Fractal structure analysis of NG, BR, GOLD, SILV, SPY, ED, ...

most research papers are written by Ph.D students.

Not sure I can agree with that...

I don't know whether there is an easy way to measure that kind of thing. But I would hazard a guess that the majority of papers that are published in the top tier of peer-reviewed journals are not written by graduate students, but rather by established researchers or professionals who hold a terminal degree and are no longer students.

It is also very common for a paper to have multiple authors. Often one of the authors is a professor and the others are students of that professor.
 
Interesting. You should also cover at least all major 7 FX pairs or better all 28 majors and minors. Other interests than liquid FX I do not have at this moment. But SPY and Gold, Oil, also T-note is also interesting. Where can I see what you are publishing ? I deleted my old telegram. I would give it a try. Looks interesting to me. But I need to check and test first. Do you offer these curves as indicator for Metatrader5 too ? Any mql seller link you have on its store ?

I don't sell anything and I'm not in the information business at all. But I will not refuse a mutually beneficial partnership.

How to contact you ? (outside of telegram)

You can create a new private thread here:

https://www.elitetrader.com/et/conversations/add

Please post more examples. Actual ones please, also when it is not so good working to get an honest picture of it. Because there are always drawdowns in every strategy. One needs to be aware of them.

I was not planning to post trading signals (at least not here). At the same time my analytics could help you to make thoughtful decisions (in order to earn or at least not to loose). In return, I would like to receive donations to continue this project/research.
 
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I would be interested in someone trying to explain why they think fractal patterns are an integral, unavoidable part of price movement.

There's a lot of craziness in technical analysis where someone picks a variety of mathematical functions, runs a fit of the parameters to make them fit a data set, and then goes "look I have a model for something". I see a lot less effort put into exploring why that particular model matters.

Are major traders using fractal model to make buy/sell decisions? Is there something inherent to supply or demand that is well modeled by fractals?
Simply put, why do you think fractals are worth paying attention to in the first place?

That could be an interesting discussion.

Trying to find cause and effect for every human decision that moves the market is a fruitless exercise and surely a path to madness. I like the simple pink noise model of price, k/pow(f,alpha), where you set k and alpha equal to 1 for simplicity sake. This gives a power spectral density of 6dB increase in power per octave decrease in frequency, or 2:1 growth rate versus 1.618:1 for a fractal data series.

So price is pink noise, now what to do about it? Whiten the data to get a flat PSD, then do your favorite technical analysis on that data series.
 
Trying to find cause and effect for every human decision that moves the market is a fruitless exercise and surely a path to madness. I like the simple pink noise model of price, k/pow(f,alpha), where you set k and alpha equal to 1 for simplicity sake. This gives a power spectral density of 6dB increase in power per octave decrease in frequency, or 2:1 growth rate versus 1.618:1 for a fractal data series.

So price is pink noise, now what to do about it? Whiten the data to get a flat PSD, then do your favorite technical analysis on that data series.

If you model doesn't ties in to basic fundamentals it's likely to go off the rails.

Looks at climate "science", a bunch of crazy models of the past several decades that have consistently been wrong.

If you're going to try to predict the price of crude oil, your model should include data on inventories around the word. If it does not, or is insensitive to that variable, then I would argue that it is obviously wrong.

Even if back testings shows 100% agreement with previous price, if would say that it's doomed to be wrong, it just had enough degrees of freedom in the fit of the models parameters that you could force it to match a data set.
 
If you model doesn't ties in to basic fundamentals it's likely to go off the rails.

Looks at climate "science", a bunch of crazy models of the past several decades that have consistently been wrong.

If you're going to try to predict the price of crude oil, your model should include data on inventories around the word. If it does not, or is insensitive to that variable, then I would argue that it is obviously wrong.

Even if back testings shows 100% agreement with previous price, if would say that it's doomed to be wrong, it just had enough degrees of freedom in the fit of the models parameters that you could force it to match a data set.

Yes, but in financial markets you get paid to take risks. The difference between reality and the results from your model are where the risks lie. Markets will never be modeled perfectly because the complexity is too great, just as in weather.

What happens when central bank models of the economy are wrong? Flucuation in the economy of course as market feedback loops try to correct the error. Unfortunately, some people win and some lose, that is the nature of life. Always has been and always will be. Marxism isn't going to solve this dilema, nor is Reaganomics.
 
We have discussed fractals before. The main problem with fractals in trading markets is that "anything" can be a fractal. If you don't like those divisions on the chart that you drew in green you could always zoom in and out and go to a different time frame to find patterns that would satisfy your initial premise.

Very we’ll said. I find this the hardest part of fractal analysis

@Collapse this is a topic I’m interested in discussing. What criteria are you using to draw your fractals?
 
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