Why Do ICRG’s Political Risk Metrics for OPEC Countries Contribute to Roughly 17.6% of Oil Price Fluctuations?

Historically, the stock market’s reaction to geopolitical shocks is characterized by a sharp, short-lived drawdown followed by a rapid recovery. Indeed, data from major wars since 1926 shows an average one-day drop of -1.1% at the onset of a conflict. The total average drawdown (bottoming out) is approximately -4.7%, typically reached within 19 days. In terms of recovery, on average, markets fully recover these losses within 42 to 47 days.

Since the direct conflict between the U.S., Israel, and Iran escalated over the weekend of March 1–2, 2026, US stock market futures have dropped by approximately 1% to 1.5% as of Monday morning trading.

That’s the basic backdrop: here are some examples from past wars:

1/ 1990 Gulf War: The S&P 500 dropped about 10% immediately after Iraq invaded Kuwait but rose 24% from its trough by the time the ground invasion began in February 1991.

2/ 2003 Iraq War: The market rose 13.6% in the first three months of the conflict.

3/ 2022 Russia-Ukraine War: The S&P 500 initially fell 7% but rebounded to pre-invasion levels within a few months. 

Because PRS has its own prop trading desk we do look at asset allocation on a general level and how our data and International Country Risk Guide (ICRG) helps predict price changes.  

So what do we see now? Over a three-month period, energy stocks perform well (that’s obvious) but so do defense stocks. Stocks like Lockheed Martin (LMT) and Northrop Grumman (NOC) have previously gained 40%–46% during similar escalations.  Gold does well, and the USD tends to strengthen as the ‘flight-to-safety’ trade kicks in.

However, there are some risks to the upside: The primary outlier in historical data is the 1973 Yom Kippur War. Because it led to a persistent oil embargo and tripled U.S. oil prices, it triggered a recession where the S&P 500 fell 40% over the following year. Analysts today warn that if the Strait of Hormuz is closed for a prolonged period, it could mirror this 1970s “stagflation” scenario rather than the more common quick-recovery pattern of the 1990s or 2000s.  Conversely, some sectors are expected to move lower over the next 90 days, particularly consumer discretionary and commercial aviation, due to higher fuel costs and airspace closures.

The Iran conflict and oil price surge is transmitted through the ICRG’s scoring of Iran via a decline in the Composite Risk Scores, driven by three sub-indices: Political, Economic, and Financial. 

In the current March 2026 landscape, here is how the ICRG components are reacting to these specific shifts:

1/ Political Risk (100 Points)

The transition from proxy struggles to direct interstate warfare in early 2026 has triggered significant drops in political risk points (where lower points = higher risk). 

External Conflict: This variable is the most immediately impacted. As of late February 2026, the ICRG has moved the risk status for Iran and regional actors from “low-level friction” to “all-out war,” drastically lowering their scores.

Government Stability: Scores for Iran have deteriorated due to “regime risk shocks” following the reported death of leadership and resulting domestic chaos.

Investment Profile: This reflects the risk of contract repudiation or expropriation. For regional actors, this score would drop as “strategic ambiguity” vanishes and nations are forced to pick sides in the conflict. 

2/Economic Risk (50 Points)

The surge in oil prices creates a divergent “wealth vs. uncertainty” effect in ICRG ratings. 

Annual Inflation Rate: For the U.S. and oil-importing nations, this variable’s score would decrease as energy-driven inflation spikes toward $100/barrel.

Budget Balance: Interestingly, oil exporters (like those in the Gulf) might see a short-term improvement in this specific sub-score due to higher petrodollar revenues, though this is often offset by the higher security costs reflected in the Political index.

Real GDP Growth: Expect lower scores globally as high energy costs act as a “tax” on industrial production and consumer demand. 

3/Financial Risk (50 Points)

This index monitors a country’s ability to pay its way.

International Liquidity: Conflict in the Strait of Hormuz threatens 20% of global oil/LNG transit, leading to a “liquidity crisis” for nations dependent on these revenues or imports.

Exchange Rate Stability: The ICRG would reflect the volatility of regional currencies and the “flight-to-safety” strength of the U.S. Dollar, which is currently expected to stabilize at higher levels due to its status as a net energy exporter. 

