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  1. Rebuy algorithm: Multicurrency trading simulation

    by , 07-31-2023 at 02:35 AM
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    In the previous article I showed you a lot of useful features that you probably did not know, but the most interesting thing is ahead - research or trading simulation. Sometimes a strategy tester is not enough. Although this is a very convenient tool for getting to know the market, but this is only the first step. If you carefully read the previous article, then you most likely know the reason already.
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  2. How to use ONNX models in MQL5

    by , 07-30-2023 at 02:12 AM
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    Among all the considered models, CNN-LSTM models have generated the best results during the experiments. In this article, we will consider how to create such a model to forecast financial timeseries and how to use the created ONNX model in an MQL5 Expert Advisor.
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  3. Category Theory in MQL5 (Part 11): Graphs

    by , 07-29-2023 at 02:12 AM
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    In our previous article, we delved into monoid groups, by exploring concept of symmetry within typical monoids. In introducing an additional axiom that all members of a monoid group must possess an inverse and restricting binary operations between mirror elements to yield the identity element, we extended applicability of monoids at crucial trade decision points. Building upon this, we now continue our study of category theory and its practical applications
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  4. MT5 version of famous WmiFor forecasting indicator

    by , 07-23-2023 at 02:36 AM
    This is MT5 version of famous WmiFor forecasting indicator -
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    WmiFor 3.5 for MT5 (with DTW engine) - indicator for MetaTrader 5

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    This indicator predicts possible future price movements by searching for similar candle patterns in the rate history.
    This is an adaptation of original indicator WmiFor 3.0 (with dynamic time warping engine, DTW) for MetaTrader 4 .
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  5. Gold Dust EA

    by , 07-22-2023 at 02:35 AM
    Gold Dust - expert for MetaTrader 5

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    The trading system is based on the future price direction forecast, which is implemented by selecting weight coefficients of an elementary single-layer neural network.
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