Digital ACSTrend - page 2

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Marry Christmas

Marry Christmass,

I share a lot of ideas with you. If you use them and find some pips, you have only one moral obligation. Today is the boxing day. And those mods are created with this spirit. Your moral obligation is to use some pips to invest in a good cause of your choice: ecological projects and fight against the poverty. As says Bono from U2 we talk not about charity, we talk about justice.

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Prediction and reaction

My predictive Net was not used for a generation of a signal we wait for a price action to develop. However this morning I was somewhat surprised by the accuracy of the prediction.

See several posts ago. My opinion is still that I would not recommend any strategy based on mt4 implementation of NN, however I will keep observing

The idea is that we need a leading indicator who will tell us if the trend is about to continue after the signal is generated. Usually for this task some slow filters are used. The innovation here is to use:

-SSA based direction indicators:

-This simple Neural Net who will tells us its prediction at the moment the signal is generated

-Fractal dimension index: very reliable market state indicator

Files:
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John Last:
I am thinking about using a Simple Neural Net which will tell me what is the probability of any given signal based on the current market conditions.

Some tests have shown that a Neural Net auto-trained according to 1.5 of the current dominant cycle has a greater probability hit rate than the same Net trained on more bars in the past.

This would be a leading filter. The best I can propose for trend filter is in the Elite section:

Look the iVAR, when it is below 0.5 the price movements are persistent, that means that the market condition is well suited for this type of system on on this time fra

______________________

Burn PS3 games

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Fractal dimension use

I see it would be good to gather here what I have written elsewhere. Just to make things precise.

The FGDI is the fractal dimension graph indicator (slight upgrade of the FDI fractal dimension indicator).

If the FGDI is lower than 1,5 level that means that the time series are persistent

If the FGDI is higher than 1,5 level than means that the times series are antipersistent

If the FGDI is equal to 1,5 there is a 50/50 probability.

The FGDI estimates the fractal dimension of the times series.

The fractal dimension = 2 - Exponent of Hurst (H)

So if the exponent of Hurst is equal to 0.5 we have a FGDI equal to 1,5.

Exponent of Hurst of 0.5 means that the movement is random without long term memory processes.

Exponent of Hurst > 0.5 - persistent

Exponent of Hurst < 0.5 - antipersistent

This is explained elsewhere and I just remember that basic stuff. The FGDI (FDI) according to me is better than the fractal dimension indicator published by Ehler, and moreover its mt4 implementation is not free but in the elite section of TSD.

The IVAR is similar to the FDI but its scale is different. The center line is 0.5.

The interpretation is the same when it goes below 0,5 the movement is persistent and vice versa, it is antipersistent.

According to the statistical mechanics if the time series are random walk the H should be equal to 0.5.

Hurst has discovered that a lot of natural phenomena follow a "biased random walk" or trend with noise. The strength of the trend can be measured by how the Hurst exponent is above 0.5 (that means FDI and FGDI below 1,5 and Ivar below 0.5)

In fact all those formula are estimating the Hurst exponent. I think that the easiest is to understand the Rescaled range analysis as a method, to understand what is going on. I precise that I have no high education in mathematics and I was able to understand the logic.

The fundamental principle is if the time series are random their range will increase with the square root of time (this is original idea of Einstein in his paper for the Brownian motion). Einstein found that the distance a random particle travels increases with the square root of time used to measure it.

And Hurst decided to make a ration dividing the Range by the the standard deviation of the observations (R/S) R- range S - standard deviation.

So

R/S = (a*N)^H

R/S = rescaled range N = number of observations a = a constant H = Hurst exponent

So we expect to have H=0.5 if the price time series are random. But they are not folks, that does not mean that they are easily predictable either .

All this may seem very theoretical. The exponential moving average is either theoretical but easy to use. This is the same.

I will share now one strategy.

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

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.

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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<H<1.0

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.

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Phase Space Singularities

The theory is that the market is not a signal. What we have is a multidimensional phase space. In those multidimensional space there are fractal attractors. There are many of them there are simple and complex (point attractors, cycle attractors etc.). For example when we see some number of cycles that does not mean that we have a signal with periodicity and frequency etc blah blah blah. The theory is that we have an underlying phase space wherein some attractor produce those cycles.

The fun thing is that the complexity of the phase Space is changing. Sometimes the phase space is relatively simple and sometimes it is really complex with its multidimensionality.

When the phase space is extremely simple we observe a Low Phase Space Singularity. When the phase space is extremely complex we see High Phase Space Singularity.

I call it singularity because the market dynamics start to be different from the normals market conditions.

