of the gurus of the industry. Just prior to the start of each new year the business sections of the quality newspapers always poll a number of analysts for their predictions of where the FTSE100 Index will be at the end of the year. Be assured this is not done as a little bit of Christmas fun, since both the columnist and the guru being polled seriously believe that this is a worthwhile exercise. They are saying between them that they know exactly what you out there will be doing on the investment scene in a year’s time! Just keep cuttings of these predictions and have your own bit of fun reading them in the future.
At some points in share price histories different trends will be featured particularly strongly, while at other times the price just seems to meander along with no apparent direction. Quite obviously, shares that move in the latter fashion will be useless to us as investors, since we will not be able to predict any future price movement. On the other hand, shares where the trends are readily observable offer the possibility of using predictive techniques in order to determine the best buying and selling times for those shares. Since there are so many shares quoted on the stock market, there will be no shortage of shares which fall into this category. We will show in this book that such is the diversity of shares that it will be possible to remain virtually fully invested, since when the time comes to sell one share, another will present itself as a good buying opportunity. It will not even be necessary to keep track of large numbers of shares. The 100 shares which comprise the FTSE100 Index, plus the shares which form the mid-250 Index, will provide plenty of opportunity. A further advantage to the investor in staying with these 350 shares is that the spread of