Trading beyond Trend
Trader mustunderstand the second, third and fifth characteristics of equilibrium fractal wave so you can trade better with financial market.
The second characteristic of equilibrium fractal wave is that equilibrium fractal wave can be extended to form another bigger equilibrium fractal wave as shown in Figure 10-6. During the important data release or market news release, the financial market can experience a high volatility or shock. When the market experiences the high volatility or shock, the last leg of equilibrium fractal wave can extends to adapt the shock or volatility introduced in the market. Even after the extension, the equilibrium fractal wave still maintains its fractal geometry, the triangle. Hence, the fractal nature of financial market is unbreakable. This price extension often determines the reversal or breakout movement around the important support and resistance levels. One possible way of trading with this second characteristic is to trade on the potential size of equilibrium fractal wave. In the case of reversal, we are betting on that the size of wave will remain the same. In the case of breakout, we are betting on that the size of wave will be extended. This characteristic is also the basis for the straddle trading strategy during the important economic data release.
Third characteristic of equilibrium fractal wave is that smaller equilibrium fractal waves can combine to form a bigger equilibrium fractal wave. Imagine, when the equilibrium fractal wave is propagating, it will start with smaller equilibrium fractal waves first. After the appearance of the several equilibrium fractal waves, we can draw the bigger equilibrium fractal wave by joining these smaller waves. These kinds of jagged patterns are repeatedly found in the financial market as shown in Figure 10-7. This third characteristic can improve our knowledge of the financial market. For example, instead of puzzling with a set of small equilibrium fractal waves, it is much more accurate to puzzle with both small and big equilibrium fractal waves together to predict the market direction. If you want to become a successful trader, you will need a discipline on how to combine the small and big equilibrium fractal wave for your trading.
The fifth characteristic of equilibrium fractal wave is the loose self-similarity (heterogeneity). In nature, it is easy to find the strict self-similarity. However, we can only expect the loose self-similarity in the financial market due to the highly diverse players, participating in the market. Even though all the equilibrium fractal waves will have the triangular form, their shape ratio will be different to each other. For example, if we display the shape ratios of all the series of equilibrium fractal waves in the chart, then we will expect the different shape ratios to its adjacent one (Figure 10-9). This does not mean that we will never have the similar or identical shape ratios in history. In fact, we can get lots of them repeating in the history. For example, we get to see the shape ratio of 0.618 all the time in the financial market. However, we are just saying that the same shape ratios will not often come in the successive manner. This heterogeneous characteristic also implies that the financial market have some shapes more frequently occurring than some other shapes. This also has an important implication for our trading. Imagine that we have a financial market with three shape ratios 0.450, 0.850 and 1.300 repeating infinitely. We only found the shape ratio 0.450 and 1.300 repeated ten times in the historical data whereas the shape ratio 0.850 repeated 100 times in the historical data. Which shape ratio shall we trade with? Of course, we will trade with the ratio 0.850. Likewise, last hundreds years, traders had a solid belief in using the Fibonacci ratios like 0.618, 0.382 and 1.618 for their trading. This belief is based on the assumption that the Fibonacci ratios 0.618, 0.382 and 1.618 occurs more frequently comparing to other non-Fibonacci ratios like 0.567, 0.855, 1.333, etc in the financial market. This loose self-similarity (heterogeneity) is the rationale behind the Fibonacci ratio analysis and other Fibonacci ratio based strategies like Elliott Wave and Harmonic Pattern. The main idea is that, among many diverse equilibrium fractal wave shapes, we need to choose the most frequently occurring shapes (i.e. ratio) for our trading.
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