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.

United Kingdom, Securities and Commodity Exchanges, Science & research, Security and commodity exchanges, Commodity Exchanges, Models, Spot market, Time-series analysis, Time series analysis, Analysis of covariance, Covariance analysis, Report

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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.

Economic forecasting, Nonlinear functional analysis

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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.

Methods, Computer networks, Neural networks, Return on investment, Rate of return

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