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forecasting the term structure of interest rates. As expected, I find that using more flexible models leads to a better in …
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wholesale power markets have only recently been deregulated. We introduce the weather factor into well-known forecasting models …
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We present new results for the likelihood-based analysis of the dynamic factor model that possibly includes intercepts and explanatory variables. The latent factors are modelled by stochastic processes. The idiosyncratic disturbances are specified as autoregressive processes with mutually...
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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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variancefunctions. In a genuine out-of-sample forecasting experiment theperformance of the best fitted asMA-asQGARCH model is compared … topure asMA and no-change forecasts. This is done both in terms ofconditional mean forecasting as well as in terms of risk … forecasting. …
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In this paper we present an exact maximum likelihood treatment forthe estimation of a Stochastic Volatility in Mean(SVM) model based on Monte Carlo simulation methods. The SVM modelincorporates the unobserved volatility as anexplanatory variable in the mean equation. The same extension...
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