0x1d0701fcdd71ce40e1fe69140f81aee585971622
0x1d0701fcdd71ce40e1fe69140f81aee585971622
Wallet digest
Activity score
36/100
Performance measurable
Open positions
4
Open notional
$3.01
Total PnL
$-21.14
Realised
$-11.94
Win rate
0%
3 closed
Largest open positions
- NO
Will the highest temperature in Buenos Aires be 18°C or higher on June 1?
2 shares @ 98.7¢·now 99.6¢·exp Jun 1, 2026$2.46
$0.02
- YES
Will the highest temperature in New York City be between 82-83°F on June 1?
357 shares @ 1.8¢·now 0.1¢·exp Jun 1, 2026$0.54
$-5.76
- YES
Will the lowest temperature in New York City be between 58-59°F on May 31?
28 shares @ 9.3¢·now 0.1¢·exp May 31, 2026$0.01
$-2.61
- YES
Will the lowest temperature in New York City be between 48-49°F on May 31?
4 shares @ 21.2¢·now 0.1¢·exp May 31, 2026$0.00
$-0.85
Recent activity
- REDEEMWill the highest temperature in Shanghai be 32°C on May 31?$0.00May 31, 19:50 UTC
- REDEEMWill the highest temperature in Shanghai be 31°C on May 31?$22.55May 31, 16:46 UTC
- REDEEMWill the highest temperature in Shanghai be 25°C on May 31?$12.94May 31, 16:44 UTC
- TRADESELLWill the highest temperature in Buenos Aires be 18°C or higher on June 1?$0.57May 30, 17:05 UTC
- TRADESELLWill the highest temperature in Buenos Aires be 18°C or higher on June 1?$0.08May 30, 16:30 UTC
- TRADEBUYWill the highest temperature in New York City be between 82-83°F on June 1?$1.10May 30, 16:09 UTC
- TRADEBUYWill the highest temperature in New York City be between 82-83°F on June 1?$1.10May 30, 16:09 UTC
- TRADEBUYWill the highest temperature in New York City be between 82-83°F on June 1?$1.10May 30, 15:49 UTC
- TRADEBUYWill the highest temperature in New York City be between 82-83°F on June 1?$1.10May 30, 15:48 UTC
- TRADEBUYWill the highest temperature in New York City be between 82-83°F on June 1?$1.10May 30, 15:47 UTC
- TRADEBUYWill the highest temperature in New York City be between 82-83°F on June 1?$1.10May 30, 15:47 UTC
- TRADESELLWill the highest temperature in Chicago be 74°F or higher on May 30?$8.92May 30, 15:43 UTC
- TRADESELLWill the lowest temperature in New York City be 51°F or below on June 1?$0.26May 30, 14:38 UTC
- TRADESELLWill the lowest temperature in New York City be 51°F or below on June 1?$0.11May 30, 14:37 UTC
- TRADEBUYWill the lowest temperature in New York City be 51°F or below on June 1?$1.10May 30, 14:32 UTC
- TRADESELLWill the lowest temperature in New York City be 51°F or below on June 1?$0.14May 30, 14:31 UTC
- TRADESELLWill the lowest temperature in New York City be 51°F or below on June 1?$0.09May 30, 14:31 UTC
- TRADESELLWill the lowest temperature in New York City be 51°F or below on June 1?$0.04May 30, 14:28 UTC
- TRADEBUYWill the lowest temperature in New York City be 51°F or below on June 1?$1.10May 30, 14:28 UTC
- TRADESELLWill the lowest temperature in New York City be 51°F or below on June 1?$0.04May 30, 14:28 UTC
Persistent ledger timeline
persistentNo trades for this wallet in Orrery's persistent ledger yet. The whale-ingest cron writes ≥ $5k trades every 10 minutes; check back after a recovery window.
Ledger intelligence
persistent7d volume
$0.00
0 trades
30d volume
$0.00
0 trades
Buy share
50%
Sample
low
0 ledger trades
No persistent whale trades for this wallet yet. The live Data API score above can still be useful, but the durable ledger sample is empty.
Profile dimensions
Trade count + how recently they were active. Low = dormant.
How trustworthy the win-rate number is, based on sample size of closed markets.
Share of trades concentrated in their top category.
Share of positions taken while the market was still uncertain (30–70¢) rather than after direction was obvious.
How risky to blindly copy. Higher = riskier — large size, single-position exposure, or thin win-rate sample.
- Trades (all time)
- 44
- Avg trade size
- $1.80
- Top category
- —
- Category concentration
- 0%
- First seen
- May 30, 11:06 UTC
- Last active
- May 31, 19:50 UTC
- Win rate sample
- 3 closed
The single Activity score is kept for the leaderboard sort. The five dimensions above are the canonical read — copy-risk bar is inverted so green is always "better for the user".