MetaTrader 5 Python User Group - how to use Python in Metatrader - page 35

New comment
 
Sergey Chalyshev:

Don't judge harshly, maybe there are python lovers out there trying to integrate it into anything and everything.

Python is a C++ library, is it not better to make MQL SB(standard library)?

MQ was initially going in this way, but then gave up under the onslaught of Ruto, RWods and Algibods )

I think the whole problem is that MQ is afraid to go beyond the sandbox, like R, Py, Alglib is not our problem anymore.

They added a link to other "programming languages" and let the other Yaps do what they want.

Reminds me of an ostrich.)

What substances must be taken to detect integration with R?

 
Renat Fatkhullin:

The problem is the narrowness of perception of the topic among the masses and a lack of understanding of the trends in the development of algotrading:

  • Machine learning is the next technological step in algotrading
  • Python is not a C++ library, but a winning machine learning platform
  • Python's integration into editor and terminal gives you the ability to instantly use off-the-shelf and completely intolerable decision-making libraries
  • Integrations are the norm, we have Native DLL, .NET DLL, OpenCL, DirectX, SQLite in addition to a large set of native functions and standard library
  • Metatrader 5 and MQL5 are rapidly evolving to support machine learning: first via Python, Terminal API integration library and functions for working with massive data, and then to the standard WinML and open ONNX model formats.

Ostrich is exactly the kind of person

  • trying to argue about the complexity of MQL5 and the benefits of MT4
  • Not developing, saving their energy
  • Trying to stop progress


To better understand the algotrading industry:

  1. Think large scale with tens of millions of consumers rather than personal/private perceptions or opportunities
  2. Evaluate 5-10 year periods and development trends, public information is sufficient.
  3. the products (robots, indicators, ...) are mainly developed by more or less professional programmers, who need more and more possibilities, including distribution
  4. mass users use the output of professional developers often without understanding the complexity of applied technologies
  5. there is enough layer of not public, but super capacious developers and consumers in the form of hedge-funds
  6. You either embrace progress or you are left out - the train is running non-stop.
If one stays within the framework of "there is only me and my interests, why should I think about the general and the future", one naturally loses the ability to defend their position on a large scale.

"Adult" trading, risk management is first and foremost a matstat. Machine learning here is essentially just one way of solving matstat problems. These are somewhat different tasks than those that arise in the development of the Internet of Things and things like that.

 
Renat Fatkhullin:


  1. there is a sufficient layer of non-public, but super-capable financial developers and consumers in the form of hedge funds

From this point on, it suddenly got very interesting, ;)

 
Aleksey Nikolayev:

"Adult" trading, risk management is first and foremost a matstat. Machine learning is essentially just one way of solving matstat problems. These are somewhat different tasks than those that arise in the development of the "Internet of Things" and other such things.

Did it say "no to matstat!" somewhere?

We've already made a big step forward by implementing the basic math library from R in the form of MQL5 sources (more than 400 functions):

Just integrating with Python will give you access to almost all possibilities of statistical analysis.

As soon as we complete Python, we'll enable full C/C++ compilation in the editor to create DLL, EXE and special EX5 modules from C++. This will allow existing C++ libraries to be recompiled into EX5 compatible form with minimal rework and will open up access to a lot of open-source libraries.

Статистические распределения в MQL5 - берем лучшее из R и делаем быстрее
Статистические распределения в MQL5 - берем лучшее из R и делаем быстрее
  • www.mql5.com
Рассмотрим функции для работы с основными статистическими распределениями, реализованными в языке R. Это распределения Коши, Вейбулла, нормальное, логнормальное, логистическое, экспоненциальное, равномерное, гамма-распределение, центральное и нецентральные распределения Бета, хи-квадрат, F-распределения Фишера, t-распределения Стьюдента, а...
 
Renat Fatkhullin :

Did it say "no to matstat!" somewhere?

We've already made a big step forward by implementing the basic math library from R in the form of MQL5 source code (over 400 functions):

Just integration with Python gives access to almost any statanalysis capability.

As soon as we finish Python, we will integrate C/C++ compilation into the editor to create DLL, EXE and special EX5 modules from C++. This will allow existing C++ libraries to be recompiled into EX5 compatible form with minimal rework and will open up access to a lot of opsource libraries.

Very interesting. Are there plans to embed (as a resource) the ex5 library in an EA or indicator to publish it on the Market?

 
Alain Verleyen:

Very interesting. Are there plans to embed (as a resource) the ex5 library in an EA or indicator to publish it on the Market?

No.

Only we will be able to distribute the modules publicly for security reasons.

Most likely there will be a section of official modules in kodobase, automatically uploaded according to instructions:

#module "public_name_in_codebase"
We are also going down the path of automatic batch managers. The codebase engine will be reformed.
 
Renat Fatkhullin :

No.

Only we will be able to distribute the modules publicly for security reasons.

Most likely there will be a section of official modules in the kodobase, automatically uploaded according to instructions:

I understand. Thank you.
 
Renat Fatkhullin:

Did it say "no to matstat!" somewhere?

We've already made a big step forward by implementing the basic math library from R in the form of MQL5 source code (over 400 functions):

Just integration with Python gives access to almost all possibilities of statanalysis.

As soon as we complete Python, we'll incorporate C/C++ compilation into the editor to create DLLs, EXEs and special EX5 modules out of C++. This will allow existing C++ libraries to be recompiled into EX5 compatible form with minimal rework and will open up access to a lot of opsource libraries.

A very shallow study of the local statistical library leads to the discovery of serious errors. The lack of response to reports of these errors looks very much like "matstat - no!".

Python is unlikely to ever have the variety of packages and the community of analytics practitioners that R has.

 
Aleksey Nikolayev:

A very shallow examination of the local statistical library leads to the discovery of serious errors. The lack of response to reports of these errors looks very much like "matstat - no!

You passed the wrong arguments there yourself and got error messages ERR_ARGUMENTS_INVALID (2).
 
Aleksey Nikolayev:

1) Any CDF - probability distribution function (discrete ones are no exception!) must DEFINITELY be defined for all real numbers. Below is an analogue of the code on R with its result showing how it should be considered in reality. By the way, you have some discrete CDF functions counting correctly and some not.

2) For value 1 you get a division by zero error.

We have an implementation of this function for integers:

//--- m,k,n,x must be integer

Make your own function if you need to. Everything is available in source code, unlike R.

1...282930313233343536373839404142...89
New comment
Reason: