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Aug 25, 2021, 11:13 AM GMT

Gauging Uncertainty in Trading, the Power of the Elliott Wave Theory

The Elliott Wave Theory underlines the fractal nature of price action

A fundamental problem that all traders face early on in their careers is how to measure uncertainty. The vast majority of novice market participants are woefully unaware of the true nature of trading risk, let alone being capable of measuring and negating the palpable risk stemming from uncertainty.

One way to deal with black swans on the market is to look at that which is scalable and transcendent. What exactly does this mean? The price action of any given asset can be viewed on charts with different timescales. And in order to get a proper sense of the underlying market sentiment at any point in time, traders need to be able to weigh in on the behaviour of the price action in the short term vs the long term.

This creates a problem of its own. It could be that the underlying price action behaves erratically and unpredictably on charts with smaller timeframes while exhibiting more decisive upswings or downswings on charts with higher magnitudes. So, how to reconcile the two starkly opposed readings and make sense of them both? Introducing the Elliott wave theory.

How does uncertainty manifest itself in trading?

Firstly, it is important to build a workable conceptualisation of what exactly is meant by uncertainty. Most novice traders are oftentimes confused by "common sense", in that they spend too much time trying to figure out the probability of something going array while their positions are active. But trading risk can never be genuinely reduced to the 1:3 "golden rule" of trading.

Common sense dictates that the probability of the underlying price action going against the direction of the open position would be dependent on the past behaviour of the price action. While there is validity to this line of reasoning, it is only half the story. Proponents of this way of thinking oftentimes fall victim to confirmation bias - they scroll back to find "evidence" that corroborates their preconceived expectations.

But in reality, uncertainty cannot be reduced solely by building models of past price behaviour. That is so because, more often than not, the catalysts of adverse fluctuations tend to be unconventional events whose origins have not been accounted for in the past. Say, a one-off speech by a prominent market figure, a new conflict in the Middle East or a global pandemic. It's not that these events haven't happened in the past, but it's almost impossible to use them as benchmarks for projecting when similar occurrences would happen again in the future.

Studying past price action can only give you a rudimentary understanding of the next likely direction of the market, but that does not reduce uncertainty.

In order to get better estimations of the probability of the price action going up or down, traders need to pay more attention to its scalability. This relates to the fractal nature of the price action - its behaviour on charts with smaller timeframes being directly connected to its behaviour on longer-term charts. Uncertainty can therefore be somewhat reduced if traders examine how the price action is scaled up and down across charts with different timeframes.

Exposing the fractal nature of the price action

The mathematician Benoit Mandelbrot coined the concept of fractals to describe their capacity to exhibit similar patterns on increasingly smaller scales. Getting back to the Elliott Wave Theory, we know that a classic 1-5 impulse wave pattern is comprised of three impulse legs (0-1; 2-3; 4-5) and two intermediate retracement legs (1-2 and 3-4).

Using Mandelbrot's concept of fractal scalability, one can assert that trends comprised of 1-5 impulse wave patterns are likely to exhibit similar behaviour on charts with smaller timescales. Indeed, it is not really difficult to find that individual impulse legs are typically comprised of smaller 1-5 impulse wave patterns themselves, while retracement legs tend to take the form of ABC corrections.

While discovering evidence of such scalability on a given asset's price action is not enough to forecast the future with certainty, it can reassure the trader of whether the price action is acting consistently or randomly. For as long as such scalability holds true, the probability of adverse fluctuations would be somewhat diminished.

Traders can therefore use the fractality of the price action to pick tops and bottoms in an established trend and choose whether to use trend continuation strategies ahead of an anticipated impulse or contrarian strategies before a subsequent retracement.