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With the aim of constructing predictive distributions for daily returns, we introduce a new Markov normal mixture model in which the components are themselves normal mixtures. We derive the restrictions on the autocovariances and linear representation of integer powers of the time series in...
Persistent link: https://www.econbiz.de/10011604877
With the aim of constructing predictive distributions for daily returns, we introduce a new Markov normal mixture model in which the components are themselves normal mixtures. We derive the restrictions on the autocovariances and linear representation of integer powers of the time series in...
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We propose a Bayesian optimal filtering setup for improving out-of-sample forecasting performance when using volatile … high frequency data with long lag structure for forecasting low-frequency data. We test this setup by using real-time Swiss … indicator series for forecasting. …
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