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A New Bootstrapped Hybrid Artificial Neural Network Approach for Time Series Forecasting · Study

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ArticleA New Bootstrapped Hybrid Artificial Neural Network Approach for Time Series Forecasting

Erol Eğrioğlu2020

Article2020

A New Bootstrapped Hybrid Artificial Neural Network Approach for Time Series Forecasting

Erol Eğrioğlu · Robert A. Fildes

25 citations·0/0 files stored·Computational Economics

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Forecasting Techniques and Applications Neural Networks and Applications Stock Market Forecasting Methods

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References

2019A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting 2018The M4 Competition: Results, findings, conclusion and way forward 2003Efficient market hypothesis and forecasting 1993Testing for neglected nonlinearity in time series models 2014Neural network ensemble operators for time series forecasting 2011Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction 2000Automatic neural network modeling for univariate time series 2003Neural network forecasts of Canadian stock returns using accounting ratios

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Year2020

Typearticle

Published2020-11-20

VenueComputational Economics

ISSN-L0927-7099

Languageen

Citations25

Files0 public / 0

ShelfForecasting Techniques and Applications

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doi10.1007/s10614-020-10073-7

openalex_workW3109943945

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