SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
An ICA-based support vector regression scheme for forecasting crude oil prices
16 references·14 citing·40 second hop
An ICA-based support vector regression scheme for forecasting crude oil prices (2016)An ICA-based support vector regression sc…Oil price forecasting using gene expression programming and artificial neural networks (2016)Oil price forecasting using g…A data analytic approach to forecasting daily stock returns in an emerging market (2016)A data analytic approach to f…Forecasting crude oil market volatility: A Markov switching multifractal volatility approach (2015)Forecasting crude oil market …A novel hybrid method for crude oil price forecasting (2015)A novel hybrid method for cru…A novel decomposition ensemble model with extended extreme learning machine for crude oil price forecasting (2015)A novel decomposition ensembl…A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting (2015)A decomposition–ensemble mode…A Novel CEEMD-Based EELM Ensemble Learning Paradigm for Crude Oil Price Forecasting (2014)A Novel CEEMD-Based EELM Ense…A compressed sensing based AI learning paradigm for crude oil price forecasting (2014)A compressed sensing based AI…Crude oil price analysis and forecasting using wavelet decomposed ensemble model (2012)Crude oil price analysis and …Carbon price forecasting with a novel hybrid ARIMA and least squares support vector machines methodology (2012)Carbon price forecasting with…Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling (2011)Crude oil price forecasting: …A flexible neural network-fuzzy mathematical programming algorithm for improvement of oil price estimation and forecasting (2011)A flexible neural network-fuz…Financial time series forecasting using independent component analysis and support vector regression (2009)Financial time series forecas…Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method (2009)Estimating the impact of extr…A New Method for Crude Oil Price Forecasting Based on Support Vector Machines (2006)A New Method for Crude Oil Pr…Application of support vector machines in financial time series forecasting (2001)Application of support vector…A New Approach for Forecasting Crude Oil Prices Based on Stochastic and Deterministic Influences of LMD Using ARIMA and LSTM Models (2023)A New Approach for Forecastin…Deterministic and uncertainty crude oil price forecasting based on outlier detection and modified multi-objective optimization algorithm (2022)Deterministic and uncertainty…Asian stock markets closing index forecast based on secondary decomposition, multi-factor analysis and attention-based LSTM model (2022)Asian stock markets closing i…Multi-Perspective Crude Oil Price Forecasting with a New Decomposition-Ensemble Framework (2021)Multi-Perspective Crude Oil P…Forecasting mid-price movement of Bitcoin futures using machine learning (2021)Forecasting mid-price movemen…Support Vector Machine Algorithms: An Application to Ship Price Forecasting (2020)Support Vector Machine Algori…Forecasting Volatility of Energy Commodities: Comparison of GARCH Models with Support Vector Regression (2020)Forecasting Volatility of Ene…Crude Oil Prices Forecasting: An Approach of Using CEEMDAN-Based Multi-Layer Gated Recurrent Unit Networks (2020)Crude Oil Prices Forecasting:…A novel hybrid approach to forecast crude oil futures using intraday data (2020)A novel hybrid approach to fo…CPPCNDL: Crude oil price prediction using complex network and deep learning algorithms (2019)CPPCNDL: Crude oil price pred…Forecasting the WTI crude oil price by a hybrid-refined method (2018)Forecasting the WTI crude oil…A novel method based on numerical fitting for oil price trend forecasting (2018)A novel method based on numer…A Novel Decomposition-Ensemble Based Carbon Price Forecasting Model Integrated with Local Polynomial Prediction (2018)A Novel Decomposition-Ensembl…Forecasting Crude Oil Price Using EEMD and RVM with Adaptive PSO-Based Kernels (2016)Forecasting Crude Oil Price U…Forecasting stock market movement direction with support vector machine (2004)Online big data-driven oil consumption forecasting with Google trends (2018)Comparing Predictive Accuracy (1994)Use of Cumulative Sums of Squares for Retrospective Detection of Changes of Variance (1994)Comparing Predictive Accuracy (1995)A multiscale analysis for carbon price drivers (2018)Carbon price forecasting with variational mode decomposition and optimal combined model (2018)Oil price forecasting using a hybrid model (2018)Event Studies in Economics and Finance (1997)A new approach for crude oil price analysis based on Empirical Mode Decomposition (2007)Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm (2008)Oil price volatility and oil-related events: An Internet concern study perspective (2014)Impacts of OPEC's political risk on the international crude oil prices: An empirical analysis based on the SVAR models (2016)The impact of extreme events on energy price risk (2021)Generalized autoregressive conditional heteroskedasticity (1986)Modeling and forecasting petroleum futures volatility (2006)A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting (2018)Crude oil time series prediction model based on LSTM network with chaotic Henry gas solubility optimization (2021)Price forecasting through neural networks for crude oil, heating oil, and natural gas (2024)Designing a neural network for forecasting financial and economic time series (1996)Forecasting with artificial neural networks: (1998)Wavelet-based evidence of the impact of oil prices on stock returns (2013)Improved EEMD-based crude oil price forecasting using LSTM networks (2018)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)Forecasting carbon price using empirical mode decomposition and evolutionary least squares support vector regression (2017)Carbon trading volume and price forecasting in China using multiple machine learning models (2019)A hybrid model for carbon price forecastingusing GARCH and long short-term memory network (2021)The Combination of Forecasts (1969)Empirical exchange rate models of the seventies (1983)Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach (2015)The effect of global oil price shocks on China's agricultural commodities (2015)Time Series Analysis: Forecasting and Control (1977)Stock price prediction using support vector regression on daily and up to the minute prices (2018)Optimizing LSTM for time series prediction in Indian stock market (2020)Machine learning techniques and data for stock market forecasting: A literature review (2022)Support vector machine with adaptive parameters in financial time series forecasting (2003)Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey (2009)Hybrid Variational Mode Decomposition and evolutionary robust kernel extreme learning machine for stock price and movement prediction on daily basis (2018)Oil price forecasting: A hybrid GRU neural network based on decomposition–reconstruction methods (2023)
this work references cited by second hop

