Geopolitical Conflict Through the Lens of Nash Equilibrium

Before beginning this blog, I should acknowledge that I do not have the ability to speak with complete confidence about the current confrontation between the U.S. and Iran. Those who are not direct participants in the conflict cannot fully understand the deeper motives, internal calculations, and hidden tensions between the parties. As an outside observer, therefore, I am not in a position to make definitive judgments. Much of the true structure of the conflict is neither visible nor easily knowable, and even a logically coherent model may fail when the underlying incentives, information, or constraints change unexpectedly.

Most media reports portray the current confrontation between the U.S. and Iran as a struggle between good and evil, or as the product of the greed of a few actors. While this framing attracts attention, it is analytically weak. Consequently, individual investors influenced by such narratives may misinterpret the prospects for war and make costly financial decisions. A recurring reality is that individual investors who simply follow sensational news headlines often underperform. Markets do not price moral stories; rather, they price incentives, constraints, probabilities, and strategic responses. (Morality itself is difficult to define and often subject to debate. As Adam Smith argued, social outcomes should be judged not only by markets but also by their effects on human well-being.)

A more useful framework is Nash Equilibrium. In strategic conflict, each side chooses actions while anticipating the reactions of the other side. Outcomes are not determined by virtue or emotion alone, but by whether any player can improve its position by unilaterally changing strategy. Formally, if the United States chooses strategy $s_U$ and Iran chooses strategy $s_I$, with payoff functions $U_U(s_U,s_I)$ and $U_I(s_U,s_I)$, an equilibrium $(s_U^*,s_I^*)$ satisfies $U_U(s_U^*,s_I^*) \geq U_U(s_U,s_I^*)$ for all $s_U$, and $U_I(s_U^*,s_I^*) \geq U_I(s_U^*,s_I)$ for all $s_I$.

At such an equilibrium, neither side can improve its position simply by changing strategy while the other side's choice remains fixed. This framework is useful because the United States and Iran do not make decisions in isolation. Each move—military signaling, sanctions, retaliation, diplomacy, proxy activation, or restraint—is chosen partly in anticipation of the opponent's response.

However, this framework has an important limitation. In real geopolitical conflicts, the payoff matrix itself is not fixed. Military events, economic pressures, domestic politics, leadership changes, misperceptions, and unexpected actions by third parties can alter both the available strategies and their associated payoffs. Thus, rather than searching for a single stable Nash equilibrium, it may be more realistic to think of the conflict as a sequence of shifting strategic equilibria.

From the perspective I held in April 2026, both sides appeared to have a reasonably clear understanding of the broad range of possible negotiated outcomes, while attempting to extract incremental gains through limited tactical adjustments. A key asymmetry in preferences also appeared important: one side might place greater emphasis on avoiding future risks, while the other might assign greater weight to immediate political and economic conditions.

A more realistic model must therefore include noisy and nonlinear factors, especially on the Iranian side, because power is distributed across multiple institutions and factions: elected offices, clerical authority, security organs, economic networks, ideological hardliners, pragmatists, and regional proxy relationships. We may write Iran's effective payoff as $\tilde{U}_I(s_U,s_I)=U_I(s_U,s_I)+\epsilon \Phi(s_U,s_I,\theta)$, where $\epsilon$ measures the scale of political noise, $\theta$ represents hidden internal factional variables, and $\Phi$ captures nonlinear interactions among competing institutions, ideological blocs, security networks, and proxy relationships. 

The difficulty is that neither $\theta$ nor even the underlying payoff function is directly observable. Moreover, these variables may themselves change during the conflict. Consequently, a model that explains the strategic environment reasonably well at one point in time may lose predictive power when new events alter incentives or reveal previously hidden information.

The situation is therefore better understood as a repeated strategic game under uncertainty, domestic fragmentation, bounded rationality, and incomplete information. This framework is less dramatic than typical media narratives, but more useful for thinking about market behavior. It should not, however, be mistaken for a deterministic forecasting model.

As of April 2026, the negotiation space appeared to have narrowed across several dimensions—sufficiently to sustain continued engagement—yet meaningful gaps remained. Crucially, the constraint was not merely the magnitude of these differences but the limited ability of both sides to credibly commit to and publicly justify an agreement given unresolved political, strategic, and domestic pressures. Within Iran, policy divergence between hardliners and moderates continued to complicate negotiations. In parallel, highly sensitive issues—such as Iran's regional proxy networks—could be postponed in an initial agreement to enable incremental progress. Such sequencing, however, would create its own complications, particularly by increasing security concerns among Gulf states. In aggregate, intensifying economic pressure could increase the incentive to negotiate without necessarily producing a comprehensive agreement.

The broader strategic structure also contains elements of the Prisoner's Dilemma. Although both sides may benefit from cooperation, uncertainty and mistrust create incentives to defect. Yet the U.S.-Iran relationship is not a one-shot game but a repeated one. Because both sides expect future interactions, the long-term costs of defection and benefits of cooperation matter. Domestic political constraints further create a divergence between public signaling and private bargaining: negotiators may adopt confrontational rhetoric—which naturally dominates media headlines—while simultaneously exploring mutually acceptable compromises behind the scenes.

The important lesson, particularly for investors, is therefore not that game theory allows us to predict geopolitical outcomes with precision. Rather, it provides a disciplined way to identify incentives, constraints, strategic interactions, and possible changes in equilibrium. The world remains nonlinear, information is incomplete, and unexpected events can rapidly change the payoff structure. The appropriate response is not to abandon analysis, but to remain humble about its predictive power and to update probabilities as new information arrives.

P.S. I wrote the original version of this article in mid-April 2026 because many of my Korean friends were worried that escalating tensions between the United States and Iran would develop into a major geopolitical crisis. As both sides appeared to be adopting increasingly hardline positions, some were inclined to sell their stocks amid the wave of negative news coverage. My intention was to show that investors should look beyond alarming headlines and avoid making investment decisions based solely on media-driven narratives.

I would add one qualification: rational analysis itself can create excessive confidence if we assume that the underlying game remains unchanged. In geopolitics, the players, information, strategies, and even the payoff matrix can change unexpectedly. For investors, therefore, the objective should not be to predict every geopolitical development correctly, but to distinguish developments that materially change economic fundamentals from those that merely add noise to an already uncertain world.