US Sector Rotation Monitor
Systematic Sector & Industry Leadership Intelligence. This page documents the model architecture used by the current production release without modifying the quantitative engine.
1. Purpose and Scope
The monitor ranks eleven US sector ETFs and a separate universe of industry ETFs. It combines relative momentum, absolute trend, market internals, macro context and parent-sector confirmation. The model is designed for cross-sectional research and monitoring; it is not a personalized portfolio, probability forecast or execution system.
2. Sector Universe
The core universe comprises the eleven US sector ETFs: XLK, XLC, XLY, XLP, XLE, XLF, XLV, XLI, XLB, XLRE and XLU. SPY is the primary market benchmark. Additional factor and breadth ETFs are used for internal confirmation.
3. Sector Score Architecture
The sector score is a robust weighted average. Missing non-critical components are ignored and remaining weights are renormalized. A minimum available-weight threshold is required before a score is published.
| Component | Raw coefficient | Treatment |
|---|---|---|
| rel_mom_63_z | 0.28 | Renormalized over available signals |
| rel_mom_21_z | 0.16 | Renormalized over available signals |
| rel_mom_126_z | 0.12 | Renormalized over available signals |
| trend_distance_z | 0.14 | Renormalized over available signals |
| abs_mom_63_z | 0.10 | Renormalized over available signals |
| abs_mom_126_z | 0.06 | Renormalized over available signals |
| trend_health_score | 0.08 | Renormalized over available signals |
| volume_impulse_z | 0.04 | Renormalized over available signals |
| sector_macro_tailwind | 0.12 | Renormalized over available signals |
4. Score Scale and States
The raw score is clipped and transformed to a 0–100 scale, then smoothed with a five-observation exponential moving average. State bands are:
| State | 0–100 range |
|---|---|
| Leading | ≥ 71.25 |
| Improving | 57.50 to 71.25 |
| Neutral | 42.50 to 57.50 |
| Weakening | 28.75 to 42.50 |
| Lagging | < 28.75 |
5. Industry Drilldown
Industry ETFs are scored independently from the sector core. Each industry is evaluated versus SPY and versus its parent-sector ETF. This layer is used to distinguish confirmed, narrow, hidden and divergent leadership.
| Industry component | Weight |
|---|---|
| Market relative momentum 3M | 0.24 |
| Market relative momentum 1M | 0.10 |
| Market relative momentum 6M | 0.08 |
| Parent relative momentum 3M | 0.25 |
| Parent relative momentum 1M | 0.08 |
| Absolute momentum 3M | 0.10 |
| Trend distance | 0.07 |
| Trend health | 0.06 |
| Volume impulse | 0.02 |
6. RRG and Momentum Maps
The Relative Rotation Graph uses standardized relative-strength level and relative momentum versus SPY. It is a phase diagnostic, not the primary score. The Sector Momentum Map uses the smoothed 0–100 score on the horizontal axis and its 21-day change on the vertical axis.
7. Macro and Market Confirmation
Macro variables include rates, curve, credit spreads, volatility, oil, the broad US dollar, financial conditions and Federal Reserve balance-sheet data. Market internals include semiconductor, Nasdaq, high-beta, equal-weight, small-cap and cyclical/defensive relative ratios. These blocks provide confirmation and context; they do not override the sector score mechanically.
8. Data Sources and Freshness
ETF prices and volumes are sourced from Tiingo. Macro data are sourced from FRED, with local/FRED stitching for selected ICE BofA option-adjusted spreads. The live monitor reports the effective market-data date separately from the UTC generation timestamp.
9. Model Confidence
Model Confidence is a dashboard-readiness diagnostic rather than a predictive probability. It combines available signal weight, data freshness, cross-sectional dispersion and internal confirmation.
10. Limitations
- ETF composition, sector definitions and industry exposures can change through time.
- Macroeconomic series may be revised and are not fully point-in-time unless explicitly reconstructed.
- Relative-momentum signals can reverse rapidly in high-volatility regimes.
- Industry ETFs have different inception dates, liquidity profiles and concentration risks.
- Scores are research classifications, not guaranteed forward-return forecasts.
- Transaction costs, taxes, implementation constraints and investor-specific suitability are outside the model.