A Comparison between Bayesian and Frequentist methods in Financial Volatility with Applications to Foreign Exchange Rates

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 generalized autoregressive conditional heteroscedasticity (GARCH) model. Our results indicate that provides better potential than approach. The finding contrary to some work line research. To illustrate our finding, we used six major foreign exchange rate datasets.