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Educational macro risk analytics
Multi-Variate Implied Engine
MVIE · LIVE|AR ██ IS ██ PD ██|STATE: GREEN|
Explore probabilistic macro-risk scenarios across market regimes.
MVIE Pro combines multi-window instability analysis, network topology, and probabilistic scenario modeling for educational risk observation. Try it now in your browser—no account or registration required.
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Three-step workflow
How It Works
From ticker input to regime-aware risk observation—MVIE Pro surfaces systemic structure in three auditable stages.
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Uncover Hidden Risks
Network topology reveals systemic dependencies you can't see in raw returns.
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Detect Regime Shifts
MVIE score catches structural breaks before full drawdown materialises.
Institutional purpose
Core pillars of macro risk intelligence
MVIE Pro exists to make systemic market risk observable before correlation breaks—not through black-box signals, but through auditable mathematics and explainable scenario narratives.
Macro regime detection
Hidden Markov and PCA-based macro regime detection. We monitor markets through mathematical stability windows—not opaque black-box models.
REGIME_ENGINE :: PCA + HMM WINDOWS: 30d | 60d | 90d STATE: GREEN | AMBER | RED OUTPUT: MVIE composite + veto threshold AUDIT: eigenvalue dispersion · AR · IS · PD
Why traditional risk tools fail in crisis regimes
Single-window correlation
Breaks down in regime shifts. A 30-day correlation matrix can't see the structural change happening at 60-day scale.
Backward-looking VaR
Historical volatility models assume tomorrow looks like yesterday. They didn't see 2008, 2020, or 2022 coming.
No systemic risk detection
Asset-level signals miss network contagion. When SPY's eigenvector centrality spikes, every "uncorrelated" position becomes correlated.
Deterministic labels without context
A single “bullish” label without regime, probability, or a volatility envelope adds little for risk education. Probabilistic scenario sets and distributions support observational analysis.
Traditional approach vs. MVIE Pro
| Traditional Risk Tools | MVIE Pro |
|---|---|
| Single correlation window | Multi-window analysis (30/60/90-day rolling) |
| Static risk metrics | Dynamic MVIE score (0-100) with regime classification |
| Ignores asset network effects | Minimum Spanning Tree topology + centrality metrics |
| Deterministic buy/sell labels | Probabilistic scenarios with volatility envelopes (illustrative) |
| No macro override mechanism | Veto Protocol — macro risk overrides micro signals |
| Black-box ML models | Transparent mathematics — every Z-score is auditable |
Inside the Brain: how MVIE works
We don't hide the math. Every layer is documented and reproducible.
1. Multi-Window Instability Engine
The MVIE composite score blends three rolling Z-scored metrics—Absorption Ratio (PCA variance concentration), Instability Score (correlation-structure change rate), and Priority Drift (MST centrality rank drift)—across 30/60/90-day windows:
Composite formula · pseudocode
# Pseudocode — MVIE composite pipeline# AR, IS, and PD are each rolling Z-score outputs (30/60/90-day windows)AR = z_score(pca_variance_share(asset_returns, top_components=3))IS = z_score(correlation_structure_change_rate(correlation_matrix, baseline))PD = z_score(network_centrality_drift(min_spanning_tree, window=rolling_window))MVIE = (0.40 * AR) + (0.35 * IS) + (0.25 * PD)Regime thresholds:
- 0–50 GREEN — Stable absorption / correlation structure; centrality ranks steady
- 50–75 AMBER — PCA concentration or correlation drift rising; MST hub order shifting
- 75–100 RED — Systemic stress band; correlation breakdown and centrality drift elevated
2. Network Topology Analysis
Spearman correlation builds a Minimum Spanning Tree (d_ij = sqrt(2(1 − ρ_ij))). Eigenvector, betweenness, and degree centrality on the MST quantify systemic hubs—and feed Priority Drift when rank order changes across rolling windows:
- Eigenvector centrality — Hub assets whose stress propagates through the MST (e.g., SPY)
- Betweenness centrality — Bridge nodes linking otherwise disconnected clusters (contagion paths)
- Degree centrality — Direct connectivity count; used with rank drift for Priority Drift (PD)
3. Probabilistic Strategy Engine
Composite regime readings (AR · IS · PD) feed a probabilistic scenario layer—illustrative BULLISH / BEARISH / NEUTRAL labels with volatility envelopes, aligned to the same macro-risk stack as the dashboard:
Scenario weights · illustrative output
Composite weights (engine — matches MVIE pipeline): Absorption Ratio (AR): 40% Instability Score (IS): 35% Priority Drift (PD): 25%Output: Direction: BULLISH | BEARISH | NEUTRAL Probability: P(direction) ∈ [0, 1] Envelope: ±2σ volatility band (illustrative) Horizon: 5 trading days, best / base / worst projections4. Veto Protocol
The Veto Protocol is a model override rule. When MVIE > 75 (RED regime), all BULLISH scenario labels are reclassified to NEUTRAL or defensive overlays in the published set, regardless of micro-indicator strength. In crisis regimes, the engine treats micro readings as high-noise; the defensive scenario narrative takes precedence in the illustrative output.
5. LLM Analyst Layer
A large language model layer synthesizes the quantitative output into a structured institutional report. The prompt is compliance-locked — no investment advice, only analytical scenarios. Output is markdown-formatted with explicit risk framework sections. The underlying model can be swapped as newer APIs become available.
Transparent Quant · No Black Boxes
Every signal is an auditable differential equation. Not a black box.
MVIE Pro reads markets with transparent mathematics — eigenvalue decomposition, Frobenius norms, and Minimum Spanning Tree centrality. The LLM layer synthesises the quantitative output into institutional language. You can inspect every Z-score, every weight, every threshold.
