Tail risk, regime transitions, and market-structure shifts — measured rigorously, validated forward, and claimed only when proven.
| Measurement | Reading | |
|---|---|---|
| 01 | Structural Tail Risk Estimation Quantifies the real-time probability of a market regime transition into crisis. The signal is pre-registered in our research log and evaluated forward-prospectively — not tuned on replayed historical crashes. | Live · real-time regime-transition probability |
| 02 | Signal-to-Noise Decomposition Separates genuine price momentum from microstructure noise and liquidity artifacts. Delivers a real-time signal quality score that tells you whether a move is driven by informed flow or temporary friction. | 0–1 · continuous quality score per asset, per cycle |
| 03 | Adaptive Rebalancing Triggers Monitors the structural stability of asset relationships in real time. Instead of trading on a fixed schedule, our architecture identifies exactly when portfolio factor exposures have shifted enough to warrant action — acting on measured structural change rather than the calendar. | LIVE · event-driven trigger cadence |
| 04 | Market Regime Classification Classifies the current market environment into one of four distinct regimes on a continuous coordinate system. Each regime maps to a measurably optimal allocation strategy, replacing subjective regime labels with quantitative precision. | 4 · quadrant classifier · updated every cycle |
| 05 | Structural Breakdown Detection Combines topological analysis of market microstructure with regime transition modeling. Detects when the geometry of return distributions is shifting before it becomes visible in price or volatility. | 2 · independent signal layers cross-confirmed |
| 06 | Multi-Scale Regime Velocity Analyzes how market dynamics shift across timescales — from intraday through weekly. Cross-scale divergence surfaces when short- and long-horizon dynamics decouple and feeds the regime read as one input among several — treated as a hypothesis under forward validation, not a settled early-warning signal. | intraday–weekly · cross-scale regime input |
Lineage, stated plainly: the eigenspace-rotation measurement builds on established results on the dynamics of correlation-matrix eigenvectors (Allez & Bouchaud, 2012) and on principal-angle geometry between subspaces. Our contributions are the topological stability measure published in the SSRN series and the use of the rotation rate as a live rebalancing trigger.
Primary crash signal spanning SPY, QQQ, IWM, DIA, and EEM, with a frozen threshold and lead-time window pre-registered in our research log. It continues live tracking for prospective Harvey-significance validation — a forward, out-of-sample evaluation rather than a retrospective replay of historical stress events.
A multi-asset research book runs live and continuously — equities, digital assets, and derivatives — as the prospective, out-of-sample test bed for the signal registry. Allocation and risk management operate automatically so that every frozen-threshold hypothesis accrues genuine forward observations, not in-sample fits.
Every signal has a pre-registered hypothesis with defined null conditions, required sample sizes, and multiple-testing correction. Over 65,000 prospective observations recorded across the registry. Validation architecture enforces statistical discipline automatically — signals are not promoted to live sizing until they clear the Harvey 2016 t>3 threshold on a frozen sample.
Our research model submits weekly to the Numerai Signals blind tournament for independent third-party validation. Resolved rounds counted here; full per-round scores published on the performance page. We do not claim a score until the tournament’s own robust-evaluation quorum is reached — Numerai’s Alpha metric requires a multi-month track record before it stabilises.
| Document | Status |
|---|---|
| Time-Series Momentum in Cryptocurrency: Anatomy, Capacity, and the Fee Constraint | PUBLISHED · SSRN · 2026 |
| Stochastic Mechanical Methods for Quantitative Portfolio Management | PUBLISHED · SSRN 6566258 |
| Nelson Decomposition of Options Greeks | PUBLISHED · SSRN 6566301 |
| Topological Factor Stability via Persistent Homology on the Grassmannian | PUBLISHED · SSRN 6566279 |
| Multi-Scale Crash Detection via RG Flow of Instanton Action | PUBLISHED · SSRN 6614703 |
| Ontological Limits of Historical Validation for Wavefunction-Calibrated Financial Systems | PUBLISHED · SSRN 6614899 |
Twelve articles — five results, three methods, four essays. Full index
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