Oil Prices and the International Country Risk Guide

So what does the empirical literature say about about oil prices as it affects the ICRG? Historically, the ICRG’s political risk metrics for OPEC countries contribute to roughly 17.6% of oil price fluctuations, second only to direct demand shocks. This means the data doesn’t just reflect the changes—it is often used by traders to predict the next leg of the oil rally

The 17.6% figure is derived from an empirical study titled “Impacts of OPEC’s political risk on the international crude oil prices: An empirical analysis based on the SVAR models,” published in the journal Energy Economics. 

Key Findings of the Study

The research analyzed the relationship between political risk and oil prices using monthly data from January 1998 to September 2014. It utilized the International Country Risk Guide (ICRG) index as the primary proxy for measuring political instability within OPEC nations. 

Contribution to Fluctuations: The study found that OPEC’s integrated political risk accounts for 17.58% (often rounded to 17.6%) of international oil price fluctuations.

Ranking of Drivers: This risk factor was identified as the second largest contributor to price volatility, surpassed only by oil demand shocks, which accounted for 34.64%of fluctuations during the same period.

Regional Impact: The research further specified that political risks originating in the Middle East have the most significant impact on global prices compared to risks in OPEC’s North African or South American member states.

Specific Risk Factors: Among the various components of political risk tracked by the ICRG, internal conflicts within OPEC nations were found to be the most influential drivers of price changes. 

ICRG v Web Scrapers: Quelle est la grande différence (si vous devez absolument le demander) ?

Looking at the empirical results generated by using the ICRG, where then might the geopolitical web scrapers fail? These are the geopolitical risk groups that typically fall into the category of “sentiment-based” or “high-frequency” AI risk groups.

While my firm uses a number of internal RAG platforms to gain insights and adjust the ratings in a more nuanced way, and while some of the more recent arrivals to the “sentiment scene” are staffed by very well-qualified individuals – some of whom are friends – the early interactions I had with them were rather depressing, as they came across as basically policy hacks who assumed that by gathering information from millions of sources each minute of the day better analysis (and decisions) would be the result.  The bottom line is that while they are highly effective at capturing market “noise” and immediate panic, these groups often struggle to replicate the structural, empirical depth of a study based on the ICRG.

The reason these groups “can’t do things like this” (referring to the stable 17.6% attribution) boils down to methodological depth vs. high-frequency breadth.

1/ The “Blinking” vs. “Heart Attack” Problem

A primary critique from risk analysts in early 2026 is that web-scraping groups monitor high-frequency data—like counting how many times a term is mentioned—which is akin to “trying to predict a heart attack by counting how many times a patient blinks”. 

The ICRG operates on “structural reality,” measuring deep-tier metrics like Bureaucracy Quality and Government Stability that cannot be “read” from a news feed alone.

Web Scrapers rely on Natural Language Processing (NLP) to scrape news and social media. They are often unable to distinguish between “performative political theater” (viral hashtags/protests) and actual structural regime shifts. 

2/ The Dominant Web-Scraping Model: Caldara and Iacoviello 

The most prominent “scraper” methodology is the Geopolitical Risk (GPR) Index developed by Dario Caldara and Matteo Iacoviello, which uses automated text-search algorithms to count keywords related to geopolitical tensions across leading international newspapers.

However, as a dictionary-based method, it faces “false positives” from irrelevant keyword matches and an inability to assess the intensity or centrality of the content. It captures attention to risk rather than the underlying quality of a country’s risk environment. 

Why Empirical Attribution (like the 17.6%) is Hard for Scrapers?

Studies such as the one cited above  – the one that uses SVAR (Structural Vector Autoregression) models – require decades of stable, consistent data points to calculate how much one variable (political risk) contributes to another (oil price) over time. 

Unlike the ICRG, has provided consistent, month-over-month risk ratings for over 140 countries since 1984, web-scraped data is often too “noisy” and volatile for long-term SVAR models. While scrapers are better at out-of-sample near-term predictions, they frequently underperform over the long term compared to stable structural models like the ICRG.

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CHRISTOPHER MCKEE, PHD CHIEF EXECUTIVE

Christopher McKee is PRS’ CEO and Owner. An international political economist, global investor, entrepreneur, and author, Chris received his PhD from Queen’s University (Canada) and has been involved in the field of geopolitical risk, limited recourse financing, and private sector development for the past 25 years.