MVIEComposite MVIE Score
MVIE = 0.40 × AR + 0.35 × IS + 0.25 × PD
Weighted composite of three structural regime indicators, scaled 0–100.
ARAbsorption Ratio
AR = Σλ(top 20%) / Σλ(all)
Share of total variance absorbed by the dominant eigenvectors of the covariance matrix. High AR → correlated, fragile regime.
ISInstability Score
IS = ‖C_t − C_baseline‖_F
Frobenius norm of the change in Spearman correlation matrix vs. baseline. Captures structural rewiring speed.
PDPriority Drift
PD = Σ |rank_t(i) − rank_0(i)| / N
Mean absolute rank displacement of eigenvector centrality in the Minimum Spanning Tree. Measures leadership rotation in the asset network.
λEigenvalue Decomposition→ZZ-Score Normalization→ΣWeighted Composite
Quantitative output → LLM synthesis → institutional report
LIVE OUTPUT
1# MVIE Analyst Report
2regime: AMBER → RED TRANSITION
3mvie_score: 74.2
4ar_zscore: +2.1σ ← Systemic risk rising
5is_zscore: +1.8σ ← Correlation rewiring
6pd_zscore: +1.4σ ← Centrality rotating
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8§ MACRO CONTEXT:
9 Eigenvalue dispersion rising across 60d/90d
10 windows. Correlation structure shows early-
11 stage regime transition. SPY eigenvector
12 centrality at 0.68 (+0.11 vs prior week).
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14veto_protocol: APPROACHING THRESHOLD
15disclaimer: observational only — not advice
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⚠ All outputs are educational scenario descriptions, not investment advice. The LLM layer is compliance-locked — no price targets, no recommendations.
MVIE engine simulator
Interactive MVIE Simulator
Interactive simulator with illustrative formulas. The live engine uses real market data, PCA eigenvalues, and Spearman correlation networks — try the engine for a real run.
Stress level: 42
CALMTRANSITIONCRISIS
Composite components
AR (Autocorrelation Ratio)
42.0IS (Instability Score)
39.9PD (Probability Drift)
35.7MVIE composite output
39.7
MVIE = 0.40×AR + 0.35×IS + 0.25×PD
State: GREEN
Veto protocol: INACTIVE
Illustrative scenario assets
BULLISH
Scenario active without override
AAPL
Large-cap equity proxy in the sample scenario set.
BULLISH
Scenario active without override
BTC-USD
High-volatility asset where stress transmits faster.
BULLISH
Scenario active without override
GLD
Defensive commodity proxy in cross-asset stress windows.
LLM insight (scenario language)
Macro regime calm. Diversification intact; signals operate without override.
Interactive sample: 3-asset portfolio
Select three tickers to view illustrative network topology, MVIE score, and regime classification from pre-computed historical data. This page is a quick sample—open the full engine anytime with no signup.
Who may use MVIE Pro for research
Hedge Funds
Macro-risk scenario overlays for multi-asset research. Regime-transition watchpoints tied to MVIE score bands (observational, not trade instructions).
Asset Managers
Systemic-risk observation for portfolio research. Educational risk-committee briefing material.
Family Offices
Tail-risk scenario illustration for learning and discussion. Network-based correlation-structure observations.
Quantitative Researchers
Reproducible network topology framework for academic and applied research. Full methodology disclosed.
Historical sample observations (not forecasts)
In a historical sample, MVIE score reached 87.3 on Feb 10, 2020—before the widely observed COVID stress window (illustrative backtest, not a guarantee of future timing)
MVIE ENGINE · 2020-02-10RED REGIME
87.3MVIE COMPOSITE
AR: 91.2IS: 84.7PD: 83.1
⚠ VETO PROTOCOL ENGAGED — all BULLISH signals → NEUTRAL
Network topology output showing SPY as dominant hub (eigenvector 0.68)
MINIMUM SPANNING TREE · CENTRALITY OUTPUT
SPY
0.68
QQQ
0.52
DXY
0.41
GLD
0.29
VIX
0.38
Nodes: 18Edges: 17 (MST)Hub: SPY
DENSITY: 0.42TOPOLOGY: MSTCLUSTERING: HIGH
LLM analyst report sample (structured institutional output)
── MVIE ANALYST REPORT ─────────────────
REGIME: AMBER → RED TRANSITION
Generated: 2024-08-14 · Model: llama-3.3-70b
§1 MACRO CONTEXT
Eigenvalue dispersion rising across 60d/90d windows. Correlation structure shows early-stage regime transition signal...
§2 RISK ASSESSMENT
Network hub SPY eigenvector centrality at 0.61 (+0.09 vs prior week). Betweenness concentration elevated in equity cluster...
§3 SCENARIO SET
BEARISH: 58% · NEUTRAL: 31% · BULLISH: 11% (pre-veto weights)
⚠ Educational output only — not investment advice
Veto Protocol activation log — 2022 bear market
VETO PROTOCOL LOG · 2022-Q1/Q2
2022-01-2476.2VETO ENGAGED
2022-02-2481.5VETO ACTIVE · WAR SHOCK
2022-03-0779.4CORRELATION BREAKDOWN
2022-05-0988.9PEAK STRESS · ALL NEUTRAL
2022-06-1683.1FED +75bps · SUSTAINED
2022-08-2674.8RISK-OFF PERSISTENT
2022-10-1371.4VETO DISENGAGED
[SYSTEM AUDIT SECURE — LOG END]
Important disclosure
MVIE Pro is an educational and informational risk-analytics tool. It is not a registered investment advisor and does not provide investment advice. All outputs are probabilistic, illustrative scenarios for learning and research only. Any investment or trading decisions are solely your responsibility. Past performance does not guarantee future results.