The key goals of the research are to: 1- Evaluate the possibility of predicting energy market returns by incorporating stock market variables and factors, and identify the predictive relationship between stock market anomalies and energy market futures returns. 2- Propose the use of high-frequency and daily news data for more accurate measurement and forecast of daily energy futures returns, and determine how daily variations in futures returns within the energy market can be accounted for by news data. 3- Enhance the explanatory power of existing predictive models by incorporating high-frequency and daily news data along with macroeconomic indicators and MF models to predict daily energy futures returns. 4- Investigate how the divergence in opinion can explain part of the variation in the daily futures returns in the energy market. 5- Demonstrate that the use of high-frequency news data can provide a more complete understanding of the energy market pricing mechanisms, enable energy market participants to make informed investment decisions, and assist regulators and policymakers in monitoring the market, detecting potential risks, and making better-informed decisions.

2022

2026