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Novel statistical forecasting models for crude oil price, gas price, and interest rate based on meta-heuristic bat algorithm
3 references·6 citing·42 second hop
Novel statistical forecasting models for crude oil price, gas price, and interest rate based on meta-heuristic bat algorithm (2018)Novel statistical forecasting models for …Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling (2011)Crude oil price forecasting: …A generalized pattern matching approach for multi-step prediction of crude oil price (2006)A generalized pattern matchin…Neural network versus econometric models in forecasting inflation (2000)Neural network versus econome…Petroleum Price Prediction with CNN-LSTM and CNN-GRU Using Skip-Connection (2023)Petroleum Price Prediction wi…Forecasting energy prices using a novel hybrid model with variational mode decomposition (2022)Forecasting energy prices usi…A Review of the Applications of Genetic Algorithms to Forecasting Prices of Commodities (2021)A Review of the Applications …Ensemble probabilistic prediction approach for modeling uncertainty in crude oil price (2020)Ensemble probabilistic predic…Daily natural gas price forecasting by a weighted hybrid data-driven model (2020)Daily natural gas price forec…Black gold falls, black plague arise - An Opec crude oil price forecast using a gray prediction model (2020)Black gold falls, black plagu…Time Series Analysis Forecasting and Control. (1971)Time Series Analysis: Forecasting and Control. (1978)Forecasting with artificial neural networks: (1998)Efficiency of crude oil markets: Evidences from informational entropy analysis (2011)Provincial carbon intensity abatement potential estimation in China: A PSO–GA-optimized multi-factor environmental learning curve method (2014)Using four different online media sources to forecast the crude oil price (2017)Designing a neural network for forecasting financial and economic time series (1996)Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm (2008)Wavelet-based evidence of the impact of oil prices on stock returns (2013)A novel hybrid method for crude oil price forecasting (2015)Improved EEMD-based crude oil price forecasting using LSTM networks (2018)Principles of forecasting : a handbook for researchers and practitioners (2001)Principles of Forecasting. A Handbook for Researchers and Practitioners (2002)Modeling and forecasting petroleum futures volatility (2006)Neural Network Models for Time Series Forecasts (1996)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)A new approach for crude oil price analysis based on Empirical Mode Decomposition (2007)Novel deterministic and probabilistic forecasting methods for crude oil price employing optimized deep learning, statistical and hybrid models (2023)A blending ensemble learning model for crude oil price forecasting (2024)A survey on uncertainty quantification in deep learning for financial time series prediction (2024)Applications of improved grey prediction model for power demand forecasting (2003)Applying the Grey prediction model to the global integrated circuit industry (2003)Grey system theory-based models in time series prediction (2009)Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)Statistical analysis of cointegration vectors (1988)Inflation forecasting using a neural network (2004)NEURAL NETWORKS IN FINANCE AND ECONOMICS FORECASTING (2007)A COMPARATIVE ANALYSIS OF ALTERNATIVE UNIVARIATE TIME SERIES MODELS IN FORECASTING TURKISH INFLATION (2012)I.—COMPUTING MACHINERY AND INTELLIGENCE (1950)Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index (2000)Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN) (2021)Machine learning predictions of China commodity price indices (2025)Fitting autoregressive models for prediction (1969)Prospect Theory: An Analysis of Decision under Risk (1979)Comparing Predictive Accuracy (1995)A novel interval-valued carbon price analysis and forecasting system based on multi-objective ensemble strategy for carbon trading market (2023)Predicting carbon futures prices based on a new hybrid machine learning: Comparative study of carbon prices in different periods (2023)The impact of Russia–Ukraine war on crude oil prices: an EMC framework (2024)Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market (2009)Investor Flows and the 2008 Boom/Bust in Oil Prices (2013)A Comparison of ARIMA and LSTM in Forecasting Time Series (2018)
this work references cited by second hop

References

  • 2011Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling282 cited
  • 2000Neural network versus econometric models in forecasting inflation155 cited
  • 2006A generalized pattern matching approach for multi-step prediction of crude oil price86 cited

Cited by

  • 2022Forecasting energy prices using a novel hybrid model with variational mode decomposition59 cited
  • 2021A Review of the Applications of Genetic Algorithms to Forecasting Prices of Commodities55 cited
  • 2020Daily natural gas price forecasting by a weighted hybrid data-driven model53 cited
  • 2023Petroleum Price Prediction with CNN-LSTM and CNN-GRU Using Skip-Connection52 cited
  • 2020Ensemble probabilistic prediction approach for modeling uncertainty in crude oil price50 cited
  • 2020Black gold falls, black plague arise - An Opec crude oil price forecast using a gray prediction model45 cited

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