Fortify the investment performance of crude oil market by integrating sentiment analysis and an interval-based trading strategy

This publication has 48 references indexed in Scilit:

• Impact of regulatory framework on bidding behavior of firms: Policy implications for the oil & gas sector
  Energy Policy, 2019
• An Adaptive Hybrid Learning Paradigm Integrating CEEMD, ARIMA and SBL for Crude Oil Price Forecasting
  Energies, 2019
• Chinese Text Sentiment Analysis Based on Extended Sentiment Dictionary
  IEEE Access, 2019
• Asymmetric pass-through of oil prices to gasoline prices with interval time series modelling
  Energy Economics, 2019
• Interval decomposition ensemble approach for crude oil price forecasting
  Energy Economics, 2018
• Forecasting Crude Oil Prices: A Comparison Between Artificial Neural Networks and Vector Autoregressive Models
  Computational Economics, 2017
• Bagging exponential smoothing methods using STL decomposition and Box–Cox transformation
  International Journal of Forecasting, 2016
• Investigating the price discovery and risk transfer functions in the crude oil and gasoline futures markets: Some empirical evidence
  Applied Energy, 2013
• Stock index return forecasting: The information of the constituents
  Economics Letters, 2012
• iMLP: Applying Multi-Layer Perceptrons to Interval-Valued Data
  Neural Processing Letters, 2007