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A New Approach for Forecasting Crude Oil Prices Based on Stochastic and Deterministic Influences of LMD Using ARIMA and LSTM Models
16 references·1 citing·43 second hop
A New Approach for Forecasting Crude Oil Prices Based on Stochastic and Deterministic Influences of LMD Using ARIMA and LSTM Models (2023)A New Approach for Forecasting Crude Oil …Forecasting the prices of crude oil: An iterated combination approach (2018)Forecasting the prices of cru…A novel hybrid method of forecasting crude oil prices using complex network science and artificial intelligence algorithms (2018)A novel hybrid method of fore…A non-iterative decomposition-ensemble learning paradigm using RVFL network for crude oil price forecasting (2017)A non-iterative decomposition…A deep learning ensemble approach for crude oil price forecasting (2017)A deep learning ensemble appr…Oil price forecasting using gene expression programming and artificial neural networks (2016)Oil price forecasting using g…Oil Price Volatility Forecast with Mixture Memory GARCH (2015)Oil Price Volatility Forecast…Oil price forecastability and economic uncertainty (2015)Oil price forecastability and…Evolutionary Neural Network model for West Texas Intermediate crude oil price prediction (2015)Evolutionary Neural Network m…A novel hybrid method for crude oil price forecasting (2015)A novel hybrid method for cru…A novel decomposition ensemble model with extended extreme learning machine for crude oil price forecasting (2015)A novel decomposition ensembl…A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting (2015)A decomposition–ensemble mode…Beyond one-step-ahead forecasting: Evaluation of alternative multi-step-ahead forecasting models for crude oil prices (2013)Beyond one-step-ahead forecas…International evidence on crude oil price dynamics: Applications of ARIMA-GARCH models (2010)International evidence on cru…Efficient Tests for an Autoregressive Unit Root (1996)Efficient Tests for an Autore…Designing a neural network for forecasting financial and economic time series (1996)Designing a neural network fo…Time Series Analysis Forecasting and Control. (1973)Time Series Analysis Forecast…Crude Oil Price Time Series Forecasting: A Novel Approach Based on Variational Mode Decomposition, Time-Series Imaging, and Deep Learning (2023)Crude Oil Price Time Series F…Comparing Predictive Accuracy (1994)Use of Cumulative Sums of Squares for Retrospective Detection of Changes of Variance (1994)Comparing Predictive Accuracy (1995)A multiscale analysis for carbon price drivers (2018)Carbon price forecasting with variational mode decomposition and optimal combined model (2018)Oil price forecasting using a hybrid model (2018)Generalized autoregressive conditional heteroskedasticity (1986)Modeling and forecasting petroleum futures volatility (2006)Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm (2008)A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting (2018)Crude oil time series prediction model based on LSTM network with chaotic Henry gas solubility optimization (2021)Price forecasting through neural networks for crude oil, heating oil, and natural gas (2024)Time Series Analysis Forecasting and Control. (1971)Time Series Analysis: Forecasting and Control (1977)Another look at measures of forecast accuracy (2006)Crude oil price analysis and forecasting using wavelet decomposed ensemble model (2012)Comparing Variational and Empirical Mode Decomposition in Forecasting Day-Ahead Energy Prices (2015)A neural network model for bankruptcy prediction (1990)Support vector machine with adaptive parameters in financial time series forecasting (2003)Predicting the Price of Bitcoin Using Machine Learning (2018)Forecasting: theory and practice (2022)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)Modelling oil price and exchange rate co-movements (2011)Measuring contagion between energy market and stock market during financial crisis: A copula approach (2012)Is gold a hedge or safe haven against oil price movements? (2013)Forecasting with artificial neural networks: (1998)A simulation study of artificial neural networks for nonlinear time-series forecasting (2001)Modelling the impact of oil prices on Vietnam’s stock prices (2009)Financial implications of fourth industrial revolution: Can bitcoin improve prospects of energy investment? (2020)Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Time Series Regression with a Unit Root (1987)Testing for a Unit Root in Time Series Regression (1988)LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power (2001)Unit root tests for panel data (2001)A simple panel unit root test in the presence of cross‐section dependence (2007)Stock price prediction based on deep neural networks (2019)A comprehensive evaluation of ensemble learning for stock-market prediction (2020)Hybrid Variational Mode Decomposition and evolutionary robust kernel extreme learning machine for stock price and movement prediction on daily basis (2018)Oil price forecasting: A hybrid GRU neural network based on decomposition–reconstruction methods (2023)Revealing the dynamic network structure of the Beck Depression Inventory-II (2014)The life course cube: A tool for studying lives (2018)Assessing the environmental impacts of renewable energy sources: A case study on air pollution and carbon emissions in China (2023)
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References

  • 1996Efficient Tests for an Autoregressive Unit Root5,637 cited
  • 1996Designing a neural network for forecasting financial and economic time series1,092 cited
  • 1973Time Series Analysis Forecasting and Control.972 cited
  • 2017A deep learning ensemble approach for crude oil price forecasting383 cited
  • 2010International evidence on crude oil price dynamics: Applications of ARIMA-GARCH models346 cited
  • 2015A novel hybrid method for crude oil price forecasting272 cited
  • 2015A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting204 cited
  • 2015A novel decomposition ensemble model with extended extreme learning machine for crude oil price forecasting204 cited
  • 2015Evolutionary Neural Network model for West Texas Intermediate crude oil price prediction175 cited
  • 2013Beyond one-step-ahead forecasting: Evaluation of alternative multi-step-ahead forecasting models for crude oil prices167 cited
  • 2018Forecasting the prices of crude oil: An iterated combination approach159 cited
  • 2017A non-iterative decomposition-ensemble learning paradigm using RVFL network for crude oil price forecasting153 cited
  • 2018A novel hybrid method of forecasting crude oil prices using complex network science and artificial intelligence algorithms146 cited
  • 2016Oil price forecasting using gene expression programming and artificial neural networks

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127 cited
  • 2015Oil Price Volatility Forecast with Mixture Memory GARCH114 cited
  • 2015Oil price forecastability and economic uncertainty111 cited
  • Cited by

    • 2023Crude Oil Price Time Series Forecasting: A Novel Approach Based on Variational Mode Decomposition, Time-Series Imaging, and Deep Learning30 cited