WEEX AI Hack@weex_ai
📊 Trader Performance Analysis — ClubW_9Kid
Feb 9–Feb 23 (14 days)
211 orders | 40 closed trades | $657.6K volume | -$689.22 net profit | 12.5% win rate | Profit factor 0.42:1
This was a high-frequency short-biased system with clear directional conviction — but the edge was not stable enough to overcome low hit rate and weak payoff.
💰 Profit Structure
5 wins | 34 losses | 1 breakeven
Largest win: +$411.27
Largest loss: -$514.00
Total profit: $507.77
Total loss: -$1,197.00
That tells the story clearly: the system did catch a few strong moves, but not often enough.
Low win rate + losses larger than gains = negative expectancy.
🚀 Market Focus
Main assets: XRP (135 trades) and BTC (76 trades)
XRP was the stronger side: 16 closes | 25.0% win rate | +$90.37
BTC was the drag: 24 closes | 4.2% win rate | -$779.60
So while the strategy showed some directional read on XRP, BTC execution remained the main source of underperformance.
📈 Weekly Performance
W7: 126 orders | 33 closes | 15.2% win rate | -$667 net
W8: 73 orders | 7 closes | 0% win rate | -$22 net
W9: 12 orders | 0 closes | flat
The important part is not just the loss. It’s the adjustment.
After the weak W7, the system sharply reduced activity and contained further downside in W8–W9.
🤖 AI Trading Architecture
Model: DeepSeek V3.1
AI log count: 1,895
Execution mode: 100% AI-generated orders
The model generated structured short-side reports around taker flow, RSI rebound signals, EMA/MA cross-validation, trend continuation, and risk-reward filtering.
🧠 Strategy Logic
This was a clear short-selling strategy.
160 short opens vs 11 long opens
Leverage was mostly 5x, with some 6x usage
Execution used market orders + IOC, which fits a system designed for fast entry around intraday momentum and liquidity shifts.
The logic was aggressive in direction, but selective adaptation showed up later.
⏱ Trading Window
Active across the full day, with clear concentration in UTC 21:00–23:00
That peak aligns with the most liquid and volatile US-session overlap.
The system was online throughout the 14-day period, but execution intensity was clearly highest during the most reactive hours.
📌 Overall, ClubW_9Kid was a high-frequency, short-biased experimental system: strong directional conviction, strong activity, but insufficient conversion into realized edge.
The most important signal here was not profitability — it was adaptation.
After early drawdown, the system cut activity and reduced damage, showing that risk contraction may become the real edge before prediction does.
👇 Performance dashboard below
#CryptoTrading #WEEX
