The thesis
Sector leadership in US equities is persistent on horizons of one to twelve months. The sector that led last quarter is more likely than chance to lead next quarter, and the sector that lagged is more likely to keep lagging. Combined with the well-documented Jegadeesh-Titman (1993) cross-sectional momentum effect at the stock level, sector momentum gives you a disciplined top-down framework: pick the right sectors, then pick the right names within them.
Academic basis
The Jegadeesh-Titman 1993 Journal of Finance paper documented that sorting US stocks by trailing 12-2 month returns produces a long-short portfolio with significant positive returns over a one-year horizon. Subsequent work has shown the effect persists at the sector and industry level (Moskowitz-Grinblatt 1999; Asness, Moskowitz, Pedersen 2013). The pullback overlay — entering pullbacks within strong sectors rather than chasing all-time highs — is a practitioner refinement that improves risk-adjusted returns by reducing drawdown depth at entry.
How Alpha Suite implements it
- Weekly sector ranking — 11 GICS sectors are ranked by 6-month and 3-month relative strength; only the top quartile is in scope for long entries.
- Pullback entries — within top-ranked sectors, the model looks for 5–10% pullbacks to a key moving average (50-day or 21-day), with volume confirmation on the bounce.
- Mean-reversion overlay — for the bottom-quartile sectors, the model can flag oversold mean-reversion candidates separately, but at smaller position size.
- Regime-aware sizing — in defensive macro regimes (defined by VIX, credit, breadth), sector momentum allocations scale down to 40–60% of normal; in trending regimes, they scale up to 100%.
When it fires
Sector momentum is a regime strategy. It performs well in trending markets where leadership is stable and pulls back during regime transitions when leadership rotates. The Alpha Suite macro regime filter automatically reduces sector-momentum sizing during volatility spikes or breadth deterioration to avoid sizing into the worst part of a rotation.
What it does not catch: Sudden sector regime shifts (think March 2020 or January 2022) where leadership flips in days, not months. The model adapts on a weekly cadence; faster shifts cost it some performance until the new ranking is reflected.
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