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This paper suggests a new approach to evaluate realized covariance (RCOV) estimators via their predictive power on return density. By jointly modeling returns and RCOV measures under a Bayesian framework, the predictive density of returns and ex-post covariance measures are bridged. The forecast...
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This study constructs a Bayesian nonparametric model to investigate whether stock market returns predict real economic growth. Unlike earlier studies, our use of an infinite hidden Markov model enables parameters to be time-varying across an infinite number of Markov-switching states estimated...
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