Multi-step forecasts from threshold ARMA models using asymmetric loss functions

DOI10.1007/S10260-007-0044-XzbMath1405.62118OpenAlexW2047030982MaRDI QIDQ635899

Marcella Niglio

Publication date: 25 August 2011

Published in: Statistical Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10260-007-0044-x

zbMATH Keywords

general loss functionslinexnonlinear predictionSETARMA

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (1)

Fitting of self-exciting threshold autoregressive moving average nonlinear time-series model through genetic algorithm and development of out-of-sample forecasts

Cites Work

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• Nonlinear time series. Nonparametric and parametric methods
• The moments of SETARMA models
• Estimation and Testing of Forecast Rationality under Flexible Loss
• Testing Forecast Optimality Under Unknown Loss
• Bayesian Estimation and Prediction Using Asymmetric Loss Functions
• On threshold moving-average models
• Conditional Minimum Volume Predictive Regions for Stochastic Processes
• Prediction with a Generalized Cost of Error Function

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