| name | sector-rotation |
| description | Rotate between sectors based on economic and market cycles. Use when optimizing sector allocation, understanding cyclical trends, or positioning for macro shifts. |
| license | Apache-2.0 |
| metadata | {"author":"ske-labs","version":"4.0"} |
Sector Rotation
Rotate sector allocation based on economic cycle phase, relative strength, and macro catalysts.
Economic Cycle Sectors
| Phase hypothesis | Economy | Sectors often evaluated |
|---|
| Early Expansion | Recovery begins | Financials, Consumer Discretionary, Information Technology |
| Mid Expansion | Growth accelerates | Industrials, Materials, Tech |
| Late Expansion | Growth peaks | Energy, Materials, Financials |
| Contraction | Slowdown/recession | Utilities, Healthcare, Consumer Staples |
Treat this map as an economic hypothesis, not a deterministic allocation rule. Classifications, constituents, and sensitivities change.
Cyclical (economy-sensitive): Consumer Discretionary, Financials, Industrials, Materials, Energy, Information Technology
Defensive (recession-resistant): Utilities, Healthcare, Consumer Staples, Real Estate
Rotation Signals
| Signal | Indicates |
|---|
| Yield curve steepening | Early cycle -- favor cyclicals |
| Yield curve flattening | Late cycle -- rotate to defensives |
| Fed cutting rates | Early cycle starting |
| Fed raising rates | Late cycle |
| Commodities rallying | Late cycle inflation |
Sector ETFs
| Sector | ETF |
|---|
| Technology | XLK |
| Healthcare | XLV |
| Financials | XLF |
| Consumer Discretionary | XLY |
| Consumer Staples | XLP |
| Energy | XLE |
| Industrials | XLI |
| Utilities | XLU |
| Materials | XLB |
| Communication Services | XLC |
| Real Estate | XLRE |
Workflow
1. Build Relative Strength Rankings
get_candles(symbol=<sector_etf>, exchange=<exchange>, interval="1D", count=260)
get_candles(symbol="SPY", exchange=<exchange>, interval="1D", count=260)
Use the current 11-sector GICS universe. Rank predeclared total-return horizons relative to the benchmark, with volatility, drawdown, liquidity, and turnover. Prevent look-ahead by using classifications and constituents known on each date; compare with equal-weight and benchmark baselines.
2. Research Macro Context
get_financial_news(topic="sector rotation economic cycle <current year>", max_results=15)
get_economics_calendar(from_date=<start>, to_date=<end>, impact="high")
Identify cycle phase, Fed policy direction, and upcoming macro catalysts that could shift rotation.
3. Detect Correlation Regime Shifts
When normally uncorrelated sectors start moving together, a macro factor is dominating individual sector dynamics:
- Tech and Utilities both rising strongly = macro factor (Fed policy, liquidity) overriding sector rotation
- All sectors falling together = risk-off regime, defensive positioning matters less
- Defensive and cyclical diverging sharply = normal rotation is active, standard cycle strategy applies
When correlation regime shifts are detected, prioritize macro analysis over traditional rotation signals.
4. Report Recommendations
Provide the as-of date, classification universe, relative-strength/volatility table, uncertain cycle assessment, turnover/tax assumptions, and proposed weights or no change. Derive weights from the portfolio mandate and concentration limits rather than always selecting three winners and losers.
Evidence and Validation
- Treat the setup as a testable hypothesis, not a prediction. Define thresholds, entry, invalidation, and exit before evaluating outcomes.
- Calibrate on the same instrument, venue, session, and timeframe. Use closed candles and a held-out or walk-forward sample; record every variant tried.
- Include spread, fees, slippage, borrow or funding, partial fills, and latency. Reject the setup when net expectancy is not positive or depends on one narrow parameter.
- Return observed inputs, missing data, cost assumptions, entry, invalidation, exit, and a valid, watch, or no-trade status.
- Research basis: Moskowitz & Grinblatt documented industry momentum; use the current GICS methodology for classification rather than assuming a fixed business-cycle map.
Key Rules
- Enforce the portfolio mandate's sector and issuer concentration limits; do not invent a universal cap.
- Rebalance on a fixed schedule and include turnover, spread, taxes, and tracking error.
- NEVER rely solely on historical cycle patterns -- confirm with current relative strength data and macro context
- Choose and validate the review frequency before testing.
- When all sectors correlate (crisis mode), standard rotation logic breaks down -- prioritize capital preservation
Related Skills
- market-correlation-trading -- Cross-asset correlations reveal regime shifts
- economic-calendar-trading -- Fed and macro data are primary rotation catalysts
