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Metatrader 5 / Metatrader 4 for MQL5 / MQL4 articles preview

This is a discussion on Metatrader 5 / Metatrader 4 for MQL5 / MQL4 articles preview within the General Discussion forums, part of the Trading Forum category; Experienced traders are well aware of the fact that most time-consuming things in trading are not opening and tracking positions ...

          
   
  1. #251
    Senior Member mql5's Avatar
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    Developing the symbol selection and navigation utility in MQL5 and MQL4

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    Experienced traders are well aware of the fact that most time-consuming things in trading are not opening and tracking positions but selecting symbols and looking for entry points.
    Of course, these are not huge issues if you work only with 1-2 symbols. But if your trading toolkit consists of hundreds of stocks and dozens of Forex symbols, it may take several hours only to find suitable entry points.

    In this article, we will develop an EA simplifying the search for stocks. The EA is to be helpful in three ways:
    • it is to pre-filter stocks providing us with a list of the ones that meet our conditions;
    • is should simplify navigation through the generated stock list;
    • it is to display additional data necessary to make a decision.

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  2. #252
    Senior Member mql5's Avatar
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  3. #253
    Senior Member mql5's Avatar
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    Practical Use of Kohonen Neural Networks in Algorithmic Trading. Part I. Tools

    The subject of Kohonen neural networks was approached to in some articles on the mql5.com website, such as Using Self-Organizing Feature Maps (Kohonen Maps) in MetaTrader 5 and Self-Organizing Feature Maps (Kohonen Maps) - Revisiting the Subject. They introduced readers to the general principles of building neural networks of this type and visually analyzing the economic numbers of markets using such maps.


    However, in practical terms, using Kohonen networks just for algorithmic trading has been confined with only one approach, namely the same visual analysis of topology maps built for the EA optimization results. In this case, one's value judgment, or rather one's vision and ability to draw reasonable conclusions from a picture turns out to be, perhaps, the crucial factor, sidelining the network properties regarding representing data in terms of nuts-and-bolts matters.


    In other words, the features of neural network algorithms were not used to the full, i.e., they were used without automatically extracting knowledge or supporting decision making with specific recommendations. In this paper, we consider the problem of defining the optimal sets of robots' parameters in a more formalized manner. Moreover, we are going to apply Kohonen network to forecasting economic ranges. However, before proceeding to these applied problems, we should revise the existing source codes, get something fixed, and make some improvements.


    It is highly recommended to read the above articles first, if you are not familiar with the terms such as 'network', 'layer', 'neuron' ('node'), 'link', 'weight', 'learning rate', 'learning range', and other notions related to Kohonen networks. Then we will have to saturate ourselves in this matter, so re-teaching the basic notions would lengthen this publication significantly.
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  4. #254
    Senior Member mql5's Avatar
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    Analyzing trading results using HTML reports

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    If a trader is trying to attract investors, it is very likely that they will want to check his or her trading results. So a trader should be able to present trading history to demonstrate the results. The MetaTrader 5 allows saving the trading history to a file (Toolbox — Trading tab — context menu — Report). A report can be saved as XLSX (to be analyzed in Microsoft Excel) and as HTML files which can be viewed in any browsers. The second option is obviously more popular, since some users may not have Excel, while everyone has a browser. Therefore, an HTML report with trading results would be more suitable for a potential investor.


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  5. #255
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    Applying Monte Carlo method in reinforcement learning

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    In the previous article, we considered the Random Decision Forest algorithm and wrote a simple self-learning EA based on Reinforcement learning.
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  6. #256
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    Practical application of correlations in trading

    Correlation is a statistical relationship between two or more random variables (or quantities which can be considered random with some acceptable degree of accuracy). Changes in one ore more variables lead to systematic changes of other related variables. The mathematical measure of the correlation of two random variables is the correlation coefficient. If a change in one random variable does not lead to a regular change in the other random variable but leads to a change in another statistical characteristic of this random variable, such a relation is not considered correlation, although it is statistical.
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