The “X” in EntropyXisn't marketing.
We started as a research group obsessed with one question: how much information is actually in a market? That question chose what we build, what we optimise, and where the next decade of edge lives.
Quantum-inspired optimisation
Variational and annealing-style solvers tuned for portfolio rebalancing, routing and combinatorial pricing — running today on classical hardware, ready for quantum back-ends.
Information theory in finance
Entropy as a market signal. Our published work shows local entropy plus directional movement isolates patterns conventional moment statistics miss.
Hybrid classical/quantum stack
Production services where quantum subroutines slot in as drop-in replacements when meaningful. No rewrites, no lock-in.
From paper to production
Every research artefact ships with a productionisation plan. We measure ourselves on what reaches a customer.
Cross-asset signal graphs
Information-theoretic dependency graphs across FX, equities, commodities and crypto — capturing lead/lag relationships that linear correlation matrices erase.
Robustness & uncertainty
Every model ships with calibrated confidence intervals, drift monitors and adversarial stress tests. Forecasts come with conviction, not just point estimates.
Entropy-Assisted Quality Pattern Identification in Finance
An entropy-assisted framework for identifying high-quality, non-overlapping patterns that exhibit consistent behaviour over time. The approach uses an entropy-based measure as a proxy for information gain: patterns that produce high one-sided movements in historical data yet retain low local entropy are treated as more informative signals of future market direction.
Signatures of Extreme Events in Cumulative Entropic Spectrum
The cumulative effect of the empirical probability distribution of a random variable is identified as a factor that amplifies the occurrence of extreme events in datasets. The cumulative entropic spectrum gives a principled way to surface tail-risk signatures that conventional moment-based statistics miss — directly relevant to volatility regime detection and risk modelling.