Covariance estimation for multivariate conditionally Gaussian dynamic linear models
Article Abstract:
An online, non-iterative Bayesian estimation and forecasting algorithm is proposed. This proposed estimator converges well with true values provided by the unknown observation covariance matrix. London metal exchange data for aluminum, copper, lead, and zinc show superiority of the time varying vector autoregressive model.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 2007
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Evaluating the forecast densities of linear and non-linear models: applications to output growth and unemployment
Article Abstract:
Research is presented describing the use of forecast density evaluations to determine changes in statistical information of both non-linear and linear type models.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 2000
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A quantile regression neural network approach to estimating the conditional density of multiperiod returns
Article Abstract:
Research is presented describing the study of neural network techniques to determine conditional density for financial returns.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 2000
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