momentum-scanner

name	momentum-scanner
description	Scan portfolio holdings for 12-month price momentum and 52-week high proximity. Use when user asks "which stocks have momentum?", "rank my holdings by performance", "momentum scan", "12-month winners and losers", "52-week high analysis", "which momentum laggards should I trim?", or "show momentum signals".
requires_profile	true

Momentum Scanner (12-Month Momentum + 52-Week High Effect)

Research basis

Jegadeesh & Titman (1993): Past 12-month winners outperform losers by 12.01% annually. Effect persists independently of beta, size, or industry. Strongest version: skip most-recent month (reversal noise), rank on months 2-12.

George & Hwang (2004): Stocks within 10% of 52-week high earn ~1.23%/month long-short vs stocks far from high. Mechanism: anchoring bias - investors slow to push past prior resistance, so nearness predicts continuation.

Combined signal: High 12m momentum AND near 52wk high = double confirmation. Strongest continuation setup.

Stage 0 - Decision Memory (load FIRST)

Before analysis, load prior decisions so verdicts stay consistent across sessions:

• mcp__aifolimizer__get_cross_ticker_lessons with max_lessons=3 - portfolio-level win/loss patterns
• For any name you issue a per-ticker BUY/SELL/TRIM/HOLD on, also load mcp__aifolimizer__get_ticker_decision_history (ticker=…, max_decisions=5) and mcp__aifolimizer__get_ticker_reflection (symbol=…, n=3).

Reconciliation rule: if a prior decision exists and your new read flips it, state explicitly WHY it changed (new data / catalyst / price move). Never silently contradict a logged decision - that drift is exactly what this prevents.

How to run

1. Call mcp__aifolimizer__get_profile - account types, capital
2. Call mcp__aifolimizer__get_portfolio - all holdings, current weights
3. Call mcp__aifolimizer__get_technicals for all held symbols - pct_from_52w_high, pct_from_52w_low, minervini_score, technical_score, trend
4. Call mcp__aifolimizer__backtest_portfolio with strategy="buy_hold" for 12-month return per symbol
5. Call mcp__aifolimizer__get_positioning_signals for top 8 holdings - crowding check before any add signal
6. Call mcp__aifolimizer__get_factor_snapshot - is the MOMENTUM FACTOR itself working? Mom trailing-252d positive = regime tailwind for this whole scan; negative = momentum regime weak, downgrade all continuation conviction one notch
7. Call mcp__aifolimizer__get_search_interest with keywords=[top 3-5 momentum names] - search-demand confirmation. Rising interest + price momentum = retail fuel; but cross with crowding (surge + consensus = late-stage, suppress add)

Call steps 3-7 in parallel after step 2 resolves.

Momentum scoring

For each holding, compute composite momentum score (0-100):

Component	Weight	Signal
12m return rank (percentile within portfolio)	50%	Higher = stronger
52wk high proximity (1 - abs(pct_from_52w_high)/100)	30%	Closer to high = stronger
Minervini score / 7	20%	Stage 2 breakout = strongest

Labels:

• Score ≥ 70: Strong Momentum - continuation bias
• Score 45-69: Mixed - hold, no directional edge
• Score < 45: Weak / Laggard - trim candidate per J&T framework

Output structure

1. Momentum ranking table

Render markdown table, sorted by composite score descending:

Ticker	Weight %	12m Return	vs 52wk High	Minervini	Composite	Label

2. Strong momentum plays (≤5)

Holdings with score ≥ 70. Per line:

TICKER · +XX% 12m · X% from 52wk high · Minervini N/7 · [Hold / Add small if not crowded]

Cross-check crowding: if crowding_score ≥ 70 (consensus), suppress add signal - state "momentum real but consensus already long."

3. Laggards (score < 45)

Per line:

TICKER · -XX% 12m · XX% below 52wk high · account: TFSA/Non-Reg · action: trim / watch / exit

For Non-Reg positions at a loss: flag tax-loss harvest opportunity. For TFSA positions at a loss: trim - no tax benefit for waiting, capital better deployed in momentum names.

4. Rebalance signal

If total weight in Strong Momentum names < 40% of portfolio: "Momentum tilt underweight - consider trimming bottom-quintile laggards and rotating into top-quintile names." If total weight in Weak names > 30%: "Drag risk - laggards consuming capital that momentum names would compound faster."

After output - log decisions

For each Strong Momentum name flagged ADD and each Laggard flagged TRIM/EXIT, call mcp__aifolimizer__log_recommendation with action (ADD/HOLD/TRIM/SELL), conviction (HIGH/MED/LOW), target_pct + stop_pct (% from entry), 1-line thesis citing composite score + 52wk-high proximity, skill="momentum-scanner". Skip pure HOLDs in mid-band. Feeds forward win-rate / track-record loop.

Rules

• Always call get_profile first - never hardcode accounts or capital
• 12m return from backtest_portfolio buy_hold - do NOT use cost basis return (that's entry-date dependent, not trailing 12m)
• 52wk proximity from get_technicals directly - pct_from_52w_high is negative (stock below high). Nearness = abs(pct_from_52w_high) closer to 0
• Under 500 words
• Skip crypto for 12m momentum ranking - crypto volatility overwhelms equity signals. Note separately.

Gotchas

• backtest_portfolio returns annualized return for buy_hold - confirm lookback covers 12 months. If portfolio position held < 12 months, return is since-inception, not full 12m. Flag with "held < 12m - partial signal."
• pct_from_52w_high is typically negative (current price below high). If 0 or positive, stock is at or above 52wk high - maximum George & Hwang signal. Do not treat as data error.
• Momentum strategies have well-documented January reversal - laggards historically bounce in January. If analysis runs in December-January, note "January reversal risk - reduce trim urgency for laggards."
• J&T skip-1-month rule: skip the most recent month return (month 1) when computing 12m momentum signal to avoid short-term reversal contamination. backtest_portfolio buy_hold returns full period - acknowledge this approximation.
• ETFs (XEQT, VFV, etc.) have momentum but different dynamics than single stocks. They don't exhibit the same earnings-driven drift. Rank them separately or flag.
• Crowding data sparse for TSX names - label "neutral" if crowding_score null, don't suppress signal on absence of data.
• Minervini score null for tickers with <200 days price history. Score as 0/7, mark "insufficient history."
• get_factor_snapshot Mom is the US momentum factor - a negative reading is a regime caution for the whole scan, not a per-ticker signal. get_search_interest is rate-limited (429) and US-name biased; if it errors, proceed without it - it's confirmation, not a gate.