Model-free forecasting for nonlinear time series (with application to exchange rates)

DOI10.1016/0167-9473(94)00008-7zbMath0875.62432OpenAlexW2018980855MaRDI QIDQ673738

Berlin Wu

Publication date: 28 February 1997

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-9473(94)00008-7

zbMATH Keywords

Neural networksExchange ratesBack-propagation methodBilinear modelsModel-free forecasting

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Inference from stochastic processes and prediction (62M20)

Related Items

An investigation of neural networks for linear time-series forecasting ⋮ Using genetic algorithms to parameters \((d,r)\) estimation for threshold autoregressive models ⋮ Recurrent support vector regression for a non-linear ARMA model with applications to forecasting financial returns

Cites Work

• An introduction to bispectral analysis and bilinear time series models
• Volterra series and geometric control theory
• Multilayer feedforward networks are universal approximators
• SOME DOUBLY STOCHASTIC TIME SERIES MODELS
• Testing linearity against smooth transition autoregressive models
• Consequences and Detection of Misspecified Nonlinear Regression Models
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• STATE-DEPENDENT MODELS: A GENERAL APPROACH TO NON-LINEAR TIME SERIES ANALYSIS
• TESTING FOR GAUSSIANITY AND LINEARITY OF A STATIONARY TIME SERIES
• On the identification problem for bilinear time series models
• Learning representations by back-propagating errors
• Approximation by superpositions of a sigmoidal function
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item