OOIR: Observatory of International Research

Papers

(The H4-Index of Journal of Forecasting is 20. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-11-01 to 2024-11-01.)

Article	Citations
The information content of uncertainty indices for natural gas futures volatility forecasting	75
Forecasting carbon price using a multi‐objective least squares support vector machine with mixture kernels	68
Trading volume and realized volatility forecasting: Evidence from the China stock market	56
Global economic policy uncertainty and gold futures market volatility: Evidence from Markov regime‐switching GARCH‐MIDAS models	45
Mixed‐frequency forecasting of crude oil volatility based on the information content of global economic conditions	36
Predicting stock market volatility based on textual sentiment: A nonlinear analysis	36
Forecasting stock return volatility: The role of shrinkage approaches in a data‐rich environment	32
A new BISARMA time series model for forecasting mortality using weather and particulate matter data	29
An empirical study on the role of trading volume and data frequency in volatility forecasting	27
Which factors drive Bitcoin volatility: Macroeconomic, technical, or both?	27
A bi‐level ensemble learning approach to complex time series forecasting: Taking exchange rates as an example	26
Forecasting unemployment in the euro area with machine learning	24
Forecasting US stock market volatility: How to use international volatility information	24
Research constituents, intellectual structure, and collaboration pattern in the Journal of Forecasting: A bibliometric analysis	22
Forecasting the volatility of agricultural commodity futures: The role of co‐volatility and oil volatility	22
Forecasting realized volatility of international REITs: The role of realized skewness and realized kurtosis	21
Forecasting international equity market volatility: A new approach	21
Predicting financial crises with machine learning methods	21
Time series forecasting methods for the Baltic dry index	21
Volatility forecasting for crude oil based on text information and deep learning PSO‐LSTM model	20
Optimal hybrid framework for carbon price forecasting using time series analysis and least squares support vector machine	20