Smart Money · per-pair browser · obs Sep 07

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

matching current filters

Showing

capped at 1000

Top sm_score

0.09

GWSA · PG

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	PG	GWSA	0.09	29.3%	0.33	1.00	84.6%	10.00	1.21 B	0.16 B	1.36 B	4.66 B		—	0.171	-0.03	12	52.6%	41	13	34d	LOCAL	Sep 04
2	YP	GWSA	0.01	11.6%	0.14	1.00	50.8%	6.55	1.32 B	0.05 B	1.37 B	11.83 B		—	0.003	-0.00	29	60.3%	615	524	12d	FOREIGN	Sep 07

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