预测分析在金融中的应用

Q1 Mathematics
Daniel Broby
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引用次数: 0

摘要

统计和计算方法正越来越多地集成到决策支持系统中,以帮助管理和帮助战略决策。研究人员需要充分了解这些技术的使用,以便在使用财务数据时做出预测。因此,本文提出了一种基于预测分析领域的文献综述方法。该研究全面涵盖了分类、回归、聚类、关联和时间序列模型。它将现有的解释性统计模型扩展到计算模型的领域。所探索的方法可以通过分析在信息系统中收集、存储和处理的金融时间序列和横截面数据来预测未来。这些模型的输出使财务经理和风险监督专业人员能够取得更好的结果。本文综述了金融领域的各种预测分析方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The use of predictive analytics in finance

Statistical and computational methods are being increasingly integrated into Decision Support Systems to aid management and help with strategic decisions. Researchers need to fully understand the use of such techniques in order to make predictions when using financial data. This paper therefore presents a method based literature review focused on the predictive analytics domain. The study comprehensively covers classification, regression, clustering, association and time series models. It expands existing explanatory statistical modelling into the realm of computational modelling. The methods explored enable the prediction of the future through the analysis of financial time series and cross-sectional data that is collected, stored and processed in Information Systems. The output of such models allow financial managers and risk oversight professionals to achieve better outcomes. This review brings the various predictive analytic methods in finance together under one domain.

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来源期刊
Journal of Finance and Data Science
Journal of Finance and Data Science Mathematics-Statistics and Probability
CiteScore
3.90
自引率
0.00%
发文量
15
审稿时长
30 days
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