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  • 标题:Mapping the Trend, Application and Forecasting Performance of Asymmetric GARCH Models: A Review Based on Bibliometric Analysis
  • 本地全文:下载
  • 作者:Neenu Chalissery ; Suhaib Anagreh ; Mohamed Nishad T.
  • 期刊名称:Journal of Risk and Financial Management
  • 印刷版ISSN:1911-8074
  • 出版年度:2022
  • 卷号:15
  • 期号:9
  • 页码:1-23
  • DOI:10.3390/jrfm15090406
  • 语种:English
  • 出版社:MDPI, Open Access Journal
  • 摘要:The past few years have witnessed renewed interest in modelling and forecasting asymmetry in financial time series using a variety of approaches. The most intriguing of these strategies is the “asymmetric” or “leverage” volatility model. This study aims to conduct a review of asymmetric GARCH models using bibliometric analysis to identify their key intellectual foundations and evolution, and offers thematic and methodological recommendations for future research to advance the domain. Bibliometric analysis was used to identify patterns in and perform descriptive analysis of articles, including citation, co-authorship, bibliographic coupling, and co-occurrence analysis. The study located 856 research papers from the Scopus database between 1992 and 2021 using key phrase and reference search methods. Publication trends, most influential authors, leading countries, and top journals are described, along with a systematic review of highly cited articles. The study summarises the development, application, and performance evaluation of asymmetric GARCH models, which will help researchers and academicians significantly contribute to this literature by addressing gaps.
  • 关键词:asymmetric GARCH models;bibliometric analysis;literature review
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