The proliferation of geopolitical risk indices over the past decade reflects a growing appetite among investors, policymakers, and corporate strategists for quantifiable measures of political uncertainty. From the Caldara-Iacoviello Geopolitical Risk Index to BlackRock’s proprietary measures and countless consultancy offerings, the market for geopolitical risk metrics has never been more crowded. But a fundamental question persists: can these indices actually be forecast?
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The answer matters enormously. If geopolitical risk is inherently unpredictable, then these indices serve primarily as contemporaneous sentiment indicators rather than forward-looking tools. If some degree of forecasting is possible, then substantial alpha awaits those who can anticipate shifts before they materialise in asset prices.
The fat tail problem
Before examining forecastability, we must confront an uncomfortable reality: geopolitical risk is fundamentally fat-tailed. The distribution of geopolitical events bears little resemblance to the Gaussian assumptions underlying most forecasting methodologies. Small perturbations occur frequently; catastrophic ruptures occur rarely but with consequences that dwarf the cumulative impact of routine volatility.
This matters for forecasting in ways that are often underappreciated. Standard time-series approaches optimise for minimising average forecast error, but in fat-tailed domains, the average is dominated by extreme events that lie outside historical sample ranges. A model that accurately forecasts 95 percent of observations may be worse than useless if it systematically misses the 5 percent that actually matter for portfolio outcomes.
The assassination of Archduke Franz Ferdinand in Sarajevo, the fall of the Berlin Wall, the September 11 attacks, the Arab Spring, the COVID-19 pandemic—these are not events amenable to time-series extrapolation. They represent genuine discontinuities, phase transitions in complex adaptive systems that cannot be reliably predicted from prior observations. Yet they account for the overwhelming majority of realised geopolitical risk in portfolio terms.
The case for unpredictability
Several theoretical arguments reinforce scepticism about forecasting. Most geopolitical risk indices draw on textual analysis of news coverage, meaning they capture events only as they enter public consciousness. By the time a risk registers in these indices, markets have typically already responded. The efficient market hypothesis, applied to political risk, implies that forecastable components should already be priced in.
Moreover, geopolitical events are driven by human agency and strategic interaction rather than mechanical processes. They are subject to genuine Knightian uncertainty rather than quantifiable risk. Frank Knight’s 1921 distinction remains salient: risk involves situations where probabilities can be estimated; uncertainty involves situations where they cannot. Game-theoretic dynamics introduce reflexivity: when actors know their behaviour is being modelled, they adjust accordingly, potentially invalidating the models themselves.
Where forecasting gains traction
Yet dismissing all forecasting potential oversimplifies the matter. The key insight is that different components of geopolitical risk exhibit different forecasting properties.
The persistent, autoregressive component of these indices—the tendency for elevated risk to remain elevated—provides a modest but reliable forecasting baseline. This captures the slow-moving structural factors that shape the geopolitical environment: democratic backsliding, inequality, fiscal stress, demographic pressure, institutional decay. These conditions evolve observably over years and decades, creating environments where fat-tailed events become more probable even if specific triggers remain unpredictable.
Certain macroeconomic and financial variables also lead geopolitical risk indices with meaningful regularity. Commodity price shocks, particularly in energy markets, frequently precede spikes in geopolitical tension. Currency crises in emerging markets often signal forthcoming political instability. Credit spreads in sovereign debt markets sometimes anticipate political ruptures before they occur. These leading indicators cannot predict black swans, but they can identify when the pond conditions favour their emergence.
Geopolitical risk as implied volatility
A more productive framing may treat geopolitical risk indices not as point forecasts but as implied volatility surfaces. Just as option prices reveal market expectations about future price distributions without predicting specific outcomes, geopolitical risk measures tell us something about the price of strategic optionality.
This connects to how sophisticated actors actually use geopolitical analysis. Alliances, for instance, function as real options—commitments that provide flexibility to respond to contingencies without specifying in advance which contingencies will materialise. NATO membership does not predict which threats will emerge; it provides optionality against a range of scenarios. Similarly, India’s simultaneous engagement with both BRICS and the Quad reflects option-like positioning that hedges against multiple geopolitical futures rather than betting on a single forecast.
The value of such strategic optionality increases precisely when point forecasting becomes harder. In fat-tailed environments, the premium on flexibility rises.