Low phase space singularity. What is typical of that is that many different algorithms are able to find the same solution simultaneously and act accordingly. Is it an accident that the Brain trend, the ASCTrend stops with digital smoothing, the ASCtrend signal, the Trend magic with or without digital smoothing and the SSAsqueeze find simultaneously the same solution?

You see brain trend had good results, ASCTtrend had good results, Trend Magic had good results. A simple moving average will have good results. The human trader judgement is blown out the statistics may be blown out and we can go against the trend and can be hurt.

The idea is that when we have a relatively simple phase space of the possible solutions the algorithms are able to find simultaneously a solution. The algorithms are able to cooperate, but the humans we do not cooperate (one guy think it is oversold, the other it is overbought, one guy has long term horizon the other has short term).

And if FGDI (FDI) is in red (iVAR below 0.5) at both 15 and 30 m. time frame is a good approximation of the possible Low phase space singularity.

This Low phase space singularity is scary for the public policy makers, because all the market participants start to have the same horizon simultaneously. They are not able to adjust the economies to the market neither to guide the market as efficient as they would like.

They even may not have an idea what is going on and how their direct expensive interventions fail one after another on the Forex market.

Sometimes the Singularity goes into one direction, sometimes we have a series of ping - pong movements. All that is highly unpredictable several movements into the future, try to train a Neural Net to predict those market conditions and you will see, in fact whatever predicting algorithm you try to implement you will fail predicting the low phase space singularity. You have to react as quick and intelligent as possible, and even a SMA is good enough.

The High Phase Space Singularity is exactly the inverse phenomenon. The Phase Space is terribly complex: nobody is right. The market gos up and down up and down. In that type of market conditions the statistical methods are the best. The Gaussian model approximates very well the market during those times.

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Excellent work

I must say that this is really heavy duty stuff. I've been a technical stock trader for 20 years, but you have left me in the dust.

I am particularly interested in the Adaptive Jstochastic method. I'm not entirely sure what indicators, etc., are required, since there is an addendum to your original post, which mentions an entry to the Include folder. Can you post everything that is required for this method?

Rob

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Fractal Tools and Fibos

Not all the signals of the Digital ASCTrend have the same value depending on what fractal structure they are born. Here I will make a vanilla example of the cycles of the fractal dimension.

With those patterns we exploit the antipersitent cycles in the volatility of the market. Periods of High volatility are followed by periods of low volatility.

And that is the second fundamental feature of the market (The first is the trending feature of the market, driven by its internal memory with high (above 0.5) Hurst exponent).

When we use appropriate instruments those cycles become apparent.

Here I expose a different fibo technique based on the fractal break - out.

The most important thing is from where we are going to make the calculation. My answer is from the fractal break - out. That sets the beginning point of the calculation.

The idea is that when a fractal break- out occurs something important is happening in the market. Something that breaks its structure.

When we see the fractal break - out this is a confirmation for the technical break - out.

And we know that something important is going on. 15 m break out is more important than the 5 m btrak - out, 30 m fractal break - out is more important than the 15 m. and so on (it is common logic).

However on a daily basis we care mainly for the fractal dimension to the 15 m and 30 m.

After the market makes a break - out he takes a rest. He makes the first correction, before continuing. And here is the important staff. This is the common sense and traditional knowledge. We measure the first correction and from there me make a fibo expansion.

This first correction may have different names. I usually call it a Ross Hook, because I am a fan of his method (Law of the Charts).

This technique is important for me because the market sets my price objectives and not an arbitrary decision from me. Usually I can and do catch break - outs but my problem is to know how much to expect from a given break - out. Here the markets tell me.

Theoretically that can be explained that the first correction after a fractal break - out sets a point fractal attractor. This is the simplest and most reliable form of fractal attractor. The market is attracted to a particular point.

Definitions: Fractal break - out - this is the transition of structure of the market. The market moves from one fractal state (with one probabilistic structure to another).

The most important fractal break - out is when we go from high fractal dimension (iVAR>0.5) towards low fractal dimension (iVAR <0.5).

We can use the FDI, or the FGDI, but they repaint the current bar (and that is normal). The iVAR never repaints even the current bar. I find it the most reliable instrument available in Metatrader for estimating those fractal patterns.

Files:
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Installation

Please copy all the files with extension .mqh to the experts/include folder

JJMASeries.mhq

PriceSeries.mhq

All the other files in experts/indicators folder

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John Last:
Please copy all the files with extension .mqh to the experts/include folder

JJMASeries.mhq

PriceSeries.mhq

All the other files in experts/indicators folder

Thanks, John. I have installed the three .mq4 files in the indicators folder, and the two .mqh files in the include folder. I am not seeing any signals on my chart. The Stochastics indicator is a straight line at the 50 level.

Confused.

Rob