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Volatility forecasting for crude oil based on text information and deep learning PSO‐LSTM model
12 references·0 citing·46 second hop
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References

  • 1986Generalized autoregressive conditional heteroskedasticity22,329 cited
  • 2008Oil price shocks and stock markets in the U.S. and 13 European countries1,264 cited
  • 2006Modeling and forecasting petroleum futures volatility479 cited
  • 2018Text-based crude oil price forecasting: A deep learning approach305 cited
  • 1999The relationship between spot and futures prices: Evidence from the crude oil market290 cited
  • 2009Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method253 cited
  • 2017Investor sentiment and the price of oil232 cited
  • 2019Novel volatility forecasting using deep learning–Long Short Term Memory Recurrent Neural Networks208 cited
  • 2019Oil financialization and volatility forecast: Evidence from multidimensional predictors154 cited
  • 2011The influence of multiple goals on driving behavior: The case of safety, time saving, and fuel saving102 cited
  • 2017Forecasting Crude Oil Prices: A Comparison Between Artificial Neural Networks and Vector Autoregressive Models81 cited
  • 2019Modeling and forecasting commodity market volatility with long‐term economic and financial variables81 cited

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