Strategy Card

Macro Regime Sector Rotation (Top 500 Most Traded US Stocks) — strategy card

Spec ID: spec-macro-driven-top500-us-stocks-1764834334 · Generated: 2026-06-05 18:09 UTC

Cluster: Macro Rotation · Sub Cluster: Regime-Based Us Sector Momentum

One-line description

Monthly long-only sector rotation strategy over the 500 most-traded US stocks. It infers macro regimes, tilts sector weights accordingly, then selects high-momentum, high-quality stocks within each sector with volatility-aware sizing.

Why this trade exists

Sector leadership tends to vary across inflation, rates, growth, labor, and volatility regimes because cash-flow duration, cyclicality, balance-sheet sensitivity, and commodity exposure differ materially by industry. A rules-based macro classifier attempts to capture these slow-moving cross-sector risk premia while avoiding purely price-based sector chasing.

Within each favored sector, the strategy emphasizes 12-month momentum excluding the most recent month, sector-relative strength, ROIC, free-cash-flow margin, and earnings revisions. This combines persistent behavioral momentum effects with quality and revision signals that may reduce exposure to financially weak winners. Monthly rebalancing, sector caps, liquidity filters, earnings blackouts, and inverse-volatility sizing are intended to make the signal more implementable in large-cap/liquid US equities.

Algorithm

[code omitted from public view]

Parameters

Param	Value	Notes
Universe	Top 500 most-traded US stocks	Ranked by 1-year dollar volume; stocks only
Backtest window	2020-01-01 to 2025-10-08	Daily bars, monthly rebalance
Macro update frequency	Monthly	Macro inputs lagged by 5 business days
Regime indicators	CPI YoY, 10Y yield, GDP/growth, unemployment/labor, VIX/risk	Implementation may use available macro proxies for some series
Regime rules	Disinflation Risk-On; Reflation Rate-Rise; Stagflation; Risk-Off High-Vol	Ordered conditional macro classifier
Sector base weights	Equal-weight 11 sectors	Converted to biased weights by regime
Sector caps	Min 3%, max 25%	Also max sector exposure 25%
Sector momentum confirmation	126 trading days	Positive sectors boosted 1.1x; negative sectors cut to 0.9x
Stock momentum	252 trading days excluding most recent 21 days	Largest score weight: 0.50
Stock relative strength	6 months vs sector	Score weight: 0.20
Quality / revisions	ROIC 0.15; FCF margin 0.10; earnings revision 0.10	Z-scored by sector; 1% winsorization
Leverage penalty	Net debt / EBITDA > 3: -0.20	Applied to composite score
Selection count	Top 30 per sector	Subject to eligibility filters
Volatility estimator	20 trading days	Used for inverse-vol sizing and vol target
Volatility target	12% annualized	Max leverage 1.0
Max position size	3%	Single-name cap
Turnover control	Min hold 20 days; keep threshold 0.15 score delta	Reduces rebalance churn
Earnings blackout	3 days before, 1 day after	Excludes upcoming earnings within 3 days
Liquidity filters	Price >= $5; 30-day ADV >= $5mm	Additional execution limit: 1% ADV/day
Costs	0.15% round trip	Proportional-to-volume slippage model

Look-ahead audit

#	Concern	Status
1	Macro publication timing	Uses a 5-business-day macro lag; still requires confirmation that vintage/release-date data, not revised final data, were used.
2	Fundamental data availability	ROIC, FCF margin, leverage, and earnings revisions must be point-in-time with realistic filing/vendor delays.
3	Universe construction	Top-500 most-traded universe can introduce survivorship or future-liquidity bias unless membership is reconstructed historically.
4	Earnings blackout	Upcoming earnings dates must come from information known before the rebalance date.
5	Execution realism	1% ADV cap, slippage, and round-trip cost are included, but market impact during stress regimes may be understated.
6	Regime proxy mapping	Some macro variables may be proxied by available database series; mapping should be documented and frozen before testing.

Caveats / known limitations

• Long-only equity exposure remains substantial; the strategy is not market-neutral and can suffer large equity drawdowns.
• Backtest max drawdown is materially larger than the stated 20% drawdown-stop threshold, suggesting either stop implementation differences, gap risk, or insufficient control effectiveness.
• Macro regime rules are hand-specified and may be overfit to recent macro narratives, especially over a short 2020-2025 sample.
• Monthly macro classification can lag rapid regime shifts, particularly during crisis transitions.
• Fundamental and revision signals are sensitive to point-in-time data quality and vendor methodology.
• Sector caps reduce concentration but may also dilute the intended macro tilts.
• High trade count indicates meaningful turnover; realized costs may exceed the modeled 15 bps round trip in stressed or crowded names.

Results

The backtest produced a positive total return of 113.01% over 2020-01-01 to 2025-10-08 with a Sharpe of 0.81, Sortino of 0.82, and profit factor of 1.73 across 3009 trades. The 64.77% win rate is encouraging, but realized volatility was high at 24.09% and the maximum drawdown reached -43.48%, making the risk profile significantly more aggressive than the nominal 12% volatility target would imply. Overall, the signal shows economically plausible return generation, but drawdown control and point-in-time data validation are key follow-ups before further research use.

Backtest metrics snapshot

Metric	Value
Total Return	113.01%
Sharpe	0.81
Sortino	0.82
Calmar	0.32
Max Drawdown	-43.48%
Volatility	24.09%
Win Rate	64.77%
Profit Factor	1.73
Total Trades	3009
Symbols	500 (A, AA, AAL, AAPL, ABBV, ABNB, ABT, ACGL, ACN, ADBE, +490 more)