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Mechanical trading systems - Weissman R.L.

Weissman R.L. Mechanical trading systems - Wiley publishing , 2005 . - 240 p.
ISBN 0-471-65435-3
Download (direct link): mechanicaltradingsystems2005.pdf
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These corrective moves tend to climax at key retracement levels such as 38, 50, or 62 percent, because countertrend traders tend to take profits and trend-followers—that is, hedgers and long-term speculators—often add on to existing positions into these logical, low-risk/high-reward retracement levels.
The most infamous example of a correction against the dominant market trend was the crash of 1987. From the ultimate S&P 500 low of 1982 at 101.44 to the 1987 highs at 337.89, we can measure a bull move of 236.45 S&P 500 points. Dividing this price move by 50 percent we get 118.23 S&P 500 points. Adding 118.23 to the 1982 lows at 101.44 gives us 219.67. The ultimate low print of the so-called crash of 1987 was in fact 216.47—which lies just below a 50 percent correction of the prior bull move (see Figure 1.3). Consequently, I contend that this so-called crash was in fact nothing more than a pullback in the bull market. This example illustrates the severity and emotionalism that can accompany major corrections against the dominant trend.
Psychological Significance of Indicator-Driven Triggers
An indicator-driven trigger can be defined as an occurrence such as a price close above or below a moving average or the crossing of an oscillator above or below a significant level.11 Because the significance of the trigger is directly proportionate to the emphasis that market participants place on the indicator, the more focus on the indicator, the greater the probability of impact on subsequent price activity. This is why deriders of technical analysis view it as a self-fulfilling prophecy. Although I agree that indicator-driven triggers often act as self-fulfilling prophecies, I do not believe that this in any way negates their utility. Instead, the indicators are like emotional barometers: The fact that there is such widespread
FIGURE 1.3 Monthly cash S&P 500 chart with retracements. ©2004 CQG, Inc. All rights reserved worldwide.
focus on indicator-driven triggers in some manner tunes various participants into emotions of fear, greed, and capitulation makes them an invaluable tool in price trend forecasting.
Another common argument against technical analysis suggests price activity in commodity and financial markets is random.12 In fact, instead of a random, bell-curved price distribution, most—around 70 percent—of the time, prices trade in a sideways or range-bound pattern.13 In statistical terms, commodity and financial markets are said to be leptokurtic. That is, they display a strong tendency toward mean reversion—in other words, prices tend to cluster around the mean.
Why then are such a large portion of technical analysts and mechanical trading systems dedicated to trend identification? The reason is because when prices are not in this mean reversion mode, they tend to trend. In sta-
Dispelling Myths and Defining Terms
tistical terms, commodity and financial markets are leptokurtic with amplified tails—when they are not in their mean-reverting mode, they tend to display powerful and sustainable trends. These trends offer traders low-risk/ high-reward opportunities, such that a single profitable trend-following trade often will offset numerous small losses, thereby resulting in an overall profitable trading system that experiences less than 50 percent winning trades.
The 200-day simple moving average examined earlier provides us with an excellent example of a trend-following indicator. Another popular variation on this mathematical trend-following indicator is known as the two-moving average crossover system (see Figure 1.4).
The two-moving-average crossover system entails the introduction of a second, shorter-term moving average, such as a 9-day simple moving average. Now instead of buying or selling whenever the market closes above or below the 200-day simple moving average, our trend-following trader establishes long positions whenever the 9-day moving average crosses over and closes above the 26-day moving average. By contrast, whenever the shorter-term moving average crosses over to close below the longer-term moving average, our trader would exit all long positions and initiate short positions.
FIGURE 1.4 Spot dollar-yen with 9- and 26-day moving averages. ©2004 CQG, Inc. All rights reserved worldwide.
In contrast to trend-following indicators such as the two-moving average crossover, mathematical countertrend indicators, such as the relative strength index (RSI) (see Figure 1.5), attempt to capitalize on the market’s tendency toward mean reversion (although mean reversion indicators can be profitable in trending markets and vice versa).14
In 1978 Welles Wilder—who developed many commonly used mathematical technical indicators—developed the RSI to provide traders with an objective tool for measuring when a market becomes either overbought or oversold. The strength of the market is measured by this following formula:
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