Approach
We publish what we believe. We do not publish how to rebuild it.
The framework below is what a client is entitled to understand before they rely on us. The construction is proprietary, and stays that way.
Risk has more than one face
A single measure of market risk is always wrong somewhere. Credit spreads miss a political rupture. Sentiment surveys miss a funding squeeze. Volatility is the last to know.
GXPOL reads macro risk through a set of independent lenses — financial conditions, real-economy behaviour, political and policy pressure, positioning, funding and liquidity, the physical economy, corporate solvency, cross-border coercion, and the structural cost of transition. Each is built separately, from its own data, and scores the same question from its own angle.
They are kept genuinely independent. No input feeds two lenses — a constraint enforced automatically, because a composite that double-counts a driver is a composite that lies with confidence.
Not everything moves together
This is the part most composite indices get wrong, and it is the centre of our approach.
Some lenses measure stress that is happening now. Others measure conditions that precede stress — and those frequently move the opposite way during a crisis. Central banks ease. Curves steepen. Commodity demand collapses. Averaging everything into one number blurs precisely the signal you need.
So we do not. We maintain a read of the regime you are in, and a separate read of stress occurring right now. Their agreement is confirmation. Their disagreement is the warning.
Discipline
Evidence, including when it is inconvenient.
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We test the thing that could embarrass us
We tried to optimise the weighting of our lenses. Rigorous out-of-sample testing showed every tilt made the result worse — the sophistication was noise. So we did not ship it. Most vendors would have fitted the weights, reported the in-sample figure, and said nothing. The evidence is in the client methodology paper.
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Hindsight is designed out
A historical reading uses only what was knowable on that date. This is harder than it sounds and easy to get quietly wrong — a model that rewrites its own past through today's lens will backtest beautifully and fail you live.
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When the data breaks, we say so
Inputs die. Sources change underneath you. When a reading is degraded, it is marked degraded. It is not silently patched with a neutral value and served as if nothing happened.
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Every call is on the record
Timestamped with the conditions that produced it, and never restated. A track record that accrues in public, rather than a backtest you are asked to believe.
What we will show you
Clients and serious prospects receive the full methodology paper: the lens architecture, the independence constraints, the regime thresholds and how they were calibrated, the out-of-sample testing, and — plainly stated — where our coverage is weaker and why.
It is enough to satisfy a quantitative due diligence. It is not a blueprint, and it is not published here.