经济学中的多主体技术

Q1 Economics, Econometrics and Finance

Intelligent Systems in Accounting, Finance and Management Pub Date : 2017-09-27 DOI:10.1002/isaf.1415

Javier Bajo, Philippe Mathieu, María José Escalona

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引用次数: 5

摘要

本文总结了经济学中使用多主体技术的一些趋势。多智能体系统、模糊集和神经网络是研究与数据挖掘、动态市场股票选择和银行压力测试相关的新兴经济学研究议程的关键工具。本文回顾了这四个例子的贡献。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Multi-agent technologies in economics

This paper summarizes some of the trends in the use of multi-agent technologies in economics. Multiple agent systems, fuzzy sets and neural networks are critical tools used to investigate the emerging economics research agenda related to data mining, dynamic markets stock selection and bank stress testing. This paper reviews the contributions of four such examples.

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来源期刊

Intelligent Systems in Accounting, Finance and Management Economics, Econometrics and Finance-Finance

CiteScore

6.00

自引率

0.00%

发文量

期刊介绍： Intelligent Systems in Accounting, Finance and Management is a quarterly international journal which publishes original, high quality material dealing with all aspects of intelligent systems as they relate to the fields of accounting, economics, finance, marketing and management. In addition, the journal also is concerned with related emerging technologies, including big data, business intelligence, social media and other technologies. It encourages the development of novel technologies, and the embedding of new and existing technologies into applications of real, practical value. Therefore, implementation issues are of as much concern as development issues. The journal is designed to appeal to academics in the intelligent systems, emerging technologies and business fields, as well as to advanced practitioners who wish to improve the effectiveness, efficiency, or economy of their working practices. A special feature of the journal is the use of two groups of reviewers, those who specialize in intelligent systems work, and also those who specialize in applications areas. Reviewers are asked to address issues of originality and actual or potential impact on research, teaching, or practice in the accounting, finance, or management fields. Authors working on conceptual developments or on laboratory-based explorations of data sets therefore need to address the issue of potential impact at some level in submissions to the journal.