Discussion of article "Brute force approach to pattern search" - page 10

 

Bruteforce and neural networks are a necessary thing to find patterns. Just some people use it incorrectly and look for the wrong place or the wrong thing, or are limited in resources, again due to the incorrect application of algorithms or programmes implementing them. For example, on mql4 or mql5, it is very difficult to implement it, no matter how much they praise this platform, it is designed initially not for these methods. But if you do it quite differently and search for the necessary data, and make the sample bigger than it is possible on mql, then these patterns are literally visible to the naked eye. For example, there is always a pattern between different currency pairs, you just need to look for them "correctly".

sample search on a simple laptop

 
savabaka:

Bruteforce and neural networks are a necessary thing to find patterns. Just some people use it incorrectly and look for the wrong place or the wrong thing, or are limited in resources, again due to the incorrect application of algorithms or programmes implementing them. For example, on mql4 or mql5, it is very difficult to implement it, no matter how much they praise this platform, it is designed initially not for these methods. But if you do it quite differently and search for the necessary data, and make the sample bigger than it is possible on mql, then these patterns are literally visible to the naked eye. For example, there is always a pattern between different currency pairs, you just need to look for them "correctly".


I agree, I have just about to publish the third article on this branch ) just on this topic, and the fourth one is planned ). here you can even see for interest at what stage of development of the method ). this video in the fourth article will be only

https://www.youtube.com/watch?v=LhY_dN6d0lE

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Forex Awaiter Prototype
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I just need to reply this article. Patterns are just a small piece of the overall picture.

If higher timeframe shows uptrend, smaller timeframe shows downtrend, a reversal pattern in smaller timeframe means a buy with small SL. 

The most important question: how to make the machine understands what is a trend? 
 

We need to make the machine  learning to understand the  profitability and the pattern relationship.And this is well explained  in the article.We dont' need it to understand  what the trend is.

My experience is neural networks dont' work in strong trends ,you can check it with bitcoin,crypto currency data series.

bitcoin - Trading blogs and financial markets analysis
bitcoin - Trading blogs and financial markets analysis
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Bitcoin is a digital currency, or crypto-currency, created and held electronically and is not backed by a government or central bank to regulate or issue it. It thus enables direct payment over the
 
Allan Ferreira:
I just need to reply this article. Patterns are just a small piece of the overall picture.

If higher timeframe shows uptrend, smaller timeframe shows downtrend, a reversal pattern in smaller timeframe means a buy with small SL. 

The most important question: how to make the machine understands what is a trend? 
understand that trend and flat are just substances invented by our brain to simplify understanding of the market. In reality, market situations are endless, and it is impossible to describe all of them in such a limited framework. The task of the machine is to determine which situations are most represented on the market and highlight those that are truly global. This is the task of the machine. The human brain is not designed to analyze large amounts of data, but the machine happily does it. The point of this method is that you don't need to know what the machine has found, you just need to know that it works.
 

The first degree polynomial looks better.

The ratio of optimisation period to profitability is 4 to 1, I have seen it not for the first time.

Half-waves, this is from probability theory, there are formulas for the maximum spread, the number of crossing 0, the probability of returning to 0.

Look at the link, by leaving only 1 degree you do linearisation, you can replace bruteforce with solving equations.

 
Rorschach:

The first degree polynomial looks better.

The ratio of optimisation period to profitability is 4 to 1, I have seen it not for the first time.

Half-waves, this is from probability theory, there are formulas for the maximum spread, the number of crossing 0, the probability of returning to 0.

Look at the link, by leaving only 1 degree you do linearisation, you can replace bruteforce with solving equations.

leaving the second degree we work with the regression channel, with the 3rd degree we start to take into account deviations within the channel.

That's how it is, without details and fanaticism.

 
Rorschach:

The first degree polynomial looks better.

The ratio of optimisation period to profitability is 4 to 1, I have seen it not for the first time.

Half-waves, this is from probability theory, there are formulas for the maximum spread, the number of crossing 0, the probability of returning to 0.

Look at the link, by leaving only 1 degree you do linearisation, you can replace bruteforce with solving equations.

The classical Taylor series is made for a function of one variable, I am using a version for a function with an unlimited number of dimensions. Although to be honest I certainly use only the first degree. simply the polynomial becomes the sum of the coefficients multiplied by the price shifts at each bar. In the end, the deciding factor is not the type of formula itself, but the frequency of the search. In general, it doesn't matter, it gives the result. Further you can roll out modifications, correct something.

 

Hi, your work and especially your thoughts are very interesting. You wrote, that both versions mt4 and mt5 are attached. I can't find a mt5 version! ?

Please add if possible.

Many thanks