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Global crude oil price prediction and synchronization based accuracy evaluation using random wavelet neural network
14 references·13 citing·49 second hop
Global crude oil price prediction and synchronization based accuracy evaluation using random wavelet neural network (2018)Global crude oil price prediction and syn…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…Forecasting energy market indices with recurrent neural networks: Case study of crude oil price fluctuations (2016)Forecasting energy market ind…Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling (2011)Crude oil price forecasting: …A flexible neural network-fuzzy mathematical programming algorithm for improvement of oil price estimation and forecasting (2011)A flexible neural network-fuz…APPLICATION OF ARTIFICIAL NEURAL NETWORK FOR STOCK MARKET PREDICTIONS: A REVIEW OF LITERATURE (2010)APPLICATION OF ARTIFICIAL NEU…Modeling and forecasting crude oil markets using ARCH-type models (2009)Modeling and forecasting crud…Forecasting model of global stock index by stochastic time effective neural network (2009)Forecasting model of global s…Oil price shocks and stock markets in the U.S. and 13 European countries (2008)Oil price shocks and stock ma…Forecasting Nonlinear Crude Oil Futures Prices (2006)Forecasting Nonlinear Crude O…A New Method for Crude Oil Price Forecasting Based on Support Vector Machines (2006)A New Method for Crude Oil Pr…Wavelet-based prediction of oil prices (2005)Wavelet-based prediction of o…Oil prices, economic activity and inflation: evidence for some Asian countries (2004)Oil prices, economic activity…Neural network forecasts of Canadian stock returns using accounting ratios (2003)Neural network forecasts of C…A blending ensemble learning model for crude oil price forecasting (2024)A blending ensemble learning …The Importance of Quantum Information in the Stock Market and Financial Decision Making in Conditions of Radical Uncertainty (2023)The Importance of Quantum Inf…Deterministic and uncertainty crude oil price forecasting based on outlier detection and modified multi-objective optimization algorithm (2022)Deterministic and uncertainty…Forecasting crude oil price with a new hybrid approach and multi-source data (2021)Forecasting crude oil price w…A novel multiscale forecasting model for crude oil price time series (2021)A novel multiscale forecastin…A novel method for online real-time forecasting of crude oil price (2021)A novel method for online rea…A novel crude oil price trend prediction method: Machine learning classification algorithm based on multi-modal data features (2021)A novel crude oil price trend…Gold price forecasting research based on an improved online extreme learning machine algorithm (2020)Gold price forecasting resear…Forcasting of energy futures market and synchronization based on stochastic gated recurrent unit model (2020)Forcasting of energy futures …Ensemble probabilistic prediction approach for modeling uncertainty in crude oil price (2020)Ensemble probabilistic predic…Energy futures and spots prices forecasting by hybrid SW-GRU with EMD and error evaluation (2020)Energy futures and spots pric…Energy futures prices forecasting by novel DPFWR neural network and DS-CID evaluation (2019)Energy futures prices forecas…A decomposition–integration model with dynamic fuzzy reconstruction for crude oil price prediction and the implications for sustainable development (2019)A decomposition–integration m…Forecasting stock market movement direction with support vector machine (2004)Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method (2009)Online big data-driven oil consumption forecasting with Google trends (2018)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)Volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory (2013)Which determinant is the most informative in forecasting crude oil market volatility: Fundamental, speculation, or uncertainty? 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this work references cited by second hop

References

  • 2008Oil price shocks and stock markets in the U.S. and 13 European countries1,264 cited
  • 2004Oil prices, economic activity and inflation: evidence for some Asian countries691 cited
  • 2017A deep learning ensemble approach for crude oil price forecasting383 cited
  • 2011Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling282 cited
  • 2006A New Method for Crude Oil Price Forecasting Based on Support Vector Machines258 cited
  • 2009Modeling and forecasting crude oil markets using ARCH-type models222 cited
  • 2003Neural network forecasts of Canadian stock returns using accounting ratios182 cited
  • 2006Forecasting Nonlinear Crude Oil Futures Prices176 cited
  • 2005Wavelet-based prediction of oil prices165 cited
  • 2017A non-iterative decomposition-ensemble learning paradigm using RVFL network for crude oil price forecasting153 cited
  • 2009Forecasting model of global stock index by stochastic time effective neural network151 cited
  • 2016Forecasting energy market indices with recurrent neural networks: Case study of crude oil price fluctuations142 cited
  • 2011A flexible neural network-fuzzy mathematical programming algorithm for improvement of oil price estimation and forecasting105 cited
  • 2010APPLICATION OF ARTIFICIAL NEURAL NETWORK FOR STOCK MARKET PREDICTIONS: A REVIEW OF LITERATURE

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103 cited

Cited by

  • 2020Energy futures and spots prices forecasting by hybrid SW-GRU with EMD and error evaluation77 cited
  • 2020Gold price forecasting research based on an improved online extreme learning machine algorithm75 cited
  • 2021Forecasting crude oil price with a new hybrid approach and multi-source data73 cited
  • 2021A novel multiscale forecasting model for crude oil price time series69 cited
  • 2021A novel method for online real-time forecasting of crude oil price60 cited
  • 2022Deterministic and uncertainty crude oil price forecasting based on outlier detection and modified multi-objective optimization algorithm57 cited
  • 2020Ensemble probabilistic prediction approach for modeling uncertainty in crude oil price50 cited
  • 2021A novel crude oil price trend prediction method: Machine learning classification algorithm based on multi-modal data features48 cited
  • 2024A blending ensemble learning model for crude oil price forecasting48 cited
  • 2019A decomposition–integration model with dynamic fuzzy reconstruction for crude oil price prediction and the implications for sustainable development46 cited
  • 2019Energy futures prices forecasting by novel DPFWR neural network and DS-CID evaluation45 cited
  • 2020Forcasting of energy futures market and synchronization based on stochastic gated recurrent unit model43 cited
  • 2023The Importance of Quantum Information in the Stock Market and Financial Decision Making in Conditions of Radical Uncertainty4 cited