Validation, Methodology & Research
Market signals earned through research, built on innovation & validated on statistical science.
RegimeSignal™ maps the S&P 500's full market cycle in advance. This is the research protocol behind it — walk-forward, expanding window, monthly refit, robustness testing, and continuous monitoring. What decides what becomes a signal.
01
Walk-Forward Testing
Every signal is evaluated under strict walk-forward protocol — no peeking, no in-sample tuning of out-of-sample windows.
02
Expanding-Window Validation
Models are validated across an expanding history so each call is judged against everything previously knowable.
03
Historical Regime Analysis
Behaviour benchmarked across full bull, weakening, correction and recovery cycles since the late-1990s.
04
Monthly Refit Methodology
A controlled, calendared refit cadence — frequent enough to adapt, slow enough to prevent overfitting to recent noise.
05
Signal Robustness Testing
Each signal is stress-tested against parameter perturbation, sub-period sampling and feature ablation before shipping.
06
Drawdown Analysis
Peak-to-trough behaviour studied around every historical trigger — what the call would have caught, missed, and signalled too early.
07
Recovery Cycle Analysis
Regime Recovery Signal (RRS) confirmation behaviour mapped across recoveries — characterizing both true confirmations and quiet false-starts.
08
Multi-Regime Performance Review
Precision, hit-rate and forward-window distributions reported per regime, not just as a single blended number.
09
Research Discipline Framework
Hypothesis → protocol → walk-forward → robustness → review. Every change passes the same gates, in the same order.
10
Adaptive Validation Procedures
When the data-generating process changes, validation windows and refit cadence adapt — explicitly, not silently.
11
Continuous Model Monitoring
Live signals are monitored for pre-trigger drift, conformal-uncertainty widening and out-of-distribution conditions.
12
Structural Research Architecture
A versioned research stack where every signal, refit and decision is logged and reproducible end-to-end.
Factor Architecture · Reference
25–35 factor predictive structure
How the model is built · BRS shown
Each RegimeSignal™ signal operates on its own purpose-built factor universe, ranging from 25 to 35 factors depending on the signal (BRS = 25, MBS Tier 1 / Tier 2 = 34, RRS = 35). The example shown here is the Bear Regime Signal (BRS) universe: 25 predictive factors organized as 8 Core Macro Drivers (70% weight) and 17 Market Drivers (30% weight).
L1-Lasso regularization selects signal-carrying factors and drives the rest to zero — producing a sparse, transparent architecture. Weights are refit monthly via expanding-window walk-forward validation.
Signal quality is corroborated by alternative algorithms on the same data (L2 Logistic, Random Forest, XGBoost) — all landing in AUC 0.88–0.91 on 304 out-of-sample months (Dec 2000 – Apr 2026). Proprietary factor constructions are not disclosed in full; methodology is reproducible from source data.
8 Core Macro Drivers · 70% Weight
- • Inflation (18% — highest weight)
- • Corporate Earnings (18%)
- • Federal Reserve Policy
- • Valuation (Forward P/E)
- • Consumer Sentiment
- • Economy (GDP/LEI)
- • Government Policy
- • Liquidity & Financial Conditions
17 Market Drivers · 30% Weight
- • Credit Spreads (HY OAS)
- • Market Breadth
- • VIX Term Structure
- • Yield Curve (10y2y)
- • NFCI Leverage
- • Equity Trend
- • Equity Momentum
- + 10 more market & technical factors
Architecture · Narrative
Twenty-Five Factors. Eighty-Plus Live Streams. Proprietary Weightings.
Most regime models claim a factor count. RegimeSignal™ shows the architecture underneath.
The four walk-forward validated signals — BRS, MBS Tier 1, MBS Tier 2, and the Regime Recovery Signal™ — each operate on their own purpose-built factor universe, ranging from approximately 25 to 35 factors per signal, with set composition calibrated to each signal's prediction horizon and target regime event. Those factors are not raw observations. They are the engineered output of 80+ live economic and market data streams flowing continuously from 13 institutional and proprietary sources: FRED macro data, premium market feeds, real-time equity, credit, and volatility prices, energy curve providers, government statistical agencies, geopolitical event databases, and a live three-AI council. Each factor is constructed, normalized, and z-score standardized through a deterministic preprocessing pipeline — no curve fitting, no lookahead, no judgment overlays applied to the quantitative core.
The factor architecture is transparent and audit-ready. The data sources are documented. The methodology is reproducible. The weights — the proprietary L1-regularized coefficients that determine how each signal's factors combine into a single score — are the institutional edge. Developed over three decades. Refined across eight bear cycles (walk-forward OOS validation covers 2000–2025; the 1990 cycle sits in pre-OOS training history). Validated walk-forward at AUC 0.91. And not for disclosure.
Early warning, before consensus.
The RegimeSignal™ framework — four walk-forward validated prediction signals and Bull / Bear Velocity gauges for the S&P 500. Not yet publicly available — join the waitlist to be notified when subscriptions open.