IsoVector is a System-State Diagnostic Model
IsoVector (ī-sō-vek-tor) measures the internal condition of the macro-financial system across multiple interacting dimensions.
- Multi-dimensional state representation (not a single indicator)
- Measures buildup, strain, & structural alignment
- Tracks condition evolution over time
- Compares current state to historical stress configurations
Vector (Model) — System Representation
IsoVector encodes macro-financial system state as a bounded, normalized vector across interacting dimensions.
The system is not represented by a single signal. It is defined by the simultaneous interaction of multiple measured conditions within a unified state space.
- The system is not described by one signal.
- It is defined by the interaction of all components simultaneously.
- Vector form preserves structural relationships that scalar summaries alone would obscure.
Iso (Philosophy) — Interpretive Discipline
- Condition, not prediction
- Structure, not narrative
- Diagnosis, not reaction
- Does not answer what will happen
- Does not answer when an event will occur
- Does not assign outcome probabilities
- Whether pressure is building
- Whether fragility is elevated
- Whether system structure resembles prior stress regimes
- Market will crash
- Event X will happen
- Probability = Y%
Measure the dryness of the forest floor.
What IsoVector Is NOT
- NOT a forecasting model
- NOT a price prediction system
- NOT sentiment-driven
- NOT a single-indicator signal
- NOT a substitute for governed measurement in the_Spine
- NOT a write-back layer into OracleChambers
IsoVector reads from governed measurement outputs & renders state. It does not originate raw measurement logic & it does not authorize prediction.
Core Model
Measures the aggregate buildup of macro-financial stress across the system.
Ex: Rising rates, wider credit spreads, & tighter liquidity conditions signal elevated pressure.
Measures how sensitive the system is to shocks once stress is already present.
Ex: High leverage, weak balance sheets, & unstable funding structures indicate elevated fragility.
Measures the ease or difficulty of funding, flow, & market functioning across the system.
Ex: Wider funding spreads, lower market depth, & tighter financial conditions indicate weaker liquidity.
Measures the degree of divergence in behavior across assets, sectors, or macro signals.
Ex: Defensive assets rising while cyclicals fall & macro series move out of sync signals higher dispersion.
Measures the persistence of directional movement in system conditions over time.
Ex: A sustained deterioration in risk conditions across multiple periods indicates negative momentum.
Measures how stress is transmitting across equities, rates, commodities, credit, & FX.
Ex: Simultaneous pressure in bonds, equities, credit, & commodities signals elevated cross-asset stress.
Measures how closely the current system state aligns with known macro regime structures.
Ex: When inflation, growth, liquidity, & market behavior move in a historically consistent pattern, coherence is higher.
Measures the degree to which localized stress has the potential to propagate into system-wide instability.
Ex: Stress concentrated in one market becomes more systemic when it spreads through funding, credit, & cross-asset channels.
Intended Interpretation
- Interpret as condition, not direction
- Read as structural state, not event timing
- Use as a representation layer between measurement & interpretation
- Assess similarity to historical stress configurations without implying certainty
Interpret second.
Never mix the two.
CPMAI Alignment
FT-GMI & its system family are aligned with PMI CPMAI standards for responsible Artificial Intelligence (AI) & Machine Learning (ML) governance.
To address layman concerns regarding black-box AI & ML operations (AI/MLOps), our system position is stated clearly below.