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A New Bootstrapped Hybrid Artificial Neural Network Approach for Time Series Forecasting
16 references·0 citing·45 second hop
A New Bootstrapped Hybrid Artificial Neural Network Approach for Time Series Forecasting (2020)A New Bootstrapped Hybrid Artificial Neur…A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting (2019)A hybrid method of exponentia…A brief history of forecasting competitions (2019)A brief history of forecastin…The M4 Competition: Results, findings, conclusion and way forward (2018)The M4 Competition: Results, …Classification of intraday S&P500 returns with a Random Forest (2018)Classification of intraday S&…Neural network ensemble operators for time series forecasting (2014)Neural network ensemble opera…Bootstrap prediction intervals for linear, nonlinear and nonparametric autoregressions (2014)Bootstrap prediction interval…Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction (2011)Advances in forecasting with …Forecasting the direction of the US stock market with dynamic binary probit models (2010)Forecasting the direction of …Forecasting with a nonlinear dynamic model of stock returns and industrial production (2004)Forecasting with a nonlinear …Neural network forecasts of Canadian stock returns using accounting ratios (2003)Neural network forecasts of C…Efficient market hypothesis and forecasting (2003)Efficient market hypothesis a…Nonlinearities, cyclical behaviour and predictability in stock markets: international evidence (2001)Nonlinearities, cyclical beha…Automatic neural network modeling for univariate time series (2000)Automatic neural network mode…Testing for neglected nonlinearity in time series models (1993)Testing for neglected nonline…Forecasting stock market prices: Lessons for forecasters (1992)Forecasting stock market pric…Bootstrap prediction intervals for autoregressions (1990)Bootstrap prediction interval…Forecasting with artificial neural networks: (1998)Time Series Forecasting with Neural Networks: A Comparative Study Using the Air Line Data (1998)25 years of time series forecasting (2006)A novel hybridization of artificial neural networks and ARIMA models for time series forecasting (2010)On the use of cross-validation for time series predictor evaluation (2012)Financial statement analysis and the prediction of stock returns (1989)Artificial neural network models for forecasting and decision making (1994)How effective are neural networks at forecasting and prediction? A review and evaluation (1998)Surveying stock market forecasting techniques – Part II: Soft computing methods (2008)Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle (1989)Heterogeneous beliefs and routes to chaos in a simple asset pricing model (1998)Forecasting stock indices with back propagation neural network (2011)Forecasting daily stock market return using dimensionality reduction (2016)The Economy as an Evolving Complex System II (2018)Efficient Capital Markets: A Review of Theory and Empirical Work (1970)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Does the Stock Market Overreact? (1985)A long memory property of stock market returns and a new model (1993)Neural networks: Forecasting breakthrough or passing fad? (1993)A Long Memory Property of Stock Market Returns and a New Model (2010)Efficient Capital Markets: II (1991)An artificial neural network (p,d,q) model for timeseries forecasting (2009)Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy (2009)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)DIAGNOSTIC CHECKING ARMA TIME SERIES MODELS USING SQUARED‐RESIDUAL AUTOCORRELATIONS (1983)Advances in Econometrics (1987)A test for independence based on the correlation dimension (1996)SMOOTH TRANSITION AUTOREGRESSIVE MODELS — A SURVEY OF RECENT DEVELOPMENTS (2002)The Combination of Forecasts (1969)Another look at measures of forecast accuracy (2006)Computational Intelligence and Financial Markets: A Survey and Future Directions (2016)M5 accuracy competition: Results, findings, and conclusions (2022)Fuzzy sets (1965)Fuzzy sets (1996)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)The accuracy of extrapolation (time series) methods: Results of a forecasting competition (1982)The M3-Competition: results, conclusions and implications (2000)Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)N-BEATS: Neural basis expansion analysis for interpretable time series forecasting (2019)A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction (2017)The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms (2017)The M4 Competition: 100,000 time series and 61 forecasting methods (2019)
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References

  • 2019A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting791 cited
  • 2018The M4 Competition: Results, findings, conclusion and way forward683 cited
  • 2003Efficient market hypothesis and forecasting516 cited
  • 1993Testing for neglected nonlinearity in time series models498 cited
  • 2014Neural network ensemble operators for time series forecasting307 cited
  • 2011Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction272 cited
  • 2000Automatic neural network modeling for univariate time series185 cited
  • 2003Neural network forecasts of Canadian stock returns using accounting ratios182 cited
  • 2001Nonlinearities, cyclical behaviour and predictability in stock markets: international evidence176 cited
  • 1992Forecasting stock market prices: Lessons for forecasters153 cited
  • 2019A brief history of forecasting competitions129 cited
  • 1990Bootstrap prediction intervals for autoregressions115 cited
  • 2018Classification of intraday S&P500 returns with a Random Forest98 cited
  • 2010Forecasting the direction of the US stock market with dynamic binary probit models97 cited
  • 2014Bootstrap prediction intervals for linear, nonlinear and nonparametric autoregressions

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93 cited
  • 2004Forecasting with a nonlinear dynamic model of stock returns and industrial production77 cited
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