| Issue |
ITM Web Conf.
Volume 72, 2025
III International Workshop on “Hybrid Methods of Modeling and Optimization in Complex Systems” (HMMOCS-III 2024)
|
|
|---|---|---|
| Article Number | 01002 | |
| Number of page(s) | 8 | |
| Section | Advances in Hybrid Modeling and Optimization Techniques | |
| DOI | https://doi.org/10.1051/itmconf/20257201002 | |
| Published online | 13 February 2025 | |
A modification of Random Forest investment assets selection algorithm
Siberian Federal University, 79, Svobodny Prospect, Krasnoyarsk, 660049, Russian Federation
* Corresponding author: anna-z@mail.ru
The paper presents selecting stocks for an investment portfolio algorithm, alternative to standard mathematical programming optimal portfolio methods. To implement the algorithm, a modification of the Random Forest machine learning model is proposed. At the first step, the algorithm builds a decision tree based on forecasts using the naive method and the ARIMA method, and then it forms a “forest” of trees from random subsamples. The algorithm was tested on different time intervals on the instruments of two exchange indices. Its implementation showed good results - at least 78% of the selected stocks increased in price over the forecast period.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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