Infrastructure and forecastable risk
Not all geopolitical risk shares the same forecasting properties. Large-scale infrastructure corridors like the India-Middle East-Europe Economic Corridor create their own risk dynamics that may be more amenable to anticipation. These projects have long gestation periods, observable milestones, identifiable stakeholders, and predictable opposition patterns.
When a major connectivity project is announced, we can reasonably forecast that competing powers will respond, that transit countries will seek to extract rents, that financing negotiations will create friction, and that domestic political opposition will emerge in various jurisdictions. The specific manifestations remain uncertain, but the category of risks is foreseeable. The Gaza conflict’s impact on IMEC’s timeline illustrates this pattern—not the specific trigger, but the vulnerability of complex multi-stakeholder projects to regional instability was entirely predictable. Infrastructure-driven geopolitical risk operates on slower timescales and through more institutionalised channels than event-driven risk, making it more tractable for strategic planning.
Regional heterogeneity
Forecasting accuracy varies substantially across geopolitical contexts. Gulf Cooperation Council political risk operates through different mechanisms than South Asian or Eastern European variants. The GCC exhibits high regime stability but sensitivity to energy market dynamics and regional security architectures. South Asia features more volatile domestic politics but relatively predictable interstate relations constrained by nuclear deterrence. Eastern Europe currently displays acute event-driven risk overlaid on structural tensions with longer historical roots.
Generic global indices obscure these differences. A forecast methodology calibrated on one region may fail entirely in another. This creates opportunities for specialists but poses challenges for global portfolio managers seeking unified frameworks.
The academic-practitioner gap
Tension persists between academic indices, which prioritise methodological rigour and replicability, and consultancy products, which prioritise actionability and client-specific relevance. Academic measures typically lag events, reflecting their reliance on published text sources. Consultancy products claim greater timeliness but often lack transparency about methodology and track record.
Surprisingly little systematic evidence exists on which approach actually forecasts better out of sample. The competitive dynamics of the consultancy market discourage rigorous backtesting that might reveal poor performance. Academic researchers face publication incentives that favour novel methodological contributions over unglamorous forecast evaluation. The result is a market where buyers have limited ability to assess product quality.
The reflexivity problem
As geopolitical risk indices become more widely used for portfolio allocation and corporate strategy, they increasingly influence the phenomena they purport to measure. Capital flows responding to risk index movements can themselves destabilise vulnerable economies. Corporate decisions to exit markets based on risk assessments can become self-fulfilling. Political actors aware of how their behaviour affects indices may engage in strategic signalling or manipulation.
This reflexivity, familiar from financial markets, complicates both forecasting and interpretation. An index that moves markets is no longer simply measuring an external reality; it has become part of the system it describes.
Implications for portfolio construction
If perfect forecasting is impossible and fat tails dominate realised outcomes, what practical guidance emerges?
First, hedge ratios matter more than point forecasts. Rather than attempting to predict geopolitical risk levels, investors should focus on portfolio exposures to geopolitical factors and the cost of hedging those exposures. The question shifts from “what will happen?” to “what is the optimal insurance policy against what might happen?”
Second, scenario planning deserves greater emphasis than probabilistic forecasting. Identifying plausible extreme scenarios and stress-testing portfolio resilience against them may deliver more value than refining median forecasts. The goal is not to predict black swans but to survive them.
Third, strategic flexibility commands a premium. Investments and corporate structures that preserve optionality—the ability to scale up, scale down, pivot, or exit—are worth more in fat-tailed environments than discounted cash flow analysis typically recognises. Liquidity, contractual flexibility, and diversified geographic footprints function as embedded options against geopolitical uncertainty.
Fourth, forecasting modest, persistent components of risk while remaining humble about tail events represents the pragmatic synthesis. Structural vulnerability indicators can inform medium-term strategic positioning even when specific trigger events remain unpredictable.
Conclusion
Geopolitical risk indices tell us something about where we are and offer hints about where we might be heading under normal conditions. But their greatest value lies in reminding us that we operate in a fat-tailed world where the most consequential events are precisely those that defy prediction.
The appropriate response is not forecasting hubris but structured humility: building portfolios and strategies robust to discontinuities we cannot foresee, maintaining optionality against futures we cannot predict, and recognising that in domains of genuine uncertainty, resilience matters more than prescience.