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explores various specifications of decompositions and various forecasting experiments. The result from these horse-races is … for richer forecasting specifications, the paper shows, using Bayesian model averaging techniques (BMA), that the …
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Since the advent of Markov chain Monte Carlo (MCMC) methods in the early 1990s, Bayesian methods have been proposed for a large and growing number of applications. One of the main advantages of Bayesian inference is the ability to deal with many different sources of uncertainty, including data,...
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can be used in risk measurement and forecasting. Value at risk (VaR) is a widely used measure of financial risk, which … series analysis conducted and led to the forecasting of the returns. It was noted that these methods could not be used in … relation of assets with each other. Furthermore, we also examined the environment as a whole, then applied forecasting models …
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