PhythonML MT4

This multicurrency Expert Advisor uses 28 currency pairs. For predictions, the advisor uses models trained by the machine learning algorithm in the Python language environment.

All signals of this advisor in real time and download settings for it can be downloaded from my website forexvisible.com - copy and paste into the browser

This version for the MT4 terminal can work with one time interval H1, the version for MT5 can work with two time intervals H1 and H2, it can be downloaded here https://www.mql5.com/en/market/product/63791

By default, the most profitable 9 pairs out of 28 are selected

The EA was trained from 2007 to 2022, it is necessary to test in the strategy tester from 2022 for Model3 = True, from this period the EA did not know anything about the history during training

The default settings are for the EURUSD H1 currency pair, and use Models3

    Description of some of the EA settings
    • UseSameLotSizeForAllPairs - the ability to select the lot size for each pair separately, true by default, one lot size for all specified by the parameter above
    • UseMaxAllTakeProfitProcent - enables the global take profit as a percentage of the current profit specified in the MaxAllTakeProfitProcent parameter, after its execution all current orders are closed. Test only on all ticks or 1 minute OHLC
    • UseMaxStopLossProcent - turns on the global stop loss as a percentage of the current profit specified in the MaxAllStopLossProcent parameter, after its execution, all current orders are closed. Test only on all ticks or 1 minute OHLC
    • IsDynamicLot - enable automatic formation of the lot size depending on the balance or free margin
    • is_koef_for_each - if true, then the lot size is formed from the balance for each currency pair separately, if false, then from the total balance or free margin
    • koef - coefficient for forming the lot size, the larger, the greater the risks
    • from - formation of the lot size depending on the balance or free margin
    • CountOfGrid - the number of pending orders in the grid
    • GridDistanseBegin - the beginning of the first pending order in the grid from the current price
    • GridDistanseEnd - end of the last pending order in the grid from the current price
    • GridKoefBegin, GridKoefEnd - distribution of coefficients for multiplying the price of a pending order in the grid



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    Profalgo Limited
    5 (5)
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    Vladislav Andruschenko
    3.97 (30)
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    Ivan Simonika
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    Vadim Zotov
    5 (5)
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    Shobhit Dalmia
    2 (1)
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    Yevhen Chystiukhin
    5 (1)
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    Yevhen Chystiukhin
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    4 (11)
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    Yevhen Chystiukhin
    2.8 (5)
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    Yevhen Chystiukhin
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    Yevhen Chystiukhin
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    Yevhen Chystiukhin
    This multi-currency expert advisor uses 28 currency pairs. For predictions, the advisor uses recurrent neural networks of the LSTM type, models trained in the Python language environment, and imported into the advisor using a new function in MQL5 for loading ONNX models. The algorithm of the advisor works simultaneously with two timeframes H15 and H1. Separate neural network models have been trained for each of the 28 pairs for both timeframes. The idea is that the advisor places orders only whe
    AlphaAI
    Yevhen Chystiukhin
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    BetaAI
    Yevhen Chystiukhin
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