Smart Money · per-pair browser · obs May 08
Every (broker × ticker) Smart Money score
Each row is one (broker, ticker) pair scored at the latest obs_date.
sm_score = total_roi × materiality × directional_score × win_rate_cycles.
Click a column header to sort. Filters narrow the row set; sorting still works on the visible rows.
Pairs Scored
1
matching current filters
Showing
1
capped at 1000
Gates
PASSED
lifetime ∈ (1d, 365d) · ≥1B IDR buy · roi ≥ 0
Scope
All
broker geography
| # | Broker | Ticker | sm_score | total_roi | materiality | directional | win_rate | profit_factor | realized (B) | unrealized (B) | total P&L (B) | total_idr_buy (B) | role | buy_share | edge_20d | lead_lag_20d | days→peak | entry_pct | n_events | n_sells | lifetime | scope | last_event |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | AZ | CITA | 0.01 | 10.9% | 0.11 | 1.00 | 65.4% | 1.31 | 1.03 B | -0.24 B | 0.80 B | 7.29 B | BALANCED | 47.4% | 0.004 | -0.01 | 20 | 48.2% | 278 | 159 | 14d | LOCAL | May 08 |
Column legend
- sm_score = total_roi × materiality × directional_score × win_rate_cycles
- total_roi = (realized + unrealized) IDR ÷ total_idr_buy, on Weighted-Avg-Cost basis
- materiality = max(total_idr_buy/1B, mean_nbs_gross × 100) — size component
- directional = sigmoid of
typical_ratio(median |net|/gross over active days) - win_rate = WIN/(WIN+LOSS) at the sell-event level (WAC vs sell price)
- profit_factor = gross_wins ÷ gross_losses (capped at 10)
- edge_20d = peer-relative alpha vs top-20 brokers, 20d window
- lead_lag_20d = Pearson(net flow, t+20d return) — forward-looking timing
- days→peak = trading days from buy event to next 60d peak
- entry_pct = share of (peak − 60d-low) move captured at entry
- buy_share = total_idr_buy ÷ (total_idr_buy + total_idr_sell) over the active window
- scope = LOCAL or FOREIGN per IDX broker directory group