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A Comparison between Bayesian and Frequentist methods in Financial Volatility with Applications to Foreign Exchange Rates
Volume 17, Issue 3 (2019), pp. 593–612
Steve S. Chung   Jalen Harris   Christopher Newmark     All authors (4)

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https://doi.org/10.6339/JDS.201907_17(3).0008
Pub. online: 4 August 2022      Type: Research Article      Open accessOpen Access

Published
4 August 2022

Abstract

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.

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Keywords
Bayesian Financial time series Foreign exchange rates Frequentist Volatility

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