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An ensemble dynamic self-learning model for multiscale carbon price forecasting
15 references·4 citing·48 second hopsampled
An ensemble dynamic self-learning model for multiscale carbon price forecasting (2022)An ensemble dynamic self-learning model f…Carbon price forecasting based on CEEMDAN and LSTM (2022)Carbon price forecasting base…Carbon price forecasting system based on error correction and divide-conquer strategies (2021)Carbon price forecasting syst…An interview with Shouyang Wang: research frontier of big data-driven economic and financial forecasting (2021)An interview with Shouyang Wa…A novel interval decomposition ensemble model for interval carbon price forecasting (2021)A novel interval decompositio…A new carbon price prediction model (2021)A new carbon price prediction…Urban carbon emission intensity under emission trading system in a developing economy: evidence from 273 Chinese cities (2020)Urban carbon emission intensi…Does weather, or energy prices, affect carbon prices? (2020)Does weather, or energy price…A new secondary decomposition ensemble learning approach for carbon price forecasting (2020)A new secondary decomposition…Forecasting carbon prices in the Shenzhen market, China: The role of mixed-frequency factors (2019)Forecasting carbon prices in …Carbon price forecasting with complex network and extreme learning machine (2019)Carbon price forecasting with…Usefulness of economic and energy data at different frequencies for carbon price forecasting in the EU ETS (2018)Usefulness of economic and en…Analysis and forecasting of the carbon price using multi—resolution singular value decomposition and extreme learning machine optimized by adaptive whale optimization algorithm (2018)Analysis and forecasting of t…A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting (2018)A novel multiscale nonlinear …A multiscale analysis for carbon price drivers (2018)A multiscale analysis for car…An overview of current research on EU ETS: Evidence from its operating mechanism and economic effect (2010)An overview of current resear…Framework for multivariate carbon price forecasting: A novel hybrid model (2024)Framework for multivariate ca…Forecasting carbon prices in China's pilot carbon market: A multi-source information approach with conditional generative adversarial networks (2024)Forecasting carbon prices in …SimVGNets: Similarity-Based Visibility Graph Networks for Carbon Price Forecasting (2023)SimVGNets: Similarity-Based V…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…The energy–climate challenge: Recent trends in CO2 emissions from fuel combustion (2007)Modeling the price dynamics of CO2 emission allowances (2008)Price drivers and structural breaks in European carbon prices 2005–2007 (2008)Carbon finance and carbon market in China: Progress and challenges (2019)How does emission trading reduce China's carbon intensity? An exploration using a decomposition and difference-in-differences approach (2019)Can China’s policy of carbon emission trading promote carbon emission reduction? (2020)Generalized autoregressive conditional heteroskedasticity (1986)A forecast comparison of volatility models: does anything beat a GARCH(1,1)? (2005)A Test for Superior Predictive Ability (2005)An innovative random forest-based nonlinear ensemble paradigm of improved feature extraction and deep learning for carbon price forecasting (2020)Chapter 4 Forecast Combinations (2006)Analyzing spillover effects between carbon and fossil energy markets from a time-varying perspective (2021)Tightening EU ETS targets in line with the European Green Deal: Impacts on the decarbonization of the EU power sector (2021)The spillover effects among fossil fuel, renewables and carbon markets: Evidence under the dual dilemma of climate change and energy crises (2023)Forecasting Volatility in Financial Markets: A Review (2003)Forecasting Volatility in Financial Markets: A Review (2003)Modelling of carbon price in two real carbon trading markets (2019)Carbon price forecasting with optimization prediction method based on unstructured combination (2020)Hybridization of hybrid structures for time series forecasting: a review (2022)Statistical analysis of cointegration vectors (1988)Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models (1991)Measuring Business Cycles: Approximate Band-Pass Filters for Economic Time Series (1999)Nonlinear dependence and connectedness between clean/renewable energy sector equity and European emission allowance prices (2021)Asymmetric causality of economic policy uncertainty and oil volatility index on time-varying nexus of the clean energy, carbon and green bond (2022)Do green bonds and economic policy uncertainty matter for carbon price? New insights from a TVP-VAR framework (2023)The MIDAS Touch: Mixed Data Sampling Regression Models (2004)China׳s carbon-emissions trading: Overview, challenges and future (2015)A hybrid framework for carbon trading price forecasting: The role of multiple influence factor (2020)China commodity price index (CCPI) forecasting via the neural network (2025)How does corporate social responsibility contribute to firm financial performance? The mediating role of competitive advantage, reputation, and customer satisfaction (2014)Can a carbon trading system promote the transformation of a low-carbon economy under the framework of the porter hypothesis? —Empirical analysis based on the PSM-DID method (2019)Regional development and carbon emissions in China (2019)Industrial agglomeration, CO2 emissions and regional development programs: A decomposition analysis based on 286 Chinese cities (2021)Pathways towards carbon neutrality in low carbon cities: The role of green patents, R&D and energy use for carbon emissions (2023)Whether the carbon emissions trading system improves energy efficiency – Empirical testing based on China's provincial panel data (2023)The European Union Emissions Trading Scheme: Origins, Allocation, and Early Results (2007)Forecasting carbon prices based on real-time decomposition and causal temporal convolutional networks (2022)How does the Russian-Ukrainian war change connectedness and hedging opportunities? Comparison between dirty and clean energy markets versus global stock indices (2023)CO2 Prices, Energy and Weather (2007)Allowance price drivers in the first phase of the EU ETS (2009)Carbon price prediction using multiple hybrid machine learning models optimized by genetic algorithm (2023)Multi-step carbon price forecasting using a hybrid model based on multivariate decomposition strategy and deep learning algorithms (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)Oil price forecasting: A hybrid GRU neural network based on decomposition–reconstruction methods (2023)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)
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References

  • 2010An overview of current research on EU ETS: Evidence from its operating mechanism and economic effect434 cited
  • 2022Carbon price forecasting based on CEEMDAN and LSTM424 cited
  • 2018A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting235 cited
  • 2019Forecasting carbon prices in the Shenzhen market, China: The role of mixed-frequency factors208 cited
  • 2018A multiscale analysis for carbon price drivers203 cited
  • 2018Usefulness of economic and energy data at different frequencies for carbon price forecasting in the EU ETS198 cited
  • 2020Does weather, or energy prices, affect carbon prices?191 cited
  • 2018Analysis and forecasting of the carbon price using multi—resolution singular value decomposition and extreme learning machine optimized by adaptive whale optimization algorithm181 cited
  • 2020A new secondary decomposition ensemble learning approach for carbon price forecasting147 cited
  • 2020Urban carbon emission intensity under emission trading system in a developing economy: evidence from 273 Chinese cities133 cited
  • 2019Carbon price forecasting with complex network and extreme learning machine126 cited
  • 2021Carbon price forecasting system based on error correction and divide-conquer strategies113 cited
  • 2021A new carbon price prediction model85 cited
  • 2021A novel interval decomposition ensemble model for interval carbon price forecasting

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76 cited
  • 2021An interview with Shouyang Wang: research frontier of big data-driven economic and financial forecasting36 cited
  • Cited by

    • 2024Forecasting carbon prices in China's pilot carbon market: A multi-source information approach with conditional generative adversarial networks47 cited
    • 2024Framework for multivariate carbon price forecasting: A novel hybrid model45 cited
    • 2023SimVGNets: Similarity-Based Visibility Graph Networks for Carbon Price Forecasting44 cited
    • 2023A novel interval-valued carbon price analysis and forecasting system based on multi-objective ensemble strategy for carbon trading market42 cited