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Exploring the predictability of attention mechanism with LSTM: Evidence from EU carbon futures prices
16 references·0 citing·41 second hop
Exploring the predictability of attention mechanism with LSTM: Evidence from EU carbon futures prices (2023)Exploring the predictability of attention…The marginal impacts of energy prices on carbon price variations: Evidence from a quantile-on-quantile approach (2021)The marginal impacts of energ…A hybrid model for carbon price forecastingusing GARCH and long short-term memory network (2021)A hybrid model for carbon pri…On the nonlinear relationship between energy use and CO2 emissions within an EKC framework: Evidence from panel smooth transition regression in the MENA region (2020)On the nonlinear relationship…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…Modelling carbon emission intensity: Application of artificial neural network (2019)Modelling carbon emission int…Forecasting carbon prices in the Shenzhen market, China: The role of mixed-frequency factors (2019)Forecasting carbon prices in …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 …Forecasting carbon price using empirical mode decomposition and evolutionary least squares support vector regression (2017)Forecasting carbon price usin…Risk spillovers across the energy and carbon markets and hedging strategies for carbon risk (2015)Risk spillovers across the en…A model of carbon price interactions with macroeconomic and energy dynamics (2011)A model of carbon price inter…Price drivers and structural breaks in European carbon prices 2005–2007 (2008)Price drivers and structural …Modeling the price dynamics of CO2 emission allowances (2008)Modeling the price dynamics o…An econometric analysis of emission allowance prices (2008)An econometric analysis of em…Forecasting Volatility in Financial Markets: A Review (2003)Forecasting Volatility in Fin…Minimum Lagrange Multiplier Unit Root Test with Two Structural Breaks (2003)Allowance price drivers in the first phase of the EU ETS (2009)Pricing Carbon: The European Union Emissions Trading Scheme (2010)Causes of the EU ETS price drop: Recession, CDM, renewable policies or a bit of everything?—New evidence (2014)Stable Paretian Models in Finance (2000)VOLATILITY CLUSTERING IN FINANCIAL MARKETS: A MICROSIMULATION OF INTERACTING AGENTS (2000)Decisions from Experience and the Effect of Rare Events in Risky Choice (2004)Modeling CO2 emission allowance prices and derivatives: Evidence from the European trading scheme (2009)Carbon emissions and stock returns: Evidence from the EU Emissions Trading Scheme (2015)A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle (1989)The Determinants of Credit Spread Changes (2001)Analysis of Financial Time Series (2006)Forecasting carbon futures volatility using GARCH models with energy volatilities (2013)China's carbon emissions trading and stock returns (2019)Autoregressive conditional heteroskedasticity and changes in regime (1994)Modeling Asymmetric Comovements of Asset Returns (1998)Dynamic Conditional Correlation (2002)Optimal hedge ratios for clean energy equities (2018)The spillover effects among fossil fuel, renewables and carbon markets: Evidence under the dual dilemma of climate change and energy crises (2023)Comparing Predictive Accuracy (1994)Comparing Predictive Accuracy (1995)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)Machine learning in energy economics and finance: A review (2019)Carbon price forecasting based on CEEMDAN and LSTM (2022)Generalized autoregressive conditional heteroskedasticity (1986)A forecast comparison of volatility models: does anything beat a GARCH(1,1)? 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Evidence from China (2016)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)The directional volatility connectedness between crude oil and equity markets: New evidence from implied volatility indexes (2016)Financial time series forecasting model based on CEEMDAN and LSTM (2018)Pricing Climate Change Exposure (2021)
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References

  • 2003Forecasting Volatility in Financial Markets: A Review800 cited
  • 2008Price drivers and structural breaks in European carbon prices 2005–2007725 cited
  • 2008Modeling the price dynamics of CO2 emission allowances697 cited
  • 2021A hybrid model for carbon price forecastingusing GARCH and long short-term memory network328 cited
  • 2008An econometric analysis of emission allowance prices327 cited
  • 2017Forecasting carbon price using empirical mode decomposition and evolutionary least squares support vector regression310 cited
  • 2011A model of carbon price interactions with macroeconomic and energy dynamics262 cited
  • 2019Modelling carbon emission intensity: Application of artificial neural network256 cited
  • 2015Risk spillovers across the energy and carbon markets and hedging strategies for carbon risk248 cited
  • 2018A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting235 cited
  • 2021The marginal impacts of energy prices on carbon price variations: Evidence from a quantile-on-quantile approach233 cited
  • 2019Forecasting carbon prices in the Shenzhen market, China: The role of mixed-frequency factors208 cited
  • 2018Usefulness of economic and energy data at different frequencies for carbon price forecasting in the EU ETS198 cited
  • 2018Analysis and forecasting of the carbon price using multi—resolution singular value decomposition and extreme learning machine optimized by adaptive whale optimization algorithm

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181 cited
  • 2020On the nonlinear relationship between energy use and CO2 emissions within an EKC framework: Evidence from panel smooth transition regression in the MENA region154 cited
  • 2020Carbon price forecasting based on modified ensemble empirical mode decomposition and long short-term memory optimized by improved whale optimization algorithm144 cited
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