Toward a Market Index for Quantum Correlation

Markets utilize indices to track features of market behavior. For example, the VIX represents the expected value of market volatility, while the more familiar S&P 500 tracks the real-time value of 500 large U.S. companies listed on exchanges such as the NYSE and the Nasdaq (e.g., Apple, JPMorgan, Walmart). An index is a formally defined aggregation rule that maps many data points into a single scalar reference value, designed to track a specific property of a system over time.

Indices that attempt to track the statistics of markets—such as the VIX—aim to quantify a latent property of the market system rather than a directly observable one like the performance of 500 companies. Properties such as volatility are inferred from behavior (e.g., option prices); the same is true for market stress, which is estimated by indices such as the St. Louis Fed Financial Stress Index and the Chicago Fed National Financial Conditions Index.

However, there is another major influence on latent market properties beyond the behavior of human market participants: technology layers. The statistics of latent market properties are strongly influenced by the technologies that mediate and facilitate trading, such as routing algorithms, execution algorithms, market-making bots, and the more recent rise of AI-based trading systems. Today, volatility, liquidity, and even correlations are not just functions of human psychology, but also artifacts of machine-speed interactions and algorithmic feedback.

As quantum information technologies—such as quantum computing and quantum communication protocols (for example, quantum key distribution)—become more commonplace, it is inevitable that they will influence latent features of markets. One such feature is correlation. Quantum information processing can produce “quantum correlations” that classical machines cannot, and which human behavior alone does not fully generate in any known way. We can therefore expect the effects of these quantum correlations to begin appearing in market data as more participants adopt quantum-secure communication protocols, for example by using quantum-generated one-time keys for encryption. These quantum correlations arise through several mechanisms, the most well-known being entanglement, a property of two quantum objects in which classical notions of individuality break down.

In recent work (Quantum Advantage in Trading: A Game-Theoretic Approach), colleagues and I have shown that when markets are modeled in specific competitive game-theoretic contexts—such as the Prisoner’s Dilemma or Chicken—the introduction of quantum entanglement can do two things:

1. provide a decisive payoff advantage to a player who uses quantum information features (of the same type used in quantum key distribution) to convey market moves, and

2. produce a superior market equilibrium among traders who all use quantum features.

Beyond strategic advantage and equilibrium effects, such quantum-induced market interactions would also imply the existence of statistically detectable signatures that, in principle, could be summarized by a quantum correlation index and used to assess when the adoption of quantum-secure communication protocols—such as quantum key distribution—is actually worthwhile.

This raises a natural question: if quantum correlations such as entanglement can offer a market edge, would they appear as observable properties of the market, or as latent ones?

If such effects are indeed latent, then the need for a quantum correlation index becomes clear. We would in fact expect quantum-induced market correlations to remain largely latent for the foreseeable future, not only because early-stage quantum technologies are inherently noisy, but more fundamentally because quantum information itself is intrinsically probabilistic rather than deterministic. As a result, there will always exist irreducible uncertainty in the realized level of correlation induced by entanglement in market interactions. This combination of technological noise and fundamental quantum uncertainty implies that any quantum correlations present in market data will necessarily be inferred statistically rather than observed directly.

Moreover, even if robust entanglement distribution becomes technologically feasible at scale, it is unlikely to be offered freely. Entanglement will almost certainly be a priced infrastructural resource, controlled by specialized providers and accessed selectively through paid services. This economic gating further implies that quantum correlations in markets will appear indirectly, partially, and heterogeneously across participants, reinforcing their fundamentally latent and statistically inferred nature.

If quantum communication and computation do become embedded in the infrastructure of markets—even indirectly through cybersecurity, coordination mechanisms, or strategic signaling—then their effects should not be understood merely as faster computation or stronger encryption. They would represent a structural change in the information geometry of markets. In the same way that electronic trading reshaped volatility, liquidity, and correlation at machine timescales, quantum information technologies would introduce a new, fundamentally nonclassical layer of interaction whose statistical fingerprints may not be well captured by existing financial metrics.

This suggests a growing gap between what markets may soon become and what current indices are designed to measure. Today’s major benchmark indices excel at tracking observable quantities (price levels, returns) and certain inferred latent properties (volatility, stress, expectations). But if quantum correlations begin to shape coordination, signaling, or strategic advantage—even in narrow segments of market activity—then we may be facing a new class of latent technological-market properties for which no measurement framework yet exists.

From this perspective, a quantum correlation index is not a speculative novelty, but a natural extension of how markets have historically adapted their measurement tools to new technological regimes. Just as volatility indices emerged from the options revolution, and liquidity and stress indices from modern market microstructure, a quantum correlation index would serve as an early attempt to make a fundamentally new informational influence on markets statistically visible. Whether such an index ultimately proves predictive, diagnostic, or merely descriptive, its development would mark an important step in aligning financial measurement with the next generation of market infrastructure.

This line of work is currently under active study in collaboration with colleagues at QLAB at the University of Maryland, with initial results expected over the coming year.