期刊论文详细信息
Journal of Data Science | |
A Comparison between Bayesian and Frequentist methods in Financial Volatility with Applications to Foreign Exchange Rates | |
article | |
Steve S. Chung1  Jalen Harris1  Christopher Newmark1  Diana Yeung2  | |
[1] Department of Mathematics, California State University;Department of Mathematics, University of Notre Dame | |
关键词: Bayesian; Financial time series; Foreign exchange rates; Frequentist; Volatility; | |
DOI : 10.6339/JDS.201907_17(3).0008 | |
学科分类:土木及结构工程学 | |
来源: JDS | |
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【 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.
【 授权许可】
CC BY
【 预 览 】
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RO202307150000370ZK.pdf | 1474KB | ![]() |