基于机器学习的越南证券交易市场政治关联聚类研究

IF 1.3 Q3 ECONOMICS
Can Dinh Ngoc, Tam Phan Huy, Tu Ta Thi Cam, Tam Luong Thi My, Hien Nguyen Thi Thuy, Minh Ngo Hai
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引用次数: 0

摘要

本文旨在使用机器学习对政治附属团体进行聚类。本研究使用的样本为胡志明市和河内证券交易所上市企业,研究数据为2015年至2020年。本研究使用的数据包括国有持股比例、企业领导人的政治关联度以及企业上市财务报表中的财务指标。作者的研究通过K-means算法测量政治联系,然后将K-means聚类结果与传统的人工测量政治联系的方法进行比较,包括0和1两个值,其中0表示无政治派别,1表示有政治派别。同时,笔者运行三个集群进行深入的洞察。作者得出结论,使用k-means模型的机器学习聚类可以取代传统的方法。在HOSE和HNX上市的具有政治关系的企业在投资活动、获取资源和资金方面给企业带来了许多好处;然而,这对企业业绩有负面影响。作者建议,适度的政治关系将有助于企业取得更好的业绩。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Political Affiliate Clustering with Machine Learning in Vietnam Stock Exchange Market
This paper aims to cluster politically affiliated groups using machine learning. The sample used in the study is enterprises listed on the stock exchanges of Ho Chi Minh City and Hanoi, research data during the period from 2015 to 2020. Data used in the study include state ownership ratio, the degree of political connection of business leaders and financial indicators in the listed financial statements of enterprises. The author’s study measures political connection by K-means algorithm and then compares the results of the K-means clustering with the traditional method of manual measurement of political connection including two values of 0 and 1, where 0 is no political affiliation and 1 is political affiliation. At the same time, the author runs three clusters to have in-depth insight. The authors conclude that machine learning clustering using the k-means model can replace the traditional method. Politically connected businesses listed on HOSE and HNX with political connections bring many benefits to businesses in investment activities, in accessing resources as well as capital; however, that businesses have a negative impact on business performance. The authors recommend that a moderate degree of political affiliation will help businesses achieve better performance.
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来源期刊
CiteScore
1.50
自引率
0.00%
发文量
18
期刊介绍: Journal of International Commerce, Economics and Policy (JICEP) is a peer-reviewed journal that seeks to publish high-quality research papers that explore important dimensions of the global economic system (including trade, finance, investment and labor flows). JICEP is particularly interested in potentially influential research that is analytical or empirical but with heavy emphasis on international dimensions of economics, business and related public policy. Papers must aim to be thought-provoking and combine rigor with readability so as to be of interest to both researchers as well as policymakers. JICEP is not region-specific and especially welcomes research exploring the growing economic interdependence between countries and regions.
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