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A decomposition–integration model with dynamic fuzzy reconstruction for crude oil price prediction and the implications for sustainable development
16 references·1 citing·47 second hop
A decomposition–integration model with dynamic fuzzy reconstruction for crude oil price prediction and the implications for sustainable development (2019)A decomposition–integration model with dy…Information linkage, dynamic spillovers in prices and volatility between the carbon and energy markets (2018)Information linkage, dynamic …Global crude oil price prediction and synchronization based accuracy evaluation using random wavelet neural network (2018)Global crude oil price predic…Oil price uncertainty and clean energy stock returns: New evidence from crude oil volatility index (2017)Oil price uncertainty and cle…Forecasting carbon price using empirical mode decomposition and evolutionary least squares support vector regression (2017)Forecasting carbon price usin…Oil Price Volatility Forecast with Mixture Memory GARCH (2015)Oil Price Volatility Forecast…A Novel CEEMD-Based EELM Ensemble Learning Paradigm for Crude Oil Price Forecasting (2014)A Novel CEEMD-Based EELM Ense…Quantifying the speculative component in the real price of oil: The role of global oil inventories (2013)Quantifying the speculative c…Does the price of oil interact with clean energy prices in the stock market? (2013)Does the price of oil interac…Stock prices of clean energy firms, oil and carbon markets: A vector autoregressive analysis (2011)Stock prices of clean energy …Time series analysis forecasting and control (2009)Time series analysis forecast…A new approach for crude oil price analysis based on Empirical Mode Decomposition (2007)A new approach for crude oil …Forecasting Nonlinear Crude Oil Futures Prices (2006)Forecasting Nonlinear Crude O…On the predictive accuracy of crude oil futures prices (2003)On the predictive accuracy of…A semiparametric approach to short-term oil price forecasting (2001)A semiparametric approach to …A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks (1995)A Model-Selection Approach to…Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecas…McVCsB: A new hybrid deep learning network for stock index prediction (2023)McVCsB: A new hybrid deep lea…Macroeconomics and Reality (1980)A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle (1989)Discretion versus policy rules in practice (1993)International crude oil prices and the stock prices of clean energy and technology companies: Evidence from non-linear cointegration tests with unknown structural breaks (2016)Time-frequency connectedness among clean-energy stocks and fossil fuel markets: Comparison between financial, oil and pandemic crisis (2021)Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Generalized autoregressive conditional heteroskedasticity (1986)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)A COMPARISON OF VAR AND NEURAL NETWORKS WITH GENETIC ALGORITHM IN FORECASTING PRICE OF OIL (2004)Modelling and forecasting fossil fuels, CO2 and electricity prices and their volatilities (2012)Modelling oil price volatility with structural breaks (2012)Causes and Consequences of the Oil Shock of 2007–08 (2009)Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market (2009)THE ROLE OF INVENTORIES AND SPECULATIVE TRADING IN THE GLOBAL MARKET FOR CRUDE OIL (2013)Speculation in the Oil Market (2014)Modeling Fluctuations in the Global Demand for Commodities (2017)Oil price elasticities and oil price fluctuations (2018)Imperfect Competition and the Effects of Energy Price Increases on Economic Activity (1996)The Long-Run Evolution of Energy Prices (1999)Applications of Hilbert–Huang transform to non‐stationary financial time series analysis (2003)Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method (2009)A novel hybrid method for crude oil price forecasting (2015)A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting (2018)Statistical inference in vector autoregressions with possibly integrated processes (1995)Generalized impulse response analysis in linear multivariate models (1998)Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold (2013)Is there dependence and systemic risk between oil and renewable energy stock prices? (2014)Wavelet-based test of co-movement and causality between oil and renewable energy stock prices (2016)Comparing Predictive Accuracy (1994)Comparing Predictive Accuracy (1995)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)A carbon price prediction model based on secondary decomposition algorithm and optimized back propagation neural network (2019)Carbon trading volume and price forecasting in China using multiple machine learning models (2019)China's carbon emissions trading and stock returns (2019)The Extreme Value Method for Estimating the Variance of the Rate of Return (1980)Oil and the Stock Markets (1996)THE IMPACT OF OIL PRICE SHOCKS ON THE U.S. STOCK MARKET* (2009)Asymmetric impacts of oil price uncertainty on Chinese stock returns under different market conditions: Evidence from oil volatility index (2018)The dynamic dependence of fossil energy, investor sentiment and renewable energy stock markets (2019)Crude oil prices and clean energy stock indices: Lagged and asymmetric effects with quantile regression (2020)Impulse response analysis in nonlinear multivariate models (1996)On the network topology of variance decompositions: Measuring the connectedness of financial firms (2014)How connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics (2020)The predictive power of online chatter (2005)Quantile regression for dynamic panel data with fixed effects (2011)Tourism demand forecasting: A deep learning approach (2019)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)
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References

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114 cited
  • 2018Global crude oil price prediction and synchronization based accuracy evaluation using random wavelet neural network92 cited
  • 2003On the predictive accuracy of crude oil futures prices91 cited
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