Stocks & Commodities V. 30:4 (20-27): Engineered Look At Trends In Cycles by Arthur Zernov

Stocks & Commodities V. 30:4 (20-27): Engineered Look At Trends In Cycles by Arthur Zernov
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Engineered Look At Trends In Cycles by Arthur Zernov

Itís easier to gain from trending markets than choppy or cyclical market movements. But you can detect trends from a cyclical perspective.

Identifying trends in prices is nothing new; these days, technical analysts and traders develop various methods for detecting trends, trying to determine what is trending now and what may trend in the future. Behind such interest in trends is a desire for an easy profit, since it is much easier to gain from a trend than it is from choppy or cyclical market movements. There are many ways to detect trends, and in this article I will examine one such method: looking at a trend from a cyclical perspective.


The traditional definition of a trend is a directional movement of prices long enough to be identified and tradable. In Figure 1, you will see a graphical representation of a trend in the weekly chart of the Standard & Poorís 500.

In my April 2011 Stocks & Commodities article, I stated that the mathematical methods used in electrical engineering to describe signal wave forms can be used for market price data analysis. From a cyclical perspective, a trend is a long cycle of a given period, whether known or unknown. The length of the cycle is relative to the cycle under review.

If you look at Figure 1, you will see the presence of a cycle when the price was trending. The cycle had a period of 14 weeks from September till December 2010. The entire trend from September 2010 till February 2011 can be considered to be part of a larger cycle; it looks as though the long cycle reached its peak in mid-May 2011.


In addition to trendlines, moving averages are another common method with which to track trends, using various time periods and types. The weekly chart of the S&P 500 in Figure 2 shows a trendline and an 18-bar moving average. Note how the moving average closely tracks the trend. The big question is how to select the correct period for the moving average. After all, not all periods are going to track the trends as closely. One way is to analyze historical data and select the period that works the best in various market conditions. The ďbestĒ does not mean the highest return, but rather the most stable one. You can then look at various parameters such as average profit factor and standard deviation.

After your analysis, the period you select for your moving average can give you secure results in many market situations. However, the moving average may underperform if the character of the market changes significantly; in fact, I am certain that the change will happen the moment I put my money on the table or when I donít expect any change to occur. If you envision the market as a big casino, you should remember that we are the players, not the dealers. We have no input on the rules, but we can try to adapt to an ever-changing market.

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