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  1. MetaTrader 5 for macOS: ready-made DMG package and CrossOver update

    by , 04-09-2021 at 03:22 PM
    We have recently released a DMG package for easy MetaTrader 5 installation on macOS computers. With this package, the platform can be installed similarly to any other application: simply drag the platform icon to Applications and wait for the installation to complete.
    more..
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  2. Developing a self-adapting algorithm (Part I): Finding a basic pattern

    by , 02-08-2021 at 02:34 PM
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    Any trading algorithm is generally a tool which may bring profit to an experienced trader or instantly destroy a deposit of an inexperienced one. The issue of creating a profitable and reliable algorithm is that we cannot understand what needs to be done in order to earn money and what methods are used by "successful traders". While HFT, arbitrage, option strategies and calendar spread-based systems boast a solid theoretical basis clearly stating what
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  3. Two iRSI in one subwindow - indicator for MetaTrader 5

    by , 01-26-2021 at 05:18 PM
    Two iRSI in one subwindow - indicator for MetaTrader 5

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Views: 32
Size:  28.3 KB

    Place two iRSI (Relative Strength Index, RSI) indicators - ' Fast ' and ' Slow ' in one subwindow. Moreover, each indicator has independent parameters:
    • XXXX averaging period - averaging period
    • XXXX type of price - price type
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  4. MACD Threshold Value Alert

    by , 01-20-2021 at 07:41 AM
    MACD Threshold Value Alert - indicator for MetaTrader 5

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Views: 30
Size:  22.2 KB

    Development of the MACD Threshold Value version. When a signal line is found above or below one of the ' Threshold ' lines, an alert is triggered.
    IMACD (Moving Average Convergence / Divergence, MACD) indicator with two levels (two threshold values). The levels are displayed as lines, but are drawn by indicator buffers.
  5. Practical application of neural networks in trading. Python (Part I)

    by , 01-06-2021 at 07:17 AM
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Views: 48
Size:  55.2 KB

    In the previous article entitled "Practical application of neural networks in trading. It's time to practice", we considered the practical application of a neural network module implemented using Matlab neural networks. However, that article did not cover questions related to the preparation of input data and network training related operations. In this article, we will consider these questions using examples and will implement further code using
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