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Fractal dimension patterns

Here I list some patterns from the fractal dimension indicators. 

Fractal break -out 

Basically the ideal price movement is in a price channel. The price channel can be horizontal (range channel) or directional (trend channel). In fact it does not matter the type. When a price breaks the borders of a chart channel we have a break - out of the channel. If that happens we have a probability that the market conditions has changed and the price will further go away from the channel.

The channel can be regular but it can be irregular. All the classifications of the channels is in fact the technical analysis.

A channel defines a trading range. We have up limits and down limits of the channel. You need at least two points from above and from below to draw a price channel. Then just draw a line connecting the up limits and the down limits of the channel.

Well, but when the prices goes beyond the channel and the gets back to the channel often the technical guys will tell you that you have drawn the channels improperly and you need more educations. When you get more education you will draw the lines properly but again you will see the prices go beyond the channel and get back to the channel. As in the avatar the pilot says before going to battle Ain't that a shit.

This is called a false break - out that happens more often that we want to admit (50 % of the cases ). Ain't that a shit again?

Anyway My idea is to get new details how to trade a Break - out.

1. Use of the volatility probability 
We have a break - out probability in periods of increased volatility. So it is necessary to check statistically the volatility. This is well known by the professional players. On the net there are studies with the volatility. Usually we expect a break - out during the open of the European Session and the US session

2. Use of fractal indicators FGDI, IVAR, FDI
We use a fractal dimension graph index indicator (FGDI). When a breakout occurs it is accompanied with a change of the fractal state of the price series.

That means that the graph goes from a state of high fractal dimension to a state of low fractal dimension. We have a shift in the internal structure of the price time series.

2.1 Fractal Break - out

Conditions: We are at a blue zone with fractal dimension greater than 1.5. We move to a zone below 1.5. This is a fractal breakout

This is usually observed after a range (FGDI greater than 1,5)

2.2 Fractal Break - in
We are at a red zone, fractal dimension less than 1,5. The fractal dimension get lower. 
I call it so because we are in a red zone of low fractal dimension and the fractal dimension gets lower.

This is usually observed in an established trend when we have a breakout in the direction of the trend.
So when we have a lower fractal dimension the movement is persistent. There is a bigger probability that the next movement will be in the direction of the previous. So when there is a reversal, the reversal tends to be quick and abrupt (Black noise). So that explains how the V tops and V bottoms are formed.

On the other hand when the fractal dimension is higher than 1.5 we have a bigger probability that the next movement will be in the opposite direction.
And the price goes up and down in a lot of oscillations. There we can find pink noise, a lot of whipsaws up and down. 

If the price time series were random there would be no correlation of each movement with the previous movement.

I can give a lot of examples of this. This approach is different and independent from the TA perspective so it combines really well with it.

H - Hurst exponent
When H = 0,5 the FGDI = 1,5

Pink noise 00.5
Black noise 0,5
See chapter 13: Fractional noise ans R/S Analysis
From the book fractal market analysis.

The best use of the system is when there is a low dimension in both two key levels 15 and 30.

If we have red on both 15 and 30 time frame our Persistent Movement Roller Coaster can begin . We will show to the old guys how we can pick tops and bottoms. If we have on both 15 and 30 time frame high fractal dimension that means that the phase space is deemed to be too complex. I call it high phase space singularity.The phase space is so complex that nobody is right. The price goes high and low like crazy.

3. A peak in the Hurst Difference

Well this is a kind of measure of the change of the transition of the fractal dimension from one state to the other. 
This is a new indicator find in the code base of mql. So the idea is to measure the rate of change of the Hurst Exponent. A high peak means that something is going on.


  • CamaRon 4121 days ago

    Well written ! 

    As you know, I still feel we have to dig deeper in this fractal matter :)

  • JohnLast 4121 days ago

    So far we try to analyse the activity of the high frequency traders and the algorithmic traders as a whole. Their microscopic activities affect our macro world. As we cannot compete directly we could try to have some clues what is going on on the macro level.

    We have some evidence from using two different approaches that there are some pockets of predictability. One of the evidence is offered by the research of Mr. Zapart. And we exchanged some correspondence with him. His idea was to show that at some moments the entropy drops down and the market gets really more predictable.

    The other evidence is from the chaos theory field. There is evidence that when we have a large Hurst exponent the market gets more predictable.

    The last tool is the Lyapunov exponent that determines how much in the future we can look.

    That all means that under some specific conditions the order flow will rule the market. That is due to the fact that at some specific moments there is a solution and the machines are able to detect it. And if they are able to detect it, they create nerd type order flow, and the order flow makes the price moving in a specific direction.

    And that predictability is completely independent from the notions of trend or range. I call this a phase space of the possible solutions. Very often there is a directional solution and many algos are able to detect it and act accordingly. The idea comes from the i Robot boom of Asimov. There is a mass psychology of the robots too. Sometimes (under specific conditions that can be measured) they act as a super nerd. And that causes flash crashes. So I apologize it is a bit confusing. But we have a behavioral hypothesis, and some tools. And most of all your approach is a big part in this picture.

    The WoW index with the analysis of the order flow may be a valuable tool.

  • JohnLast 4121 days ago

    So the sequence is:

    1. Market State creating a pocket  of predictability
    2. The algos find a solution simultaniously even if their logic is different
    3. The algos form a super algo nerd 
    4. The algo nerd creates an order flow
    5. The order flow move the prices 



  • JohnLast 4121 days ago

    6. Eventually the algos run a lot of stops and Flah Crash occurs ;).