Who We Are
We illuminate the expanse of market opportunities by seeing through apparent chaos to the structural reality of markets.
We conceive markets as a dynamic macro system—an interconnected universe of systematic macro forces—where surface moves reflect deeper causal structures.
Grounded in scientific method and principles-based reasoning, we formalise empirical relationships that link macro forces to market outcomes, render structure visible through coherent scenarios and simulation-based path ensembles, and calibrate portfolios within defined bounds of risk and conviction.
Our discipline is systematic and self-correcting—refining as theory advances and evidence accumulates.
Through this continual refinement, we translate understanding into measured positioning, embed resilience across regimes, and sustain accountability through process.
PHILOSOPHY
We believe markets are microefficient but macroinefficient—while individual securities reflect available information, macro forces create inefficiencies across markets and asset classes.
These macro-inefficiencies form the foundation of our approach: we uncover opportunities embedded within the expansive macro fabric. We start by formalising forward-looking capital market assumptions from empirical macro–return relationships, conditioned on market-implied expectations across horizons, including option-implied distributions, and expressed as distributions of path outcomes that preserve path realism.
We conceptualise markets as a dynamic system—an interconnected universe revolving around centres of systematic macro forces. As our understanding deepens through empirical research and advanced modelling, we make latent structural mechanics explicit within the seeming chaos of market movements through coherent macro scenarios and simulation-based total-portfolio paths, capturing interaction, transmission, and state transitions across assets and horizons; comparison to market-implied expectations reveals macro inefficiencies—the market opportunities we illuminate—and conviction is expressed through calibrated allocations within defined risk limits, with disciplined implementation.
The structure of the system matters as much as its elements; the properties of the whole are not contained in the properties of the parts. We prioritise emergent system properties—interdependencies, feedback loops, and delays—essential to explaining macro-market behaviour and calibrating allocations.
PROCESS
We conceptualise and model the macro system and calibrate allocations within it.
We start from pricing-consistent initial conditions and formalise forward-looking capital market assumptions from empirical macro–return relationships, holding views as distributions of path outcomes—paths, not points—and updating through time via state-space evolution.
We operationalise system-dynamics principles to evolve coherent macro scenarios into simulation-based total-portfolio path ensembles that make interdependencies, feedback effects, time delays, and state transitions explicit—emergent order made visible—with scenario-conditioned covariance surfaces to inform regime-aware diversification.
We form a confidence-weighted blend by reconciling our assumptions with the market-implied consensus, including option-implied distributions, to size and characterise divergence. We then translate those departures through robust optimisation—with uncertainty sets, expected shortfall awareness, and scenario constraints—into calibrated allocations within defined risk limits.
We implement with macro coherence and responsiveness, monitor for state transitions, reconcile to pricing, and refine on a governed review cadence.
Formalise — pricing-consistent starts and forward-looking assumptions from empirical macro–return relationships; views held as distributions of path outcomes.
Evolve — coherent scenarios into simulation-based total-portfolio path ensembles via system-dynamics principles, making feedback and state transitions explicit with scenario-conditioned covariances.
Reconcile — market-implied expectations mapped into macro-factor space to characterise priced–research divergence and define the opportunity set.
Blend — confidence-weighted synthesis of research and market-implied consensus to inform portfolio construction.
Optimise — robust optimisation under model uncertainty and practical constraints, translating divergence into calibrated allocations within defined risk limits.
Implement — macro-coherent and state-responsive implementation, under continuous monitoring for state transitions.
VISION
We envision a way of investing that sees through apparent chaos to the underlying order—the structural reality of markets.
We make that order visible through scientific method, principles-based reasoning, and systemising coherence, making the system’s causal logic explicit.
By bridging theoretical finance with empirical research, we pursue a science of markets—evolving principles until they withstand reality and developing models that recalibrate dynamically as new information emerges.
This continual refinement resolves uncertainty into probabilistic clarity and transforms understanding into conviction.
We express that clarity with discipline—converting conviction through measured positioning and embedding portfolio resilience across shifting regimes and accountability in process.
DISTINCTION
We are distinguished by how we conceive the market itself—not as a sequence of prices, but as a dynamic macro system of interacting forces.
Every observable move is a surface expression of deeper causal structures; our work is to make those structures visible.
Through scientific method, we bring that conception into being: observing, inferring, and testing, we refine models until the relationships we infer withstand reality across state changes—and innovate as theory advances and evidence accumulates. Thus we uncover how the system works and how to act within it.
This makes our distinction both philosophical and practical: a science of markets that disciplines action inside the system it explains—transforming speculation into informed adaptation, understanding into expression, and principle into disciplined execution.
This means portfolios founded on systemic understanding, resilient through regime transitions, and aligned with the causal logic that governs outcomes.