Algorithm for identifying suspicious financial transactions in the financial market
Rubrics: SCIENTIFIC ARTICLES
Authors:
1.
Moscow International Academy
graduate student
Russian Federation
graduate student
Russian Federation
2.
Moscow University of Finance and Law
graduate student
graduate student
3.
Moscow University of Finance and Law
(docent)
employee
employee
Type:
Article
Pages:
from 203
to 209
Status:
Published
Received:
25.11.2025
Accepted:
03.12.2025
Published:
03.12.2025
Subject area:
UDC 331
Language:
Russian
Keywords:
: investment risk, market manipulation, algorithm for identifying suspicious financial transactions, digital experimental verification, price trends, modeling
Abstract (English):
The article describes the experimental confirmation of the efficiency of the algorithm for identifying suspicious financial transactions in the financial market, developed to detect market manipulation. The relevance of the study lies in the interest of financial market participants in the ongoing search for opportunities to reduce investment risks when acquiring large blocks of securities for long-term investment in the context of fundamental incompleteness and uncertainty of information about the future movement of the market over a long investment horizon. To make the results of the study more convincing, the experimental verification of the algorithm was carried out on numbers that model price trends, but describe events that do not depend on human influence - on numbers composed of the first 240 digits of π and on the numbers of protons and neutrons in the nuclei of atoms of chemical elements included in the Periodic Table. The analysis of the obtained results confirmed the correctness and efficiency of the algorithm.
The article describes the experimental confirmation of the efficiency of the algorithm for identifying suspicious financial transactions in the financial market, developed to detect market manipulation. The relevance of the study lies in the interest of financial market participants in the ongoing search for opportunities to reduce investment risks when acquiring large blocks of securities for long-term investment in the context of fundamental incompleteness and uncertainty of information about the future movement of the market over a long investment horizon. To make the results of the study more convincing, the experimental verification of the algorithm was carried out on numbers that model price trends, but describe events that do not depend on human influence - on numbers composed of the first 240 digits of π and on the numbers of protons and neutrons in the nuclei of atoms of chemical elements included in the Periodic Table. The analysis of the obtained results confirmed the correctness and efficiency of the algorithm.
Keywords:
: investment risk, market manipulation, algorithm for identifying suspicious financial transactions, digital experimental verification, price trends, modeling
: investment risk, market manipulation, algorithm for identifying suspicious financial transactions, digital experimental verification, price trends, modeling
1. The List: Forbes Global. The World's Largest Public Companies. (daty obrascheniya 15 maya 2019 – 2024 godov)
2. Kuz'min A.V., Kurlyandskiy V.V. Prognozirovanie dinamiki stoimosti krupnyh paketov akciy, vybiraemyh dlya dolgosrochnogo investirovaniya, v usloviyah suschestvovaniya global'nyh subrynkov akciy, funkcioniruyuschih v rezhime DARK POOL // Vestnik MGPU. Seriya "Ekonomicheskie nauki". 2024 № 2 (40), 90-98, https://doihttps://doi.org/10.25688/2312-6647.2024.40.2.07
3. Periodic Table of elements, 2025 – URL: https://ru.periodic-table.io/ (data obrascheniya 09.09.25).
