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  • 标题:A COMPARISON BETWEEN BAYESIAN AND FREQUENTIST METHODS IN FINANCIAL VOLATILITY WITH APPLICATIONS TO FOREIGN EXCHANGE RATES
  • 本地全文:下载
  • 作者:Steve S. Chung ; Jalen Harris ; Christopher Newmark
  • 期刊名称:Journal of Data Science
  • 印刷版ISSN:1680-743X
  • 电子版ISSN:1683-8602
  • 出版年度:2019
  • 卷号:17
  • 期号:3
  • 页码:593-612
  • DOI:10.6339/JDS.201907_17(3).0008
  • 出版社:Tingmao Publish Company
  • 摘要:In this paper, a comparison is provided for volatility estimation in Bayesian and frequentist settings. We compare the predictive performance of these two approaches under the generalized autoregressive conditional heteroscedasticity (GARCH) model. Our results indicate that the frequentist estimation provides better predictive potential than the Bayesian approach. The finding is contrary to some of the work in this line of research. To illustrate our finding, we used the six major foreign exchange rate datasets..
  • 关键词:Bayesian; Financial time series; Foreign exchange rates; Frequentist; Volatility
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