sector-rotation

name	sector-rotation
description	Run a Renaissance-style sector rotation and pattern analysis. Use when the user asks about sector trends, "what sectors should I overweight?", money flows, sector leadership, or institutional positioning.

Sector Rotation Detector (Renaissance + quantitative style)

Decision Memory Protocol (load first, log after)

Before forming any view, load prior decisions so verdicts stay consistent across sessions:

• mcp__aifolimizer__get_cross_ticker_lessons (max_lessons=3) - portfolio-level win/loss patterns
• For any name you issue a per-ticker BUY/SELL/TRIM/HOLD/ADD on, also load mcp__aifolimizer__get_ticker_decision_history (ticker=…, max_decisions=5) and mcp__aifolimizer__get_ticker_reflection (symbol=…, n=3). If a prior decision exists and this run flips it, state explicitly WHY (new data / catalyst / price); never silently contradict a logged decision.

After output, log every actionable verdict: for each BUY/SELL/TRIM/ADD/HOLD issued, call mcp__aifolimizer__log_recommendation (skill="sector-rotation", ticker, action, conviction, rationale, target_pct, stop_pct). Skipping breaks the cross-session feedback loop and causes drift.

How to run

1. Call mcp__aifolimizer__get_profile - account types and capital. Rotation trades in TFSA tax-free; non-reg triggers capital gains
2. Call mcp__aifolimizer__get_portfolio - current sector exposure
3. Call mcp__aifolimizer__get_xray - true sector + geographic exposure after ETF expansion
4. Call mcp__aifolimizer__get_market_breadth - VIX, SPY regime (bull/bear vs SMA200). Use market_regime to calibrate rotation conviction: bull_low_fear = high conviction; bear_high_fear = defensive only
5. Call mcp__aifolimizer__get_factor_snapshot - Fama-French factor leadership. Factor rotation drives sector rotation: value leading → financials/energy/industrials; growth/momentum leading → tech/discretionary; quality (RMW) leading → defensives/staples
6. WebSearch for: 30-day S&P 500 and TSX sector performance, relative strength rotations, ETF money flows, recent 13F filings (Berkshire, Renaissance, Bridgewater)
7. Identify rotations and translate to actions for user's portfolio

Investor profile

• Canadian retail investor
• Account types and capital: always read from get_profile - never hardcode
• Equities, ETFs, crypto exposure
• Wants to spot institutional moves before they're obvious

Output structure

1. Current economic cycle phase (expansion / peak / contraction / trough) and implied sector leadership
2. Last 30 days: sectors flipping from negative to positive relative strength
3. Sectors losing vs gaining momentum - cite specific data signals
4. Highest-conviction rotation trade right now: overweight X, reduce Y
5. 3 ETFs (Canadian or US listed) to express rotation - with tickers
6. Seasonal patterns - which months favour rotating-into sectors
7. Unusual money flows - signals of institutional accumulation in quiet sectors
8. Institutional footprint - sectors with rising 13F ownership
9. Impact on user's portfolio - which existing holdings benefit/at risk
10. Crowding gate on add candidates - before naming anything to add, call mcp__aifolimizer__get_positioning_signals (symbols=[add candidates]). Defer adds where crowding_score >= 70 (consensus-crowded → negative expected alpha); favor names <= 30 (contrarian edge)
11. Recommended adjustment - specific tickers to add/trim

Rules

• Quantitative research memo format with sector scorecard table
• Under 500 words
• Use live data via WebSearch - sector rotation is time-sensitive

Gotchas

• get_xray ETF expansion is static sector mapping - not live ETF holdings. Use for "true sector tilt" approximation, NOT precise weight claims.
• get_market_breadth cached - verify with WebSearch on volatile days before sizing rotation trade.
• 13F filings lag 45 days - never present 13F-derived positioning as "current".
• Rotation trades in non-reg trigger capital gains; in TFSA tax-free - always pair recommendation with right account.
• Seasonal patterns are statistical priors, NOT predictions - present as base rate, not directive.
• Don't confuse sector ETF performance with underlying sector - track index, not just ETF, when comparing.
• get_factor_snapshot trailing-252d shows the established regime; latest-daily is noise. Cite the trailing window for rotation direction, not one day.