基于金融指标的国家分类智能代理

P. S. D. M. Neto, Rosilda B. Souza, George D. C. Cavalcanti, T. Ferreira
{"title":"基于金融指标的国家分类智能代理","authors":"P. S. D. M. Neto, Rosilda B. Souza, George D. C. Cavalcanti, T. Ferreira","doi":"10.1109/BRICS-CCI-CBIC.2013.44","DOIUrl":null,"url":null,"abstract":"Traditionally, the countries classification is performed based on several features, that are related to economic and social factors. However, the classification process is costly due to the difficulty of obtaining those features and the need for intervention of human expertise. In this paper, we propose an intelligent agent that classifies countries based on financial indices. The artificial agent calculates the probability density function (pdf) of the return series of financial indices. This pdf characterizes the fluctuation of a market. Based on the return series and pdf, the volatility and the B coefficient of the exponential function, that describe the behavior of world markets, are estimated. Then, the intelligent agent classifies the indices from developed and developing countries using a Self-Organizing Map (SOM) neural network. The results show that the proposed intelligent agent is an accurate, fast and cheap alternative to the classifications provided by traditional organizations.","PeriodicalId":306195,"journal":{"name":"2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Intelligent Agent to Classify Countries Based on Financial Indices\",\"authors\":\"P. S. D. M. Neto, Rosilda B. Souza, George D. C. Cavalcanti, T. Ferreira\",\"doi\":\"10.1109/BRICS-CCI-CBIC.2013.44\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traditionally, the countries classification is performed based on several features, that are related to economic and social factors. However, the classification process is costly due to the difficulty of obtaining those features and the need for intervention of human expertise. In this paper, we propose an intelligent agent that classifies countries based on financial indices. The artificial agent calculates the probability density function (pdf) of the return series of financial indices. This pdf characterizes the fluctuation of a market. Based on the return series and pdf, the volatility and the B coefficient of the exponential function, that describe the behavior of world markets, are estimated. Then, the intelligent agent classifies the indices from developed and developing countries using a Self-Organizing Map (SOM) neural network. The results show that the proposed intelligent agent is an accurate, fast and cheap alternative to the classifications provided by traditional organizations.\",\"PeriodicalId\":306195,\"journal\":{\"name\":\"2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BRICS-CCI-CBIC.2013.44\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BRICS-CCI-CBIC.2013.44","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

传统上,国家分类是根据几个特征进行的,这些特征与经济和社会因素有关。然而,由于难以获得这些特征和需要人类专业知识的干预,分类过程成本很高。本文提出了一种基于金融指标对国家进行分类的智能代理。人工智能体计算金融指标收益序列的概率密度函数(pdf)。这个图表描述了市场波动的特征。基于收益序列和pdf,估计了描述世界市场行为的指数函数的波动率和B系数。然后,智能体使用自组织地图(SOM)神经网络对发达国家和发展中国家的指标进行分类。结果表明,所提出的智能代理是传统组织提供分类的一种准确、快速、廉价的替代方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
An Intelligent Agent to Classify Countries Based on Financial Indices
Traditionally, the countries classification is performed based on several features, that are related to economic and social factors. However, the classification process is costly due to the difficulty of obtaining those features and the need for intervention of human expertise. In this paper, we propose an intelligent agent that classifies countries based on financial indices. The artificial agent calculates the probability density function (pdf) of the return series of financial indices. This pdf characterizes the fluctuation of a market. Based on the return series and pdf, the volatility and the B coefficient of the exponential function, that describe the behavior of world markets, are estimated. Then, the intelligent agent classifies the indices from developed and developing countries using a Self-Organizing Map (SOM) neural network. The results show that the proposed intelligent agent is an accurate, fast and cheap alternative to the classifications provided by traditional organizations.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Computer Simulations of Small Societies Under Social Transfer Systems Modeling of Reasoning in Intelligent Systems by Means of Integration of Methods Based on Case-Based Reasoning and Inductive Notions Formation Bi-dimensional Neural Equalizer Applied to Optical Receiver A New Algorithm Based on Differential Evolution for Combinatorial Optimization A Cooperative Parallel Particle Swarm Optimization for High-Dimension Problems on GPUs
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1