＊＊mql4とはFXの自動売買のプログラム言語です＊＊

質問は下記。

You are a programmer who develops automated forex trading.

Using mql4, teach mql4 code that uses deep learning!

結果は以下。

Sure, I can provide a brief introduction to developing mql4 code that utilizes deep learning techniques.

Deep learning is a subset of machine learning that utilizes artificial neural networks to learn and make predictions from complex data. It is a powerful technique that has been widely adopted in various fields, including finance and forex trading.

To use deep learning in mql4, you will need to incorporate a neural network library into your code. There are several neural network libraries available for mql4, including FANN and TensorFlow.

Once you have installed the library, you can begin to define and train your neural network. This involves specifying the number of layers, nodes, and activation functions that your network will use. You will also need to provide your network with a dataset to learn from, which should include historical forex data and any relevant technical indicators.

After training your network, you can use it to make predictions on future forex prices. This involves inputting current market data into your network and using it to generate a prediction of future prices.

Here's an example of mql4 code that uses a neural network to predict future forex prices:

mql4Copy code#property strict

// Include neural network library
#include <fann\src\include\fann.h>

// Define input and output data
double inputs[][2] = {{0.5, 0.4}, {0.3, 0.2}, {0.1, 0.3}, {0.2, 0.5}};
double outputs[] = {0.6, 0.5, 0.4, 0.7};

void OnTick()
{
    // Create neural network
    struct fann *ann = fann_create_standard(3, 2, 3, 1);

    // Train neural network
    fann_train_data *data = fann_create_train_from_callback(4, 2, 1, 
    [](unsigned int index, unsigned int num_input, unsigned int num_output, 
    fann_type *input, fann_type *output)
    {
        memcpy(input, inputs[index], num_input * sizeof(fann_type));
        output[0] = outputs[index];
    });
    fann_train_on_data(ann, data, 1000, 10, 0.01);

    // Predict future price
    double current_price = MarketInfo(Symbol(), MODE_BID);
    double future_price = fann_run(ann, &current_price)[0];

    // Close neural network
    fann_destroy_train(data);
    fann_destroy(ann);
}

In this example, we are training a neural network to predict future forex prices based on two inputs (0.5 and 0.4, for example). The neural network has three layers (input, hidden, and output) and is trained using the backpropagation algorithm. We then use the trained network to predict the future price of a currency pair based on the current bid price.

This is just a basic example, and there are many more advanced techniques and strategies that can be used to develop effective deep learning models for forex trading. However, it should give you a good starting point for incorporating deep learning into your mql4 code.

なかなかよきよき。