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Multiple time series forecasting using quasi-randomized functional link neural networks
Moudiki, Thierry; Planchet, Frédéric; Cousin, Areski - In: Risks 6 (2018) 1, pp. 1-20
We are interested in obtaining forecasts for multiple time series, by taking into account the potential nonlinear relationships between their observations. For this purpose, we use a specific type of regression model on an augmented dataset of lagged time series. Our model is inspired by dynamic...
Persistent link: https://www.econbiz.de/10011996579
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Moody's ratings statistical forecasting for industrial and retail firms
Caridad y López del Río, Lorena; García-Moreno … - In: Economies 9 (2021) 4, pp. 1-15
Long-term ratings of companies are obtained from public data plus some additional nondisclosed information. A model based on data from firms' public accounts is proposed to directly obtain these ratings, showing fairly close similitude with published results from Credit Rating Agencies. The...
Persistent link: https://www.econbiz.de/10013199892
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Machine learning advances for time series forecasting
Masini, Ricardo P.; Medeiros, Marcelo C.; Mendes, Eduardo F. - 2020
series forecasting. We consider both linear and nonlinear alternatives. Among the linear methods we pay special attention to …
Persistent link: https://www.econbiz.de/10012817069
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Nonlinear inflation forecasting with recurrent neural networks
Almosova, Anna; Andresen, Niek - In: Journal of Forecasting 42 (2022) 2, pp. 240-259
time‐series in general and inflation in particular, we investigate if the forecasting performance can be improved even …
Persistent link: https://www.econbiz.de/10014503715
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Forecasting with artificial network models
Rech, Gianluigi - 2002
This paper contains a forecasting exercise on 30 time series, ranging on several fields, from economy to ecology. The … statistical approach to artificial neural networks modelling developed by the author is compared to linear modelling and to other … three well-known neural network modelling procedures: Information Criterion Pruning (ICP), Cross-Validation Pruning (CVP …
Persistent link: https://www.econbiz.de/10010281250
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Complexity: A review of the classics
Furtado, Bernardo Alves; Sakowski, Patrícia Alessandra … - 2014
This text was written as part of the project "Modelling of Complex Systems for Public Policy". It reviews the classical …
Persistent link: https://www.econbiz.de/10011372139
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Complexidade: Uma revisão dos clássicos
Furtado, Bernardo Alves; Sakowski, Patrícia Alessandra … - 2014
This text was written as part of the project "Modelling of Complex Systems for Public Policy". It reviews the classical …
Persistent link: https://www.econbiz.de/10011372350
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Complexity: A review of the classics
Furtado, Bernardo Alves; Sakowski, Patrícia Alessandra … - 2015
This text was written as part of the project Modelling of Complex Systems for Public Policy. It reviews the classical …
Persistent link: https://www.econbiz.de/10012234215
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Modelling and Simulation: An Overview
McAleer, Michael; Chan, Felix; Oxley, Les - 2013
through the comparison of simultaneous and sequential estimation, modelling tail credit risk using transition matrices … underwriters and issuing firms in the Japanese corporate bond market, stochastic life table forecasting: a time-simultaneous fan …
Persistent link: https://www.econbiz.de/10010326266
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The effectiveness of central bank purchases of long-term treasury securities: A neural network approach
Tänzer, Alina - 2024
Central bank intervention in the form of quantitative easing (QE) during times of low interest rates is a controversial topic. This paper introduces a novel approach to study the effectiveness of such unconventional measures. Using U.S. data on six key financial and macroeconomic variables...
Persistent link: https://www.econbiz.de/10014533855