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Multiscale Combined Model Based on Run‐Length‐Judgment Method and Its Application in Oil Price Forecasting
16 references·0 citing·47 second hopsampled
Multiscale Combined Model Based on Run‐Length‐Judgment Method and Its Application in Oil Price Forecasting (2014)Multiscale Combined Model Based on Run‐Le…Support vector regression with chaos-based firefly algorithm for stock market price forecasting (2012)Support vector regression wit…A multiple adaptive wavelet recurrent neural network model to analyze crude oil prices (2012)A multiple adaptive wavelet r…Country risk forecasting for major oil exporting countries: A decomposition hybrid approach (2011)Country risk forecasting for …A flexible neural network-fuzzy mathematical programming algorithm for improvement of oil price estimation and forecasting (2011)A flexible neural network-fuz…Oil prices — Brownian motion or mean reversion? A study using a one year ahead density forecast criterion (2010)Oil prices — Brownian motion …Forecasting oil price trends using wavelets and hidden Markov models (2010)Forecasting oil price trends …Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method (2009)Estimating the impact of extr…A novel algorithm for prediction of crude oil price variation based on soft computing (2009)A novel algorithm for predict…Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm (2008)Forecasting crude oil price w…A new approach for crude oil price analysis based on Empirical Mode Decomposition (2007)A new approach for crude oil …Forecast of oil price and consumption in the short term under three scenarios: Parabolic, linear and chaotic behaviour (2006)Forecast of oil price and con…A generalized pattern matching approach for multi-step prediction of crude oil price (2006)A generalized pattern matchin…Modeling and forecasting cointegrated relationships among heavy oil and product prices (2005)Modeling and forecasting coin…A monthly crude oil spot price forecasting model using relative inventories (2005)A monthly crude oil spot pric…A Novel Hybrid AI System Framework for Crude Oil Price Forecasting (2004)A Novel Hybrid AI System Fram…Probabilistic forecasts from probabilistic models: A case study in the oil market (1995)Probabilistic forecasts from …Event Studies in Economics and Finance (1997)Oil price volatility and oil-related events: An Internet concern study perspective (2014)Text-based crude oil price forecasting: A deep learning approach (2018)The impact of extreme events on energy price risk (2021)Time Series Analysis Forecasting and Control. 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(2016)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)Predicting stock market index using fusion of machine learning techniques (2014)Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)Financial time series forecasting model based on CEEMDAN and LSTM (2018)Forecasting methods and applications (1993)Neural network forecasting for seasonal and trend time series (2003)Forecasting the WTI crude oil price by a hybrid-refined method (2018)Modes decomposition method in fusion with robust random vector functional link network for crude oil price forecasting (2019)Multi-step-ahead crude oil price forecasting based on two-layer decomposition technique and extreme learning machine optimized by the particle swarm optimization algorithm (2021)Expectations and the neutrality of money (1972)Econometric Models and Economic Forecasts (1990)The Role of Monetary Policy (1995)Global economic activity and crude oil prices: A cointegration analysis (2009)Does OPEC Matter? An Econometric Analysis of Oil Prices (2004)A New Method for Crude Oil Price Forecasting Based on Support Vector Machines (2006)Estimating and forecasting the real prices of crude oil: A data rich model using a dynamic model averaging (DMA) approach (2016)Forecasting: theory and practice (2022)
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References

  • 2008Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm706 cited
  • 2012Support vector regression with chaos-based firefly algorithm for stock market price forecasting471 cited
  • 2007A new approach for crude oil price analysis based on Empirical Mode Decomposition447 cited
  • 2009Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method253 cited
  • 2005Modeling and forecasting cointegrated relationships among heavy oil and product prices172 cited
  • 2005A monthly crude oil spot price forecasting model using relative inventories150 cited
  • 2011A flexible neural network-fuzzy mathematical programming algorithm for improvement of oil price estimation and forecasting105 cited
  • 2010Forecasting oil price trends using wavelets and hidden Markov models87 cited
  • 2006A generalized pattern matching approach for multi-step prediction of crude oil price86 cited
  • 2009A novel algorithm for prediction of crude oil price variation based on soft computing77 cited
  • 2006Forecast of oil price and consumption in the short term under three scenarios: Parabolic, linear and chaotic behaviour70 cited
  • 2004A Novel Hybrid AI System Framework for Crude Oil Price Forecasting67 cited
  • 2012A multiple adaptive wavelet recurrent neural network model to analyze crude oil prices66 cited
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Probabilistic forecasts from probabilistic models: A case study in the oil market
62 cited
  • 2010Oil prices — Brownian motion or mean reversion? A study using a one year ahead density forecast criterion58 cited
  • 2011Country risk forecasting for major oil exporting countries: A decomposition hybrid approach53 cited
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