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Transformer-based forecasting for intraday trading in the Shanghai crude oil market: Analyzing open-high-low-close prices
16 references·2 citing·49 second hop
Transformer-based forecasting for intraday trading in the Shanghai crude oil market: Analyzing open-high-low-close prices (2023)Transformer-based forecasting for intrada…Transformer-based attention network for stock movement prediction (2022)Transformer-based attention n…Stock market index prediction using deep Transformer model (2022)Stock market index prediction…A new crude oil price forecasting model based on variational mode decomposition (2020)A new crude oil price forecas…China’s crude oil futures: Introduction and some stylized facts (2018)China’s crude oil futures: In…Dependence changes between the carbon price and its fundamentals: A quantile regression approach (2017)Dependence changes between th…Deep learning with long short-term memory networks for financial market predictions (2017)Deep learning with long short…A feature weighted support vector machine and K-nearest neighbor algorithm for stock market indices prediction (2017)A feature weighted support ve…A deep learning ensemble approach for crude oil price forecasting (2017)A deep learning ensemble appr…A novel hybrid method for crude oil price forecasting (2015)A novel hybrid method for cru…Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling (2011)Crude oil price forecasting: …Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models (2008)Volatility in crude oil futur…A New Method for Crude Oil Price Forecasting Based on Support Vector Machines (2006)A New Method for Crude Oil Pr…Modeling and forecasting cointegrated relationships among heavy oil and product prices (2005)Modeling and forecasting coin…Pairs Trading: Quantitative Methods and Analysis (2004)Pairs Trading: Quantitative M…The Long-Run Evolution of Energy Prices (1999)The Long-Run Evolution of Ene…Principles of corporate finance (1982)Principles of corporate finan…Major Issues in High-Frequency Financial Data Analysis: A Survey of Solutions (2025)Major Issues in High-Frequenc…Model-driven multimodal LSTM-CNN for unbiased structural forecasting of European Union allowances open-high-low-close price (2024)Model-driven multimodal LSTM-…The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis (1989)Investment under Uncertainty (1994)Investment Under Uncertainty. 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References

  • 2017Deep learning with long short-term memory networks for financial market predictions2,827 cited
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  • 2017A deep learning ensemble approach for crude oil price forecasting383 cited
  • 2017A feature weighted support vector machine and K-nearest neighbor algorithm for stock market indices prediction382 cited
  • 2022Stock market index prediction using deep Transformer model371 cited
  • 2004Pairs Trading: Quantitative Methods and Analysis345 cited
  • 2008Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models304 cited
  • 2011Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling282 cited
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  • 2022Transformer-based attention network for stock movement prediction241 cited
  • 2018China’s crude oil futures: Introduction and some stylized facts194 cited
  • 2017Dependence changes between the carbon price and its fundamentals: A quantile regression approach176 cited

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2020
A new crude oil price forecasting model based on variational mode decomposition
172 cited
  • 2005Modeling and forecasting cointegrated relationships among heavy oil and product prices172 cited
  • Cited by

    • 2024Model-driven multimodal LSTM-CNN for unbiased structural forecasting of European Union allowances open-high-low-close price32 cited
    • 2025Major Issues in High-Frequency Financial Data Analysis: A Survey of Solutions28 cited