{"title":"金融市场中的博弈论优化整合:基于 TCCM 框架的系统性文献综述","authors":"Aritra Ganti, Shubham Singhania","doi":"10.1108/jm2-04-2024-0114","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>While being integrated together conceptually and practically, the literature on game theory in the context of financial markets lacks a cohesive understanding. This study aims to systematically scrutinize and analyse the literature of game theory in the context of financial markets, through a systematic literature review.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>A systematic literature-based approach, through the theories, context, characteristics and methodology (TCCM) framework has been applied to 97 articles, extracted and filtered from two databases, Scopus and Web of Science, for a comprehensive review and understanding of the intellectual development in the domain of game theory and financial markets.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>The review highlighted the most utilitarian theories within the literature, the context of research in terms of countries and industries, four themes which characterize the literature, as well as the methodologies and research designs used in this research domain. The paper also uncovered certain essential areas that present scope for further research.</p><!--/ Abstract__block -->\n<h3>Research limitations/implications</h3>\n<p>While two of the largest indexation databases have been used, some relevant articles may have been excluded due to the restriction of databases and screening criteria, which may lead to the less exploration of several facets of the domain.</p><!--/ Abstract__block -->\n<h3>Practical implications</h3>\n<p>Practically, the paper has implications for multiple stakeholders including traders, businesses and governments. For traders, this paper acts as a guide to entering and understanding the dynamics of financial markets. The review also covers decision-making from the perspective of firms, including venture capitalists. 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引用次数: 0
摘要
目的金融市场背景下的博弈论文献虽然在概念和实践上都融为一体,但却缺乏连贯的理解。本研究旨在通过系统性的文献综述,对金融市场背景下的博弈论文献进行系统性的审视和分析。设计/方法/途径通过理论、背景、特征和方法(TCCM)框架,对从 Scopus 和 Web of Science 两个数据库中提取和筛选出的 97 篇文章进行了系统性的文献综述,以全面回顾和了解博弈论和金融市场领域的知识发展。研究结果该综述强调了文献中最具功利性的理论、国家和行业方面的研究背景、体现文献特点的四个主题以及该研究领域所使用的方法和研究设计。研究局限/意义虽然本文使用了两个最大的索引数据库,但由于数据库和筛选标准的限制,一些相关文章可能被排除在外,这可能导致对该领域多个方面的探索较少。对于交易者而言,本文可作为进入和了解金融市场动态的指南。本文还从企业(包括风险资本家)的角度对决策进行了评述。本文将使企业了解博弈论如何帮助影响或分析其利益相关者之间在信息披露方面的战略互动,或消费者及其对企业行为刺激的行为。 原创性/价值 据作者所知,本研究是首部试图全面概述金融市场博弈论文献的同类研究。这样,本研究将有助于评估该领域的知识现状,并找出文献中的空白,从而提出新的研究方向。
Integration of game theory optimization in financial markets: a systematic literature review based on TCCM framework
Purpose
While being integrated together conceptually and practically, the literature on game theory in the context of financial markets lacks a cohesive understanding. This study aims to systematically scrutinize and analyse the literature of game theory in the context of financial markets, through a systematic literature review.
Design/methodology/approach
A systematic literature-based approach, through the theories, context, characteristics and methodology (TCCM) framework has been applied to 97 articles, extracted and filtered from two databases, Scopus and Web of Science, for a comprehensive review and understanding of the intellectual development in the domain of game theory and financial markets.
Findings
The review highlighted the most utilitarian theories within the literature, the context of research in terms of countries and industries, four themes which characterize the literature, as well as the methodologies and research designs used in this research domain. The paper also uncovered certain essential areas that present scope for further research.
Research limitations/implications
While two of the largest indexation databases have been used, some relevant articles may have been excluded due to the restriction of databases and screening criteria, which may lead to the less exploration of several facets of the domain.
Practical implications
Practically, the paper has implications for multiple stakeholders including traders, businesses and governments. For traders, this paper acts as a guide to entering and understanding the dynamics of financial markets. The review also covers decision-making from the perspective of firms, including venture capitalists. This paper would allow firms to understand how game theory can help influence or analyze the strategic interactions between their stakeholders in terms of information disclosure, or consumers and their behavior to stimuli from the firm’s actions.
Originality/value
To the best of the authors’ knowledge, this study is the first of its kind that attempts to comprehensively provide an overview of the literature on game theory in financial markets. In doing so, this study shall help assess the current state of knowledge in the said field and locate gaps in the literature to propose new research directions.
期刊介绍:
Journal of Modelling in Management (JM2) provides a forum for academics and researchers with a strong interest in business and management modelling. The journal analyses the conceptual antecedents and theoretical underpinnings leading to research modelling processes which derive useful consequences in terms of management science, business and management implementation and applications. JM2 is focused on the utilization of management data, which is amenable to research modelling processes, and welcomes academic papers that not only encompass the whole research process (from conceptualization to managerial implications) but also make explicit the individual links between ''antecedents and modelling'' (how to tackle certain problems) and ''modelling and consequences'' (how to apply the models and draw appropriate conclusions). The journal is particularly interested in innovative methodological and statistical modelling processes and those models that result in clear and justified managerial decisions. JM2 specifically promotes and supports research writing, that engages in an academically rigorous manner, in areas related to research modelling such as: A priori theorizing conceptual models, Artificial intelligence, machine learning, Association rule mining, clustering, feature selection, Business analytics: Descriptive, Predictive, and Prescriptive Analytics, Causal analytics: structural equation modeling, partial least squares modeling, Computable general equilibrium models, Computer-based models, Data mining, data analytics with big data, Decision support systems and business intelligence, Econometric models, Fuzzy logic modeling, Generalized linear models, Multi-attribute decision-making models, Non-linear models, Optimization, Simulation models, Statistical decision models, Statistical inference making and probabilistic modeling, Text mining, web mining, and visual analytics, Uncertainty-based reasoning models.