Answers are grounded in this paper and cite their sources.
This paper examines the links between global benchmark pricing and local and regional economic and geopolitical fluctuations. We introduce a heavy oil price index based on a revenue-based storage valuation model that ties the value of storage to the spread between the price of heavy oil purchased from regional competitors and the domestic spot price. This value can be interpreted as a benchmark heavy oil price, reflecting the shadow price of storage, and is modeled as a simple spread option. High frequency daily data is used to determine the shadow value of heavy crude oil storage at different strategic locations. The values are aggregated to derive a global heavy crude oil storage index as a benchmark for heavy oil prices. The index captures major price movements among the leading heavy oil and primary benchmarks and can be used to provide advanced signals for energy policy and market balancing. To assess its sensitivity to geopolitical conditions, we incorporate news-based geopolitical risk (GPR) and market-based volatility (COVOL) measures within HAR-type and instrumental variable frameworks. The results indicate that the index reflects both geopolitical shocks and market volatility, with distinct short- and long-term dynamics across index specifications. The index also demonstrates improved forecasting performance relative to naive autoregressive benchmarks for heavy crudes such as Basrah, as well as WTI and Brent.
No takes yet. Share an insight, caveat, or question.
Considine et al. (2026) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: