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Ensemble forecasting system based on decomposition-selection-optimization for point and interval carbon price prediction
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Ensemble forecasting system based on decomposition-selection-optimization for point and interval carbon price prediction (2022)Ensemble forecasting system based on deco…Carbon price forecasting based on CEEMDAN and LSTM (2022)Carbon price forecasting base…Forecasting carbon price using a multi‐objective least squares support vector machine with mixture kernels (2021)Forecasting carbon price usin…A multi-factor integrated model for carbon price forecasting: Market interaction promoting carbon emission reduction (2021)A multi-factor integrated mod…A hybrid model for carbon price forecastingusing GARCH and long short-term memory network (2021)A hybrid model for carbon pri…Carbon price forecasting based on modified ensemble empirical mode decomposition and long short-term memory optimized by improved whale optimization algorithm (2020)Carbon price forecasting base…A new secondary decomposition ensemble learning approach for carbon price forecasting (2020)A new secondary decomposition…Carbon price forecasting with complex network and extreme learning machine (2019)Carbon price forecasting with…A carbon price prediction model based on secondary decomposition algorithm and optimized back propagation neural network (2019)A carbon price prediction mod…Information linkage, dynamic spillovers in prices and volatility between the carbon and energy markets (2018)Information linkage, dynamic …A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting (2018)A novel multiscale nonlinear …A hybrid model using signal processing technology, econometric models and neural network for carbon spot price forecasting (2018)A hybrid model using signal p…Using computational intelligence to forecast carbon prices (2016)Using computational intellige…Chaotic characteristic identification for carbon price and an multi-layer perceptron network prediction model (2015)Chaotic characteristic identi…A novel decomposition ensemble model with extended extreme learning machine for crude oil price forecasting (2015)A novel decomposition ensembl…Forecasting carbon futures volatility using GARCH models with energy volatilities (2013)Forecasting carbon futures vo…Carbon price forecasting with a novel hybrid ARIMA and least squares support vector machines methodology (2012)Carbon price forecasting with…Carbon price forecasting using leaky integrator echo state networks with the framework of decomposition-reconstruction-integration (2024)Carbon price forecasting usin…An optimized and interpretable carbon price prediction: Explainable deep learning model (2024)An optimized and interpretabl…A secondary decomposition-ensemble framework for interval carbon price forecasting (2024)A secondary decomposition-ens…Forecasting carbon price in China unified carbon market using a novel hybrid method with three-stage algorithm and long short-term memory neural networks (2023)Forecasting carbon price in C…Causal carbon price interval prediction using lower upper bound estimation combined with asymmetric multi-objective evolutionary algorithm and long short-term memory (2023)Causal carbon price interval …An enhanced decomposition integration model for deterministic and probabilistic carbon price prediction based on two-stage feature extraction and intelligent weight optimization (2023)An enhanced decomposition int…A novel interval-valued carbon price analysis and forecasting system based on multi-objective ensemble strategy for carbon trading market (2023)A novel interval-valued carbo…A hybrid carbon price prediction model based-combinational estimation strategies of quantile regression and long short-term memory (2023)A hybrid carbon price predict…Comparing Predictive Accuracy (1994)Time series forecasting using a hybrid ARIMA and neural network model (2003)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)Carbon trading volume and price forecasting in China using multiple machine learning models 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volatility models: does anything beat a GARCH(1,1)? (2005)A Test for Superior Predictive Ability (2005)A multiscale analysis for carbon price drivers (2018)Impulse response analysis in nonlinear multivariate models (1996)Generalized impulse response analysis in linear multivariate models (1998)On the network topology of variance decompositions: Measuring the connectedness of financial firms (2014)The dynamic dependence of fossil energy, investor sentiment and renewable energy stock markets (2019)How connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics (2020)Time-frequency connectedness among clean-energy stocks and fossil fuel markets: Comparison between financial, oil and pandemic crisis (2021)Control problems of grey systems (1982)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)A hybrid algorithm for carbon dioxide emissions forecasting based on improved lion swarm optimizer (2019)Price drivers in the carbon emissions trading scheme: Evidence from Chinese emissions trading scheme pilots (2020)Palladium Price Predictions via Machine Learning (2024)An overview of current research on EU ETS: Evidence from its operating mechanism and economic effect (2010)Forecasting carbon price using empirical mode decomposition and evolutionary least squares support vector regression (2017)A hybrid framework for carbon trading price forecasting: The role of multiple influence factor (2020)A combination forecasting model based on hybrid interval multi-scale decomposition: Application to interval-valued carbon price forecasting (2021)Hybridization of hybrid structures for time series forecasting: a review (2022)Comparing Predictive Accuracy (1995)A CNN-LSTM based deep learning model with high accuracy and robustness for carbon price forecasting: A case of Shenzhen's carbon market in China (2024)Predictions of steel price indices through machine learning for the regional northeast Chinese market (2024)Thermal coal futures trading volume predictions through the neural network (2024)Time Series Analysis: Forecasting and Control (1977)Hybrid Variational Mode Decomposition and evolutionary robust kernel extreme learning machine for stock price and movement prediction on daily basis (2018)Oil price forecasting using a hybrid model (2018)Oil price forecasting: A hybrid GRU neural network based on decomposition–reconstruction methods (2023)Efficient Capital Markets: A Review of Theory and Empirical Work (1970)Time Series Analysis Forecasting and Control. (1971)Testing the equality of prediction mean squared errors (1997)Forecasting gold price using a novel hybrid model with ICEEMDAN and LSTM-CNN-CBAM (2022)
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References

