# QUEUE-07 — Turnover relief: weekly rebalance vs daily (next cost lever after n_drop 1)

**Status:** QUEUED · **Priority:** P1 · **Effort:** custom strategy module + run

## Hypothesis (prove)
n_drop 2→1 proved the cost/turnover frontier is the binding constraint
(EVIDENCE#015, ch.03/ch.09: identical IC/RankIC, net flips −3.21% → +2.13%).
The next lever in the same direction: rebalance the TopkDropout book only
**weekly** (e.g. on Mondays) instead of daily — cutting forced churn further
should lift net performance at the same signal quality.

Source: `book/references/chat-ideas.md` ("weekly rebalance" among the turnover
reduction ideas), ch.09 claim inventory.

## Change vs exp-26 reference (ONE variable)
- **Strategy**: daily TopkDropout (topk 10, n_drop 1) → custom
  `WeeklyRebalanceDropoutStrategy` that recomputes the target book once per
  week and otherwise holds (no-trade buffer band for small deltas).
- All signal/config unchanged.

## Acceptance
- `total_cost`/turnover strictly below the reference AND `net_IR > 0.21` AND
  `net_ann_return > +2.13%`.
- Reference numbers to beat: turnover ~0.74 (round-3 live), est. ~20% daily
  book turnover at topk10/n_drop2 (pre-clean-lake estimate).

## Execution prerequisites
1. New contrib module `tac_qlib/contrib/strategy/weekly_rebalance.py`
   (`WeeklyRebalanceDropoutStrategy` subclassing `TopkDropoutStrategy`, trade
   only when the trade calendar day is the week's first trading day), copy to
   the venv site-packages copy.
2. Workflow YAML wiring the strategy.
3. Trace + run + snapshot.

## Sibling (deferred)
No-trade buffer band and notional-vs-qty order sizing are variants of the same
cost lever; queue them only if Q07 reproduces positively.