Cycle Indicators - Fibonacci - Seasonal Trade - Gann Theory - Elliot Wave
Proper Use of Cycle Technical Indicators
Futures chart Cycle indicators is a term to indicate repeating patterns of market movement, specific to recurrent events, such as seasons, elections, etc. Many markets have a tendency to move in cyclical patterns. Cycle indicators determine the timing of a particular market patterns.
Many securities, particularly futures, show a strong tendency to move in cyclical patterns. The theory is that price changes can be anticipated at key cyclical intervals, or periods. The time span of market cycles can run from several decades to only a few days, or even hours. Within each market, several cycles of differing time periods act upon the prices. Since price patterns are a result of these overlapping series of cycles, it is common to combine two or more cycles to form a composite cycle, specific for each market and analysis time frame. The following indicators and line studies can be used to measure cycles:
Fourier transform is based on the principle that any finite, time-ordered set of data can be described by decomposing it into a set of sine waves, which are specified by cycle length, amplitude and phase relationship. To use Fourier on trending data of commodity prices, you must first de-trend the data with a linear regression trend line or a moving average.
Elliot wave is based on the principle that prices move in two major wave patterns: impulse waves (define prevailing trend direction) and corrective waves (move against the trend). A complete Elliot Cycle consists of both these waves. Within these two waves, there are smaller wave patterns. The impulse wave consists of five smaller waves, three in trend direction and two counter-trend; the corrective wave consists of three price waves, two in the direction of correction and one counter-correction. A problem with this method is the subjectivity involved in interpreting the wave patterns and determining the starting point of the cycle. Also, this method was developed for stock prices and may not reflect the behavior of agricultural commodity prices.
Gann theory is based on the idea that there is a mathematical relationship between price and time. Specifically, certain geometric patterns can be applied to price charts to forecast market behavior.
One concept is the trend angle. A 45% trend (remember to first correct for the chart scale) is considered a 1x1 ratio of time to price and is the primary trend line used in Gann analysis. There are also 1x8, 1x4, 1x2, 2x1, 4x1 and 8x1 ratios. Prices move within these angled channels, the lines of which act as support/resistance.
Another concept is replacement levels. Price is divided into 1/8ths and made into percentage levels. The key levels are 50%, 25% and 75%. (The significance of 1/8 is from tick sizes in grains (1/4 cent) tick values in currencies ($12.50=1/8) and the tick values of other contracts ($25=1/4)).
seasonal are based on the idea that prices of agricultural commodities reflect naturally occurring cycles, such as the 28-day lunar cycle and the 6-12 month crop seasons. Such cycles are specific to the production and storage of each commodity, as well as the growing location for each.
Fibonacci retracement is a very popular tool among technical traders and is based on the key numbers identified by mathematician Leonardo Fibonacci in the thirteenth century. In technical analysis, Fibonacci retracement is created by taking two extreme points (usually a major peak and trough) on a stock chart and dividing the vertical distance by the key Fibonacci ratios of 23.6%, 38.2%, 50%, 61.8% and 100%. Once these levels are identified, horizontal lines are drawn and used to identify possible support and resistance levels.
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