  • 2022Carbon price forecasting based on CEEMDAN and LSTM424 cited
  • 2018Information linkage, dynamic spillovers in prices and volatility between the carbon and energy markets385 cited
  • 2012Carbon price forecasting with a novel hybrid ARIMA and least squares support vector machines methodology376 cited
  • 2013Forecasting carbon futures volatility using GARCH models with energy volatilities346 cited
  • 2021A hybrid model for carbon price forecastingusing GARCH and long short-term memory network316 cited
  • 2019A carbon price prediction model based on secondary decomposition algorithm and optimized back propagation neural network259 cited
  • 2018A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting235 cited
  • 2015Chaotic characteristic identification for carbon price and an multi-layer perceptron network prediction model209 cited
  • 2015A novel decomposition ensemble model with extended extreme learning machine for crude oil price forecasting204 cited
  • 2018A hybrid model using signal processing technology, econometric models and neural network for carbon spot price forecasting173 cited
  • 2016Using computational intelligence to forecast carbon prices151 cited
  • 2020A new secondary decomposition ensemble learning approach for carbon price forecasting147 cited
  • 2020Carbon price forecasting based on modified ensemble empirical mode decomposition and long short-term memory optimized by improved whale optimization algorithm

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144 cited
  • 2021A multi-factor integrated model for carbon price forecasting: Market interaction promoting carbon emission reduction138 cited
  • 2019Carbon price forecasting with complex network and extreme learning machine126 cited
  • 2021Forecasting carbon price using a multi‐objective least squares support vector machine with mixture kernels125 cited
  • Cited by

    • 2023Forecasting carbon price in China unified carbon market using a novel hybrid method with three-stage algorithm and long short-term memory neural networks52 cited
    • 2023A hybrid carbon price prediction model based-combinational estimation strategies of quantile regression and long short-term memory44 cited
    • 2024A secondary decomposition-ensemble framework for interval carbon price forecasting43 cited
    • 2023A novel interval-valued carbon price analysis and forecasting system based on multi-objective ensemble strategy for carbon trading market42 cited
    • 2023Causal carbon price interval prediction using lower upper bound estimation combined with asymmetric multi-objective evolutionary algorithm and long short-term memory37 cited
    • 2024An optimized and interpretable carbon price prediction: Explainable deep learning model36 cited
    • 2023An enhanced decomposition integration model for deterministic and probabilistic carbon price prediction based on two-stage feature extraction and intelligent weight optimization32 cited
    • 2024Carbon price forecasting using leaky integrator echo state networks with the framework of decomposition-reconstruction-integration30 cited