low zones, like the indicator in Figure 11.4. For an indicator with more than four years of data, that would ensure at least a years worth of time in the high and low zones and would make a deficiency of observations less likely. In effect, the time-in-zone limit prevents excessive optimization by excluding zone-level possibilities that would appear the most impressive based on per annum gain alone.

Another consideration is that in some cases, a closer examination of the zone performance reveals that the bullish-zone gains and bearish-zone losses occurred with the indicator moving in particular directions. In those cases, the bullish or bearish messages suggested by the per annum results would be misleading for a good portion of the time, as the market might actually have had a consistent tendency, for example, to fall after the indicators first move into the bullish zone and to rise after its first move into the bearish zone.

It can therefore be useful to subdivide the zones into rising-in-zone and falling-in-zone, which can have the added benefit of making the information in the neutral zone more useful. This requires definitions for "rising" and "falling." One way to define those terms is through the indicators rate of change. In Figure 11.5,

Figure 11.4 Dow Jones Industrial average (DJIA) and an indicator with

approximately 30 percent of its time in the high and low zones.

w**kfy Date 1/19/6» - 7/36/96 ftof SceUI

Dow Jonee IndUBtrial Average

5421 4811 4269 3788 3362 2983 2647 2349 2085 1850 1642 1457 1293 1147 1018 903 802 711 631

5421 4811 4269 3788 3362 2983 2647 2349 2085 1850 1642 1457 1293 1147 1018 903 802 711 631

tstt

171.8 159.0 147.2 136.3 126.2 116.9 108.2 100.2 92.8 85.9 79.5

*. © -

t55t"

171.8 159.0 147.2 136.3 126.2 116.9 108.2 100.2 92.8 85.9 79.5

Three-Weak Moving Average

7/2 /9 - 10 .1

Low Inflationary Praaauraa

Commodity Research Bureau Futuree Price Index (Year-to-Year Change)

Source: Ned Davis Research. Used by permission.

figure 11.5 Standard & Poors (S&P) 500 stock index with "Big Mo"

stochastic indicator. the percent gain per annum of the market is better classified when the indicators direction as well as location is considered.

Wtekty Data 3/04/66 - 7/26/96 (Lag ice/*)

Standard & Poors 600 Stock Index

657 566 4» 421 363 313 269 232 200 173 149 128 110 95 82

Big Mo Moving Up While in Mode

Big Mo Moving Down While in Mode

Big Mos Direction is Determined By Whether it is Higher or Lower Then It Was Five Weeks Ago

657 566 488 421 363 313 269 232 200 173 149 128 110 95 82 71

Extremely Beerieh

Big Mo - Composite Longer-Term Investment Guide

Source: Ned Davis Research. Used by permission.

which applies the approach to the primary stock market model used by Ned Davis Research, their "Big Mo" indicator is "rising" in the zone if it is higher than it was five weeks ago and "falling" if it is lower. Again, the time spent in the zones and the number of cases are foremost concerns when using this approach.

Alternatively, "rising" and "falling" can be defined using percentage reversals from extremes, in effect using zones and trading signals to confirm one another. In Figure 11.6, for example, the CRB (Commodity Research Bureau) Index indicator is "rising" and on a sell signal once the indicator has risen from a trough, whereas it is "falling" and on a buy signal after the indicator has declined from a peak. Even though the reversal requirements resulted from optimization, the indicator includes a few poorly timed signals and would be risky to use on its own. But the signals could be used to provide confirmation with the indicator in its bullish or bearish zone, in this case the same zones as those used in Figure 11.4. For example, in late 1972 and early 1973 the indicator would have been rising and in the upper zone, a confirmed bearish message. The indicator would then have peaked and started to lose upside

Figure 11.6 DJIA and CRB indices. Chart shows DJIAs

annual gain as a function of CRBs zone location.

Wttkly Data 1/07/72 - 7/26/96 {Log Scab)

Dow Jones Industrial Average

5287 4557 3928 3386 2918 2516 2168 1869 1611 1389 1197 1032 889 767 661 570

Profitable Tradea: 79*

Gain/ Annum: 11.5*

Buy-Hold Gain/Annum: 7.6X Signal : 8/04/72 - 7/26/96

When Smoothed Y/Y Change of CRB Index: Up 18.1% From a Trough - Sen Down 7.7% From a Peak - Buy

T8TT 171.8 159.0 147.2 136.3 126.2 116.9 108.2 100.2 92.8 85.9 79.5

7/28/96 - 106.1

High Inflationary Preaaurea

CRB Index Year-to-Year Chenge (Three-Week Smoothing) With Signals and Modes

Source: Ned Davis Research. Used by permission.

momentum, generating a "falling" signal and losing the confirmation. That signal would not be confirmed until the indicators subsequent drop into its lower zone.

The charts box shows the negative hypothetical returns with the indicator on a sell signal while in the upper zone, and on a buy signal while in the lower zone. In contrast to the rate-of-change approach to subdividing zones, this method fails to address the market action with the indicator in the middle zone. But it does illustrate how zone analysis can be used in conjunction with trade-signal analysis to gauge the strength of an indicators message.

Subsequent Performance Analysis

In addition to using signals and zones, results can be quantified by gauging market performance over various periods following a specified condition. In contrast to the trade-signal and zone-based quantification methods, a system based on subsequent performance calculates market performance after different specified time periods have