References

  • 2001Application of support vector machines in financial time series forecasting1,270 cited
  • 2009Financial time series forecasting using independent component analysis and support vector regression538 cited
  • 2012Carbon price forecasting with a novel hybrid ARIMA and least squares support vector machines methodology376 cited
  • 2011Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling282 cited
  • 2015A novel hybrid method for crude oil price forecasting272 cited
  • 2006A New Method for Crude Oil Price Forecasting Based on Support Vector Machines258 cited
  • 2009Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method253 cited
  • 2015A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting204 cited
  • 2015A novel decomposition ensemble model with extended extreme learning machine for crude oil price forecasting204 cited
  • 2012Crude oil price analysis and forecasting using wavelet decomposed ensemble model146 cited
  • 2014A Novel CEEMD-Based EELM Ensemble Learning Paradigm for Crude Oil Price Forecasting138 cited
  • 2016Oil price forecasting using gene expression programming and artificial neural networks127 cited
  • 2015Forecasting crude oil market volatility: A Markov switching multifractal volatility approach125 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

2014
A compressed sensing based AI learning paradigm for crude oil price forecasting
122 cited
  • 2016A data analytic approach to forecasting daily stock returns in an emerging market111 cited
  • 2011A flexible neural network-fuzzy mathematical programming algorithm for improvement of oil price estimation and forecasting105 cited
  • Cited by

    • 2018Forecasting the WTI crude oil price by a hybrid-refined method97 cited
    • 2021Forecasting mid-price movement of Bitcoin futures using machine learning84 cited
    • 2022Asian stock markets closing index forecast based on secondary decomposition, multi-factor analysis and attention-based LSTM model84 cited
    • 2020Support Vector Machine Algorithms: An Application to Ship Price Forecasting61 cited
    • 2020A novel hybrid approach to forecast crude oil futures using intraday data60 cited
    • 2018A novel method based on numerical fitting for oil price trend forecasting60 cited
    • 2022Deterministic and uncertainty crude oil price forecasting based on outlier detection and modified multi-objective optimization algorithm57 cited
    • 2019CPPCNDL: Crude oil price prediction using complex network and deep learning algorithms54 cited
    • 2018A Novel Decomposition-Ensemble Based Carbon Price Forecasting Model Integrated with Local Polynomial Prediction52 cited
    • 2016Forecasting Crude Oil Price Using EEMD and RVM with Adaptive PSO-Based Kernels52 cited
    • 2023A New Approach for Forecasting Crude Oil Prices Based on Stochastic and Deterministic Influences of LMD Using ARIMA and LSTM Models51 cited
    • 2021Multi-Perspective Crude Oil Price Forecasting with a New Decomposition-Ensemble Framework46 cited
    • 2020Crude Oil Prices Forecasting: An Approach of Using CEEMDAN-Based Multi-Layer Gated Recurrent Unit Networks41 cited
    • 2020Forecasting Volatility of Energy Commodities: Comparison of GARCH Models with Support Vector Regression36 cited