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136

understand the application of these techniques, it is necessary to identifj the following features: 5

1. The Daily HiLo Activator (in this case, it is the moving average of the daily highs) is presented as a stepped line. The 4 dajs of interest are maiiced by the letters A B, C, and D and appear on both (a) and (b) of Figure 19-2.

2. The 50-minute HiLo Artivator (seen in Figure 19-2b) is the moving average of the 50-minute highs, used as a Buy Stop, or the moving average of the 50-minute lows, used as a Sell Stop.

3. The 10-minute Gann swings, based on 10-minute bars (in Figure 19-2b). The solid line shows when the Gann swing represents an upward trend, and the broken line when it shows a downtrend.

The interpretation of these techniques relies on the faster response provided by the 10-minute bars, combined with the direction given by the longer time frames.

1. Based on the 10-minute Gann swings, the trend tumed from up to down at about 12 1-00. while the daily Gann swings place the trend change much later, near 120-00.

2. The slope of the daily Gann swing, measured from point X to point Y on both charts, was down, defining the dominant trend. Short trades can be entered using the downtrend of the 10-minute time frame. The process of coordinating the trend of the higher time period with that of the lower time period, and acting in only that direction, seems to be the most advantageous approadi. The low of eadi 10-minute swing, maited E, F, G, H, and 1 on the 10-minute bar chart, provides opportunitie* to add to the original position

3. At the top left of the 10-minute chart, the 10-minute close falls below the Sell Stop of the 50minute HiLo Activator at point (about 120-06). The Buy Stop then applies and follows declining prices for 3 dajs. These changes occur in the same area where the Gann swing indicates a trend change from up to down.



4. The 50-minute moving average of the highs, shown in a step formation on the lOminute chart, tracks the highs of the market rallies on dajs 1, 3, and 4. The daily moving average of the highs (the Daily HiLo Activator) remained level on day 2 and tumed down on day 3. The trend can only change to up when the Daily HiLo Activator tums up again

A COMMENT ON MULTIPLETIME FRAMES

in thinking out the use of multiple time frames it is necessary to understand that you cannot substitute a 10-period moving average of 1-hour bars with a 40-period moving average of 15-minute bars. Similarly, you cannot substitute a 10-week average with a 50-day average. It seems natural to think that any two frends covering the same time span will give the same result, but that is not the case. Although we can average many data points, we cannot get rid of all the noise; fewer data points over the same time span will ahvajs yield a smoother result. Therefore, the use of hourly, daily, and weekly time periods-multiple time frames-gives a much different picture of the maitet than simply using three different moving averages based on the same data. It is much easier to see the major frend using weekly data, find the short-term direction based on daily data, and time your entry using hourly bars.

This chart analysis w.\s ff .vi.led by I tert Fj-.msz



20 Advanced Techniques

Volatility IS an essential ingredient in many calculations, trom Wilders RSI to vanable stop-loss points and point-and-figure box sizes. But volatility is more uniform than its short-term measurement would imply; it is a more predictable component of a price series than the trend. Volatility is usually the main ingredient in ride die more volatile the maitet, the greater the risk. As sjstematic programs mature, there seems to be a greater, justifiable concentration on how to manage volatility.

MEASURING VOLATILITY

In general, the volatility of most price series, whether stocks, financial maitets. commodities, or the spread between two series, is directly proportional to the increase and decrease in the price level. This price-volatility relationship has been described as lognormal in the stock maitet and is very similar to a percentage-growth relationship. In Chapter (-Pointand-Figure Charting, it was shown that sojiseans increased in volatility at an average rate of 2.38°o relative to price, very much the same as a logarithmic increase.

{n-day volatility) V(n) = x In {P,.i - Pi,)

where V(n) is the n-day volatility PuKiai is todays price

Phase is the base price of the commodity, somewhere below the cost of production is a scaling factor, near 1

This shows that, beginning at its base price, the volatility of a maitet increases in proportion to its price increase. To express this relationship for interest rate maitets. it is necessaij to use yield rather than price, in addition, as we have discussed fi-om time to time throughout this book, that currency volatility cannot be expressed this way because it has no base price; instead, it has a point of equilibrium. Prices become more volatile as they move away from equilibrium in either direction

Shifting the Volatility Base

It follows that prices are more volatile at higher levels and that most trading sjstems must cope with this change by adjusting their parameters. For example, a stop-loss in gold might be $2 per ounce when the price is under $350 per ounce, $4 per ounce at about 5-100, and $10 per ounce at $500. A point-and-figure box size might varj in the same way as the stoploss. as prices become higher, it requires a larger box size to maintain the same frequency of frend changes and signals. Similarly, a swing chart will need a larger reversal criterion.

Using the stop-loss as an example, most fraders are willing to take a fixed amount of risk (for example, $500), regardless of whether this risk is too large or too small for maitet conditions; for many traders, it is only a matter of how much they can afford to lose. A stoploss that is based on margin offers some improvement because margins are sel according to maitet rid; and contract size, however, the lag time needed for the exchange to change the margin is far too long to keep this relationship current. A percentage stop is a popular

solution for analjsts who realize that volatility increases with price, but it falls far behind during ma}or bull and bear maitets. A reasonable representation of long-term or underlj ing rist is the adjusted, lognormal price-volatility relationship. Although volatility may varj greatly at any price level, this relationship edablishes a foundation for the non--al level.

Base Price

The volatility relationship must include the price level at which volatility is essentially zero. Of course, we cannot find that level on a chart because no trading would have occurred. Although we do not know the price now, we call the level at which volatility is zero the base price. All interest rates, stock indices, and commodities have a base price. Certainly, if Treasurj bills were to decline to a point at which the yield was near zero, most investors would choose to place their money elsewhere, causing activity (and volatility) to disappear. Similarly, when the price of com fails to $1.75 per bushel, below the cost of production, farmers are not inclined to sell; they will wait until prices rise



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