Trading Between the Lines by Elaine Knuth

Author:Elaine Knuth
Language: eng
Format: epub
Publisher: Wiley
Published: 2011-02-03T16:00:00+00:00

Self-Similar Fractals We See

Without going into any discussion of fractal theory and the mathematics of fractals (the Hurst exponent7 and Mandelbrot’s work on time series data), which is beyond not only the purpose of this book but the competencies of your author, we accept that price is determined by the market participants who are reacting not only to price information, but also to information outside of the markets and at different times. Not all participants work in the same moment nor do they make decisions based on the same kind of information or timescale of price. Operating in different time frames, we respond to events and fundamental information as time progresses; so price information in liquid active markets, therefore, must occur in multiple time frames.

Because of this, when we look at a price chart of a liquid market it is almost impossible to say what is the time scale of the data—daily, monthly, 15-minutes? My thought is that if we identify market turning points with the methods described in the previous chapters, we can then magnify the characteristic of the current prevailing price action by breaking price action down into fractals of time. A data series does not repeat itself, but the behavior of market participants does repeat regardless of time frame of participation, and it is this that creates the phenomenon of a self-similar pattern (fractal).

For example, Figure 5.1 is the complete picture of a market and price data set. This shows obvious demonstrations of cyclical behavior in waves and trends over a period of 20 years. The wave patterns may also look like chaotic sound oscillations, though the pattern shown just happens to be the price of world sugar (a commodity actively traded in all parts of the world). Each bar represents a period of one month, or a one-month trading session.

FIGURE 5.1 Sugar No. 11, 20 Years, Monthly

Source: Genesis Financial Technologies, Inc.

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