Identification of daily oil price shocks and their uncertainties via conditional heteroskedasticity

Supplement to “Identification of daily oil price shocks and their uncertainties via conditional heteroskedasticity”

Asymetric Shocks and Long-Memory Volatility: An Egarch Approach to Global Oil and Local Import Dynamics

This study investigates the volatility dynamics of commodity import prices in Republic of Moldova and global Brent crude oil prices, employing advanced econometric models to enhance understanding of risk in small open economies and energy markets. Utilizing monthly data from 1992 to 2025 for Republic of Moldova's Commo...

The Role of Energy Market Uncertainties in Forecasting US State-Level Stock Market Volatility: A GARCH-MIDAS Approach

In this paper, we employ the generalized autoregressive conditional heteroscedasticity-mixed data sampling (GARCH-MIDAS) framework to forecast the daily volatility of state-level stock returns in the United States based on monthly metrics of oil price uncertainty (OPU) and the broader energy uncertainty index (EUI). Th...

Price Conflict and US Stock Return Volatility Forecasting: Insights from over 150 Years with a Mixed-Frequency Framework

Untangling the Asymmetric Effects of Oil Price Dynamics and Disaggregated Shocks on Economic Policy Uncertainty: Evidence from India

India’s economic policy uncertainty (EPU) is significantly affected by global commodity market fluctuations, particularly oil prices. Oil-related shocks, such as supply, demand and risk, have been shown to affect domestic, economic and financial conditions in the previous literature, but the effects of these shocks hav...

Conditional projection methods for large-scale Bayesian VARs

This work develops fast methods for conditional forecasting and structural scenario analysis with high-dimensional Bayesian vector autoregressions (VARs) and compute counterfactual predictions for oil price scenarios in the context of the 2026 closure of the Strait of Hormuz.