Effects of chief economists in financial institutions on capital market development

In this paper, we investigate the effects of chief economists employed by securities companies on the development of capital market. Utilizing securities companies in China from 2006 to 2022 as the research subjects, the paper employs Python algorithms to construct an index of chief economists and c...

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Vydáno v:International review of financial analysis Ročník 105; s. 104403
Hlavní autoři: He, Muyuan, Chen, Aizhen, Han, Yutong, He, Chengying, Geng, Xiaoxu
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Inc 01.09.2025
Témata:
Capital market
Chief economist
Gradient boosting tree model
Random Forest model
Chief economist
Capital market
Gradient boosting tree model
Random Forest model
ISSN:1057-5219
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Shrnutí:In this paper, we investigate the effects of chief economists employed by securities companies on the development of capital market. Utilizing securities companies in China from 2006 to 2022 as the research subjects, the paper employs Python algorithms to construct an index of chief economists and combines the Douglas function to deduce the conclusion that chief economists have played a positive role in the process where securities companies serve the capital market. Among them, the higher the social influence and the stronger the research ability are, the more prominent the professional ability of chief economists becomes, and the more effective the service of securities companies to the capital market is. Additionally, machine learning models such as decision trees and random forests disclose the non-linear characteristics of the impact of the chief economist system on the effectiveness of securities companies in serving the capital market. The conclusion of this paper furnishes valuable evidence for securities companies of this kind to leverage their own resources to advance the development of the capital market and also expands the economic effects brought about by the chief economist system for society. •Reveal the inherent logic of financial institutions and companies serving the capital market.•Random forest machine learning comprehensively captures the nonlinear characteristics of the chief economist effect.•Reputation, information transmission and knowledge spillover are the main ways of the chief economist effect.
ISSN:1057-5219
DOI:10.1016/j.irfa.2025.104403