M.V. Khramtsov1, R.A. Kochkarov2, A.A. Rylov3

1−3 Financial University under the Government of the Russian Federation (Moscow, Russia)

1 maks_future@mail.ru, 2 rkochkarov@fa.ru, 3arylov@fa.ru

In this problem, an approach is proposed to optimize the portfolio by the number of securities booms and preserve their composition using machine learning algorithms. It is proposed to predict the value of securities to make a decision on changing the share in the portfolio. Consider well-known algorithms and propose an automated algorithm for optimizing a portfolio of securities based on machine learning methods.

Existing principles of operation of trading algorithms are considered. The main directions of their application in investment activity are given. Theoretical aspects of portfolio optimization are considered, the distinctive features of trading advisors and their areas of application are highlighted. A model using a neural network is proposed.

The proposed neural network model predicts the future closing price of an asset. For the model, tests were made for the accuracy of forecasting. The model has the ability to quickly change the parameters in order to increase the accuracy of the forecast for a shorter period.

Khramtsov M.V., Kochkarov R.A., Rylov A.A. Portfolio optimization with machine learning. Information-measuring and Control Systems. 2023. V. 21. № 5. P. 48−55. DOI: https://doi.org/10.18127/j20700814-202305-06 (in Russian)

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