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TOOLS FOR NON-LINEAR TIME SERIES FORECASTING IN ECONOMICS – AN EMPIRICAL COMPARISON OF REGIME SWITCHING VECTOR AUTOREGRESSIVE MODELS AND RECURRENT NEURAL NETWORKS

Binner, Jane M.; Elger, Thomas; Nilsson, Birger; … - In: Applications of artificial intelligence in finance and …, (pp. 71-91). 2004

specific forecasting experiment is U.K. inflation and we utilize monthly data from 1969 to 2003. The RS-VAR and the RNN perform …

Persistent link: https://www.econbiz.de/10015388169

Forecast accuracy of the linear and nonlinear autoregressive models in macroeconomic modeling

Taiebnia, Ali; Mohammadi, Shapour - In: Journal of forecasting 42 (2023) 8, pp. 2045-2062

Persistent link: https://www.econbiz.de/10014432847

Tackling large outliers in macroeconomic data with vector artificial neural network autoregression

Polito, Vito; Zhang, Yunyi - 2021

We develop a regime switching vector autoregression where artificial neural networks drive time variation in the coefficients of the conditional mean of the endogenous variables and the variance covariance matrix of the disturbances. The model is equipped with a stability constraint to ensure...

Persistent link: https://www.econbiz.de/10012668293

Does the macroeconomy predict UK asset returns in a nonlinear fashion? : comprehensive out-of-sample evidence

Guidolin, Massimo; Hyde, Stuart; McMillan, David G.; … - 2010

Persistent link: https://www.econbiz.de/10008668600

Does the macroeconomy predict UK asset returns in an nonlinear fashion? : comprehensive out-of-sample evidence

Guidolin, Massimo; Hyde, Stuart; McMillan, David G.; … - 2010

We perform a comprehensive examination of the recursive, comparative predictive performance of a number of linear and non-linear models for UK stock and bond returns. We estimate Markov switching, threshold autoregressive (TAR), and smooth transition autoregressive (STR) regime switching models,...

Persistent link: https://www.econbiz.de/10008990694

Does the macroeconomy predict UK asset returns in a nonlinear fashion? : comprehensive out-of-sample evidence

Guidolin, Massimo; Hyde, Stuart; McMillan, David G.; … - In: Oxford bulletin of economics and statistics 76 (2014) 4, pp. 510-535

Persistent link: https://www.econbiz.de/10010474888

Forecasting using nonlinear long memory models with artificial neural network expansion

Chaleampong Kongcharoen - In: Uncertainty analysis in econometrics with applications …, (pp. 241-254). 2013

Persistent link: https://www.econbiz.de/10009711144

Addition of subset and dummy variables in the Threshold Spatial Vector Autoregressive with Exogenous Variables Model to forecast inflation and money outflow

Setiawan, Setiawan; Sohibien, Gama Putra Danu; Prastyo, … - In: Economies : open access journal 12 (2024) 12, pp. 1-27

The TSpVARX model can be used in inflation and money outflow forecasting by accommodating the reciprocal relationship … adjustments, still cannot be accommodated in the TSpVARX model. This condition causes inflation and money outflow forecasting … fuel price changes. These additions enhance the model's accuracy in forecasting inflation and money outflow by accounting …

Persistent link: https://www.econbiz.de/10015198420

Machine learning advances for time series forecasting

Masini, Ricardo P.; Medeiros, Marcelo C.; Mendes, Eduardo F. - 2020

In this paper we survey the most recent advances in supervised machine learning and highdimensional models for time series forecasting. We consider both linear and nonlinear alternatives. Among the linear methods we pay special attention to penalized regressions and ensemble of models. The...

Persistent link: https://www.econbiz.de/10012390030

Machine learning advances for time series forecasting

Masini, Ricardo P.; Medeiros, Marcelo C.; Mendes, Eduardo F. - In: Journal of economic surveys 37 (2023) 1, pp. 76-111

Persistent link: https://www.econbiz.de/10014287800